[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: metal/moe.metal

```metal
acc2[1] += yl[i+ 9] * (qs[i/2] & 0x0c00);
                        acc1[2] += yl[i+16] * (qs[i/2] & 0x0030);
                        acc2[2] += yl[i+17] * (qs[i/2] & 0x3000);
                        acc1[3] += yl[i+24] * (qs[i/2] & 0x00c0);
                        acc2[3] += yl[i+25] * (qs[i/2] & 0xc000);
                    }
                    float dall = dh[0];
                    float dmin = dh[1] * 1.f/16.f;
                    sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc2[0]) * (sc[0] & 0xF) * 1.f/ 1.f +
                                         (acc1[1] + 1.f/256.f * acc2[1]) * (sc[2] & 0xF) * 1.f/ 4.f +
                                         (acc1[2] + 1.f/256.f * acc2[2]) * (sc[4] & 0xF) * 1.f/16.f +
                                         (acc1[3] + 1.f/256.f * acc2[3]) * (sc[6] & 0xF) * 1.f/64.f) -
                                 dmin * (sumy[0] * (sc[0] & 0xF0) + sumy[1] * (sc[2] & 0xF0) +
                                         sumy[2] * (sc[4] & 0xF0) + sumy[3] * (sc[6] & 0xF0));
                }

                qs += args.nb01/2;
                sc += args.nb01;
                dh += args.nb01/2;
            }

            y4 += 4 * QK_K;
        }
    }

    device float * dst_f32 = (device float *)(dst + (uint64_t)token * args.nb1);
    for (int row = 0; row < nr0 && first_row + row < args.ne0; row++) {
        const float sum_all = simd_sum(sumf[row]);
        if (tiisg == 0) dst_f32[first_row + row] = sum_all;
    }

    (void)shmem;
    (void)tiitg;
    (void)tgpig;
}

kernel void kernel_mul_mv_id_q4_K_sum6_f32(
        constant ds4_metal_args_mul_mv_id & args,
        device const char * src0s,
        device const char * src1,
        device       char * dst,
        device const char * ids,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3  tgpig[[threadgroup_position_in_grid]],
        ushort tiitg[[thread_index_in_threadgroup]],
        ushort tiisg[[thread_index_in_simdgroup]],
        ushort sgitg[[simdgroup_index_in_threadgroup]]) {
    const short NSG = FC_mul_mv_nsg;
    const short nr0 = N_R0_Q4_K;
    const int nb = args.ne00 / QK_K;
    const int first_row = (tgpig.x * NSG + sgitg) * nr0;
    const uint token = tgpig.y;
    device const int32_t *token_ids = (device const int32_t *)(ids + (uint64_t)token * args.nbi1);
    device const char *token_src1 = src1 + (uint64_t)token * args.nb12;

    constexpr uint16_t kmask1 = 0x3f3f;
    constexpr uint16_t kmask2 = 0x0f0f;
    constexpr uint16_t kmask3 = 0xc0c0;

    const short ix = tiisg / 8;
    const short it = tiisg % 8;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: metal/moe.metal

```metal
acc2[1] += yl[i+ 9] * (qs[i/2] & 0x0c00);
                        acc1[2] += yl[i+16] * (qs[i/2] & 0x0030);
                        acc2[2] += yl[i+17] * (qs[i/2] & 0x3000);
                        acc1[3] += yl[i+24] * (qs[i/2] & 0x00c0);
                        acc2[3] += yl[i+25] * (qs[i/2] & 0xc000);
                    }
                    float dall = dh[0];
                    float dmin = dh[1] * 1.f/16.f;
                    sumf[row] += dall * ((acc1[0] + 1.f/256.f * acc2[0]) * (sc[0] & 0xF) * 1.f/ 1.f +
                                         (acc1[1] + 1.f/256.f * acc2[1]) * (sc[2] & 0xF) * 1.f/ 4.f +
                                         (acc1[2] + 1.f/256.f * acc2[2]) * (sc[4] & 0xF) * 1.f/16.f +
                                         (acc1[3] + 1.f/256.f * acc2[3]) * (sc[6] & 0xF) * 1.f/64.f) -
                                 dmin * (sumy[0] * (sc[0] & 0xF0) + sumy[1] * (sc[2] & 0xF0) +
                                         sumy[2] * (sc[4] & 0xF0) + sumy[3] * (sc[6] & 0xF0));
                }

                qs += args.nb01/2;
                sc += args.nb01;
                dh += args.nb01/2;
            }

            y4 += 4 * QK_K;
        }
    }

    device float * dst_f32 = (device float *)(dst + (uint64_t)token * args.nb1);
    for (int row = 0; row < nr0 && first_row + row < args.ne0; row++) {
        const float sum_all = simd_sum(sumf[row]);
        if (tiisg == 0) dst_f32[first_row + row] = sum_all;
    }

    (void)shmem;
    (void)tiitg;
    (void)tgpig;
}

kernel void kernel_mul_mv_id_q4_K_sum6_f32(
        constant ds4_metal_args_mul_mv_id & args,
        device const char * src0s,
        device const char * src1,
        device       char * dst,
        device const char * ids,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3  tgpig[[threadgroup_position_in_grid]],
        ushort tiitg[[thread_index_in_threadgroup]],
        ushort tiisg[[thread_index_in_simdgroup]],
        ushort sgitg[[simdgroup_index_in_threadgroup]]) {
    const short NSG = FC_mul_mv_nsg;
    const short nr0 = N_R0_Q4_K;
    const int nb = args.ne00 / QK_K;
    const int first_row = (tgpig.x * NSG + sgitg) * nr0;
    const uint token = tgpig.y;
    device const int32_t *token_ids = (device const int32_t *)(ids + (uint64_t)token * args.nbi1);
    device const char *token_src1 = src1 + (uint64_t)token * args.nb12;

    constexpr uint16_t kmask1 = 0x3f3f;
    constexpr uint16_t kmask2 = 0x0f0f;
    constexpr uint16_t kmask3 = 0xc0c0;

    const short ix = tiisg / 8;
    const short it = tiisg % 8;
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: metal/moe.metal

```metal
constexpr uint16_t kmask1 = 0x3f3f;
    constexpr uint16_t kmask2 = 0x0f0f;
    constexpr uint16_t kmask3 = 0xc0c0;

    const short ix = tiisg / 8;
    const short it = tiisg % 8;
    const short iq = it / 4;
    const short ir = it % 4;

    float sumf[nr0] = {0.f};
    uint16_t sc16[4];
    thread const uint8_t *sc8 = (thread const uint8_t *)sc16;

    for (int expert_slot = 0; expert_slot < 6; expert_slot++) {
        const int32_t expert = token_ids[expert_slot];
        device const block_q4_K *x =
            (device const block_q4_K *)(src0s + expert * args.nb02 + first_row * args.nb01);
        device const float *y = (device const float *)(token_src1 + expert_slot * args.nb11);
        device const float *y4 = y + ix * QK_K + 64 * iq + 8 * ir;

        for (int ib = ix; ib < nb; ib += 4) {
            float yl[16];
            float yh[16];
            float4 sumy = {0.f, 0.f, 0.f, 0.f};

            for (short i = 0; i < 8; ++i) {
                yl[i + 0] = y4[i +   0]; sumy[0] += yl[i + 0];
                yl[i + 8] = y4[i +  32]; sumy[1] += yl[i + 8];
                yh[i + 0] = y4[i + 128]; sumy[2] += yh[i + 0];
                yh[i + 8] = y4[i + 160]; sumy[3] += yh[i + 8];
            }

            device const uint16_t *sc = (device const uint16_t *)x[ib].scales + iq;
            device const uint16_t *q1 = (device const uint16_t *)x[ib].qs + 16 * iq + 4 * ir;
            device const half *dh = &x[ib].d;

            for (short row = 0; row < nr0; row++) {
                if (first_row + row < args.ne0) {
                    sc16[0] = sc[0] & kmask1;
                    sc16[1] = sc[2] & kmask1;
                    sc16[2] = ((sc[4] >> 0) & kmask2) | ((sc[0] & kmask3) >> 2);
                    sc16[3] = ((sc[4] >> 4) & kmask2) | ((sc[2] & kmask3) >> 2);

                    device const uint16_t *q2 = q1 + 32;

                    float4 acc1 = {0.f, 0.f, 0.f, 0.f};
                    float4 acc2 = {0.f, 0.f, 0.f, 0.f};

                    FOR_UNROLL (short i = 0; i < 4; ++i) {
                        acc1[0] += yl[2 * i + 0] * (q1[i] & 0x000F);
                        acc1[1] += yl[2 * i + 1] * (q1[i] & 0x0F00);
                        acc1[2] += yl[2 * i + 8] * (q1[i] & 0x00F0);
                        acc1[3] += yl[2 * i + 9] * (q1[i] & 0xF000);
                        acc2[0] += yh[2 * i + 0] * (q2[i] & 0x000F);
                        acc2[1] += yh[2 * i + 1] * (q2[i] & 0x0F00);
                        acc2[2] += yh[2 * i + 8] * (q2[i] & 0x00F0);
                        acc2[3] += yh[2 * i + 9] * (q2[i] & 0xF000);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Explain what this code does and identify the inference stage it belongs to.

File: metal/moe.metal

```metal
constexpr uint16_t kmask1 = 0x3f3f;
    constexpr uint16_t kmask2 = 0x0f0f;
    constexpr uint16_t kmask3 = 0xc0c0;

    const short ix = tiisg / 8;
    const short it = tiisg % 8;
    const short iq = it / 4;
    const short ir = it % 4;

    float sumf[nr0] = {0.f};
    uint16_t sc16[4];
    thread const uint8_t *sc8 = (thread const uint8_t *)sc16;

    for (int expert_slot = 0; expert_slot < 6; expert_slot++) {
        const int32_t expert = token_ids[expert_slot];
        device const block_q4_K *x =
            (device const block_q4_K *)(src0s + expert * args.nb02 + first_row * args.nb01);
        device const float *y = (device const float *)(token_src1 + expert_slot * args.nb11);
        device const float *y4 = y + ix * QK_K + 64 * iq + 8 * ir;

        for (int ib = ix; ib < nb; ib += 4) {
            float yl[16];
            float yh[16];
            float4 sumy = {0.f, 0.f, 0.f, 0.f};

            for (short i = 0; i < 8; ++i) {
                yl[i + 0] = y4[i +   0]; sumy[0] += yl[i + 0];
                yl[i + 8] = y4[i +  32]; sumy[1] += yl[i + 8];
                yh[i + 0] = y4[i + 128]; sumy[2] += yh[i + 0];
                yh[i + 8] = y4[i + 160]; sumy[3] += yh[i + 8];
            }

            device const uint16_t *sc = (device const uint16_t *)x[ib].scales + iq;
            device const uint16_t *q1 = (device const uint16_t *)x[ib].qs + 16 * iq + 4 * ir;
            device const half *dh = &x[ib].d;

            for (short row = 0; row < nr0; row++) {
                if (first_row + row < args.ne0) {
                    sc16[0] = sc[0] & kmask1;
                    sc16[1] = sc[2] & kmask1;
                    sc16[2] = ((sc[4] >> 0) & kmask2) | ((sc[0] & kmask3) >> 2);
                    sc16[3] = ((sc[4] >> 4) & kmask2) | ((sc[2] & kmask3) >> 2);

                    device const uint16_t *q2 = q1 + 32;

                    float4 acc1 = {0.f, 0.f, 0.f, 0.f};
                    float4 acc2 = {0.f, 0.f, 0.f, 0.f};

                    FOR_UNROLL (short i = 0; i < 4; ++i) {
                        acc1[0] += yl[2 * i + 0] * (q1[i] & 0x000F);
                        acc1[1] += yl[2 * i + 1] * (q1[i] & 0x0F00);
                        acc1[2] += yl[2 * i + 8] * (q1[i] & 0x00F0);
                        acc1[3] += yl[2 * i + 9] * (q1[i] & 0xF000);
                        acc2[0] += yh[2 * i + 0] * (q2[i] & 0x000F);
                        acc2[1] += yh[2 * i + 1] * (q2[i] & 0x0F00);
                        acc2[2] += yh[2 * i + 8] * (q2[i] & 0x00F0);
                        acc2[3] += yh[2 * i + 9] * (q2[i] & 0xF000);
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: metal/moe.metal

```metal
constexpr uint16_t kmask1 = 0x3f3f;
    constexpr uint16_t kmask2 = 0x0f0f;
    constexpr uint16_t kmask3 = 0xc0c0;

    const short ix = tiisg / 8;
    const short it = tiisg % 8;
    const short iq = it / 4;
    const short ir = it % 4;

    float sumf[nr0] = {0.f};
    uint16_t sc16[4];
    thread const uint8_t *sc8 = (thread const uint8_t *)sc16;

    for (int expert_slot = 0; expert_slot < 6; expert_slot++) {
        const int32_t expert = token_ids[expert_slot];
        device const block_q4_K *x =
            (device const block_q4_K *)(src0s + expert * args.nb02 + first_row * args.nb01);
        device const float *y = (device const float *)(token_src1 + expert_slot * args.nb11);
        device const float *y4 = y + ix * QK_K + 64 * iq + 8 * ir;

        for (int ib = ix; ib < nb; ib += 4) {
            float yl[16];
            float yh[16];
            float4 sumy = {0.f, 0.f, 0.f, 0.f};

            for (short i = 0; i < 8; ++i) {
                yl[i + 0] = y4[i +   0]; sumy[0] += yl[i + 0];
                yl[i + 8] = y4[i +  32]; sumy[1] += yl[i + 8];
                yh[i + 0] = y4[i + 128]; sumy[2] += yh[i + 0];
                yh[i + 8] = y4[i + 160]; sumy[3] += yh[i + 8];
            }

            device const uint16_t *sc = (device const uint16_t *)x[ib].scales + iq;
            device const uint16_t *q1 = (device const uint16_t *)x[ib].qs + 16 * iq + 4 * ir;
            device const half *dh = &x[ib].d;

            for (short row = 0; row < nr0; row++) {
                if (first_row + row < args.ne0) {
                    sc16[0] = sc[0] & kmask1;
                    sc16[1] = sc[2] & kmask1;
                    sc16[2] = ((sc[4] >> 0) & kmask2) | ((sc[0] & kmask3) >> 2);
                    sc16[3] = ((sc[4] >> 4) & kmask2) | ((sc[2] & kmask3) >> 2);

                    device const uint16_t *q2 = q1 + 32;

                    float4 acc1 = {0.f, 0.f, 0.f, 0.f};
                    float4 acc2 = {0.f, 0.f, 0.f, 0.f};

                    FOR_UNROLL (short i = 0; i < 4; ++i) {
                        acc1[0] += yl[2 * i + 0] * (q1[i] & 0x000F);
                        acc1[1] += yl[2 * i + 1] * (q1[i] & 0x0F00);
                        acc1[2] += yl[2 * i + 8] * (q1[i] & 0x00F0);
                        acc1[3] += yl[2 * i + 9] * (q1[i] & 0xF000);
                        acc2[0] += yh[2 * i + 0] * (q2[i] & 0x000F);
                        acc2[1] += yh[2 * i + 1] * (q2[i] & 0x0F00);
                        acc2[2] += yh[2 * i + 8] * (q2[i] & 0x00F0);
                        acc2[3] += yh[2 * i + 9] * (q2[i] & 0xF000);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Explain what this code does and identify the inference stage it belongs to.

File: metal/moe.metal

```metal
constexpr uint16_t kmask1 = 0x3f3f;
    constexpr uint16_t kmask2 = 0x0f0f;
    constexpr uint16_t kmask3 = 0xc0c0;

    const short ix = tiisg / 8;
    const short it = tiisg % 8;
    const short iq = it / 4;
    const short ir = it % 4;

    float sumf[nr0] = {0.f};
    uint16_t sc16[4];
    thread const uint8_t *sc8 = (thread const uint8_t *)sc16;

    for (int expert_slot = 0; expert_slot < 6; expert_slot++) {
        const int32_t expert = token_ids[expert_slot];
        device const block_q4_K *x =
            (device const block_q4_K *)(src0s + expert * args.nb02 + first_row * args.nb01);
        device const float *y = (device const float *)(token_src1 + expert_slot * args.nb11);
        device const float *y4 = y + ix * QK_K + 64 * iq + 8 * ir;

        for (int ib = ix; ib < nb; ib += 4) {
            float yl[16];
            float yh[16];
            float4 sumy = {0.f, 0.f, 0.f, 0.f};

            for (short i = 0; i < 8; ++i) {
                yl[i + 0] = y4[i +   0]; sumy[0] += yl[i + 0];
                yl[i + 8] = y4[i +  32]; sumy[1] += yl[i + 8];
                yh[i + 0] = y4[i + 128]; sumy[2] += yh[i + 0];
                yh[i + 8] = y4[i + 160]; sumy[3] += yh[i + 8];
            }

            device const uint16_t *sc = (device const uint16_t *)x[ib].scales + iq;
            device const uint16_t *q1 = (device const uint16_t *)x[ib].qs + 16 * iq + 4 * ir;
            device const half *dh = &x[ib].d;

            for (short row = 0; row < nr0; row++) {
                if (first_row + row < args.ne0) {
                    sc16[0] = sc[0] & kmask1;
                    sc16[1] = sc[2] & kmask1;
                    sc16[2] = ((sc[4] >> 0) & kmask2) | ((sc[0] & kmask3) >> 2);
                    sc16[3] = ((sc[4] >> 4) & kmask2) | ((sc[2] & kmask3) >> 2);

                    device const uint16_t *q2 = q1 + 32;

                    float4 acc1 = {0.f, 0.f, 0.f, 0.f};
                    float4 acc2 = {0.f, 0.f, 0.f, 0.f};

                    FOR_UNROLL (short i = 0; i < 4; ++i) {
                        acc1[0] += yl[2 * i + 0] * (q1[i] & 0x000F);
                        acc1[1] += yl[2 * i + 1] * (q1[i] & 0x0F00);
                        acc1[2] += yl[2 * i + 8] * (q1[i] & 0x00F0);
                        acc1[3] += yl[2 * i + 9] * (q1[i] & 0xF000);
                        acc2[0] += yh[2 * i + 0] * (q2[i] & 0x000F);
                        acc2[1] += yh[2 * i + 1] * (q2[i] & 0x0F00);
                        acc2[2] += yh[2 * i + 8] * (q2[i] & 0x00F0);
                        acc2[3] += yh[2 * i + 9] * (q2[i] & 0xF000);
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
c2[1] += yh[2 * i + 1] * (q2[i] & 0x0F00);
                        acc2[2] += yh[2 * i + 8] * (q2[i] & 0x00F0);
                        acc2[3] += yh[2 * i + 9] * (q2[i] & 0xF000);
                    }

                    sumf[row] += dh[0] * ((acc1[0] + 1.f / 256.f * acc1[1]) * sc8[0] +
                                          (acc1[2] + 1.f / 256.f * acc1[3]) * sc8[1] * 1.f / 16.f +
                                          (acc2[0] + 1.f / 256.f * acc2[1]) * sc8[4] +
                                          (acc2[2] + 1.f / 256.f * acc2[3]) * sc8[5] * 1.f / 16.f) -
                                 dh[1] * (sumy[0] * sc8[2] + sumy[1] * sc8[3] +
                                          sumy[2] * sc8[6] + sumy[3] * sc8[7]);
                }

                q1 += args.nb01 / 2;
                sc += args.nb01 / 2;
                dh += args.nb01 / 2;
            }

            y4 += 4 * QK_K;
        }
    }

    device float *dst_f32 = (device float *)(dst + (uint64_t)token * args.nb1);
    for (int row = 0; row < nr0 && first_row + row < args.ne0; row++) {
        const float sum_all = simd_sum(sumf[row]);
        if (tiisg == 0) dst_f32[first_row + row] = sum_all;
    }

    (void)shmem;
    (void)tiitg;
    (void)tgpig;
}

#define QK_NL 16

// Builds the compact per-expert work map used by batched MoE matmul. DS4 routes
// each token to a small fixed top-k list, so this turns token-major ids into
// expert-major slices that the tiled matmul can consume.
template<short ne20>
kernel void kernel_mul_mm_id_map0(
        constant ds4_metal_args_mul_mm_id_map0 & args,
        device  const char * src2,
        device        char * htpe,
        device        char * hids,
        threadgroup   char * shmem [[threadgroup(0)]],
        ushort tpitg[[thread_position_in_threadgroup]],
        ushort   ntg[[threads_per_threadgroup]]) {
    const short ide = tpitg;

    uint32_t n_all = 0;

    device int32_t * ids_i32 = (device int32_t *) hids + ide*args.ne21;

    for (int i21 = 0; i21 < args.ne21; i21 += ntg) {
        if (i21 + tpitg < args.ne21) {
            device const int32_t * src2_i32 = (device const int32_t *) (src2 + (i21 + tpitg)*args.nb21);

            threadgroup uint16_t * sids = (threadgroup uint16_t *) shmem + tpitg*ne20;

            #pragma unroll(ne20)
            for (short i20 = 0; i20 < ne20; i20++) {
                sids[i20] = src2_i32[i20];
            }
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        for (short t = 0; t < ntg; t++) {
            if (i21 + t >= args.ne21) {
                break;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
c2[1] += yh[2 * i + 1] * (q2[i] & 0x0F00);
                        acc2[2] += yh[2 * i + 8] * (q2[i] & 0x00F0);
                        acc2[3] += yh[2 * i + 9] * (q2[i] & 0xF000);
                    }

                    sumf[row] += dh[0] * ((acc1[0] + 1.f / 256.f * acc1[1]) * sc8[0] +
                                          (acc1[2] + 1.f / 256.f * acc1[3]) * sc8[1] * 1.f / 16.f +
                                          (acc2[0] + 1.f / 256.f * acc2[1]) * sc8[4] +
                                          (acc2[2] + 1.f / 256.f * acc2[3]) * sc8[5] * 1.f / 16.f) -
                                 dh[1] * (sumy[0] * sc8[2] + sumy[1] * sc8[3] +
                                          sumy[2] * sc8[6] + sumy[3] * sc8[7]);
                }

                q1 += args.nb01 / 2;
                sc += args.nb01 / 2;
                dh += args.nb01 / 2;
            }

            y4 += 4 * QK_K;
        }
    }

    device float *dst_f32 = (device float *)(dst + (uint64_t)token * args.nb1);
    for (int row = 0; row < nr0 && first_row + row < args.ne0; row++) {
        const float sum_all = simd_sum(sumf[row]);
        if (tiisg == 0) dst_f32[first_row + row] = sum_all;
    }

    (void)shmem;
    (void)tiitg;
    (void)tgpig;
}

#define QK_NL 16

// Builds the compact per-expert work map used by batched MoE matmul. DS4 routes
// each token to a small fixed top-k list, so this turns token-major ids into
// expert-major slices that the tiled matmul can consume.
template<short ne20>
kernel void kernel_mul_mm_id_map0(
        constant ds4_metal_args_mul_mm_id_map0 & args,
        device  const char * src2,
        device        char * htpe,
        device        char * hids,
        threadgroup   char * shmem [[threadgroup(0)]],
        ushort tpitg[[thread_position_in_threadgroup]],
        ushort   ntg[[threads_per_threadgroup]]) {
    const short ide = tpitg;

    uint32_t n_all = 0;

    device int32_t * ids_i32 = (device int32_t *) hids + ide*args.ne21;

    for (int i21 = 0; i21 < args.ne21; i21 += ntg) {
        if (i21 + tpitg < args.ne21) {
            device const int32_t * src2_i32 = (device const int32_t *) (src2 + (i21 + tpitg)*args.nb21);

            threadgroup uint16_t * sids = (threadgroup uint16_t *) shmem + tpitg*ne20;

            #pragma unroll(ne20)
            for (short i20 = 0; i20 < ne20; i20++) {
                sids[i20] = src2_i32[i20];
            }
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        for (short t = 0; t < ntg; t++) {
            if (i21 + t >= args.ne21) {
                break;
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
c2[1] += yh[2 * i + 1] * (q2[i] & 0x0F00);
                        acc2[2] += yh[2 * i + 8] * (q2[i] & 0x00F0);
                        acc2[3] += yh[2 * i + 9] * (q2[i] & 0xF000);
                    }

                    sumf[row] += dh[0] * ((acc1[0] + 1.f / 256.f * acc1[1]) * sc8[0] +
                                          (acc1[2] + 1.f / 256.f * acc1[3]) * sc8[1] * 1.f / 16.f +
                                          (acc2[0] + 1.f / 256.f * acc2[1]) * sc8[4] +
                                          (acc2[2] + 1.f / 256.f * acc2[3]) * sc8[5] * 1.f / 16.f) -
                                 dh[1] * (sumy[0] * sc8[2] + sumy[1] * sc8[3] +
                                          sumy[2] * sc8[6] + sumy[3] * sc8[7]);
                }

                q1 += args.nb01 / 2;
                sc += args.nb01 / 2;
                dh += args.nb01 / 2;
            }

            y4 += 4 * QK_K;
        }
    }

    device float *dst_f32 = (device float *)(dst + (uint64_t)token * args.nb1);
    for (int row = 0; row < nr0 && first_row + row < args.ne0; row++) {
        const float sum_all = simd_sum(sumf[row]);
        if (tiisg == 0) dst_f32[first_row + row] = sum_all;
    }

    (void)shmem;
    (void)tiitg;
    (void)tgpig;
}

#define QK_NL 16

// Builds the compact per-expert work map used by batched MoE matmul. DS4 routes
// each token to a small fixed top-k list, so this turns token-major ids into
// expert-major slices that the tiled matmul can consume.
template<short ne20>
kernel void kernel_mul_mm_id_map0(
        constant ds4_metal_args_mul_mm_id_map0 & args,
        device  const char * src2,
        device        char * htpe,
        device        char * hids,
        threadgroup   char * shmem [[threadgroup(0)]],
        ushort tpitg[[thread_position_in_threadgroup]],
        ushort   ntg[[threads_per_threadgroup]]) {
    const short ide = tpitg;

    uint32_t n_all = 0;

    device int32_t * ids_i32 = (device int32_t *) hids + ide*args.ne21;

    for (int i21 = 0; i21 < args.ne21; i21 += ntg) {
        if (i21 + tpitg < args.ne21) {
            device const int32_t * src2_i32 = (device const int32_t *) (src2 + (i21 + tpitg)*args.nb21);

            threadgroup uint16_t * sids = (threadgroup uint16_t *) shmem + tpitg*ne20;

            #pragma unroll(ne20)
            for (short i20 = 0; i20 < ne20; i20++) {
                sids[i20] = src2_i32[i20];
            }
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        for (short t = 0; t < ntg; t++) {
            if (i21 + t >= args.ne21) {
                break;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
c2[1] += yh[2 * i + 1] * (q2[i] & 0x0F00);
                        acc2[2] += yh[2 * i + 8] * (q2[i] & 0x00F0);
                        acc2[3] += yh[2 * i + 9] * (q2[i] & 0xF000);
                    }

                    sumf[row] += dh[0] * ((acc1[0] + 1.f / 256.f * acc1[1]) * sc8[0] +
                                          (acc1[2] + 1.f / 256.f * acc1[3]) * sc8[1] * 1.f / 16.f +
                                          (acc2[0] + 1.f / 256.f * acc2[1]) * sc8[4] +
                                          (acc2[2] + 1.f / 256.f * acc2[3]) * sc8[5] * 1.f / 16.f) -
                                 dh[1] * (sumy[0] * sc8[2] + sumy[1] * sc8[3] +
                                          sumy[2] * sc8[6] + sumy[3] * sc8[7]);
                }

                q1 += args.nb01 / 2;
                sc += args.nb01 / 2;
                dh += args.nb01 / 2;
            }

            y4 += 4 * QK_K;
        }
    }

    device float *dst_f32 = (device float *)(dst + (uint64_t)token * args.nb1);
    for (int row = 0; row < nr0 && first_row + row < args.ne0; row++) {
        const float sum_all = simd_sum(sumf[row]);
        if (tiisg == 0) dst_f32[first_row + row] = sum_all;
    }

    (void)shmem;
    (void)tiitg;
    (void)tgpig;
}

#define QK_NL 16

// Builds the compact per-expert work map used by batched MoE matmul. DS4 routes
// each token to a small fixed top-k list, so this turns token-major ids into
// expert-major slices that the tiled matmul can consume.
template<short ne20>
kernel void kernel_mul_mm_id_map0(
        constant ds4_metal_args_mul_mm_id_map0 & args,
        device  const char * src2,
        device        char * htpe,
        device        char * hids,
        threadgroup   char * shmem [[threadgroup(0)]],
        ushort tpitg[[thread_position_in_threadgroup]],
        ushort   ntg[[threads_per_threadgroup]]) {
    const short ide = tpitg;

    uint32_t n_all = 0;

    device int32_t * ids_i32 = (device int32_t *) hids + ide*args.ne21;

    for (int i21 = 0; i21 < args.ne21; i21 += ntg) {
        if (i21 + tpitg < args.ne21) {
            device const int32_t * src2_i32 = (device const int32_t *) (src2 + (i21 + tpitg)*args.nb21);

            threadgroup uint16_t * sids = (threadgroup uint16_t *) shmem + tpitg*ne20;

            #pragma unroll(ne20)
            for (short i20 = 0; i20 < ne20; i20++) {
                sids[i20] = src2_i32[i20];
            }
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        for (short t = 0; t < ntg; t++) {
            if (i21 + t >= args.ne21) {
                break;
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
}
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        for (short t = 0; t < ntg; t++) {
            if (i21 + t >= args.ne21) {
                break;
            }

            threadgroup const uint16_t * sids = (threadgroup const uint16_t *) shmem + t*ne20;

            short sel = 0;
            #pragma unroll(ne20)
            for (short i20 = 0; i20 < ne20; i20++) {
                sel += (sids[i20] == ide)*(i20 + 1);
            }

            ids_i32[n_all] = (i21 + t)*ne20 + sel - 1;

            n_all += sel > 0;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);
    }

    device uint32_t * tpe_u32 = (device uint32_t *) (htpe);
    tpe_u32[ide] = n_all;
}

typedef decltype(kernel_mul_mm_id_map0<1>) kernel_mul_mm_id_map0_t;

// Host-visible map builders for the routed-expert counts used by DS4 graph
// shapes. Some arities are generic leftovers retained for nearby batch sizes.
template [[host_name("kernel_mul_mm_id_map0_ne20_1" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<1>;
template [[host_name("kernel_mul_mm_id_map0_ne20_2" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<2>;
template [[host_name("kernel_mul_mm_id_map0_ne20_4" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<4>;
template [[host_name("kernel_mul_mm_id_map0_ne20_5" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<5>;
template [[host_name("kernel_mul_mm_id_map0_ne20_6" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<6>;
template [[host_name("kernel_mul_mm_id_map0_ne20_8" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<8>;
template [[host_name("kernel_mul_mm_id_map0_ne20_10")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<10>;
template [[host_name("kernel_mul_mm_id_map0_ne20_16")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<16>;
template [[host_name("kernel_mul_mm_id_map0_ne20_22")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<22>;

// Batched routed-expert matmul. It reads the expert-major map produced above,
// loads selected expert weights, and writes results back to token-major slots
// so the DS4 FFN can apply SwiGLU, weighting, and the down projection.
template<typename S0, typename S0_4x4, typename S0_8x8, typename S1, typename S1_2x4, typename S1_8x8, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread S0_4x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
        constant ds4_metal_args_mul_mm_id & args,
        device const char * src0,
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
}
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        for (short t = 0; t < ntg; t++) {
            if (i21 + t >= args.ne21) {
                break;
            }

            threadgroup const uint16_t * sids = (threadgroup const uint16_t *) shmem + t*ne20;

            short sel = 0;
            #pragma unroll(ne20)
            for (short i20 = 0; i20 < ne20; i20++) {
                sel += (sids[i20] == ide)*(i20 + 1);
            }

            ids_i32[n_all] = (i21 + t)*ne20 + sel - 1;

            n_all += sel > 0;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);
    }

    device uint32_t * tpe_u32 = (device uint32_t *) (htpe);
    tpe_u32[ide] = n_all;
}

typedef decltype(kernel_mul_mm_id_map0<1>) kernel_mul_mm_id_map0_t;

// Host-visible map builders for the routed-expert counts used by DS4 graph
// shapes. Some arities are generic leftovers retained for nearby batch sizes.
template [[host_name("kernel_mul_mm_id_map0_ne20_1" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<1>;
template [[host_name("kernel_mul_mm_id_map0_ne20_2" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<2>;
template [[host_name("kernel_mul_mm_id_map0_ne20_4" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<4>;
template [[host_name("kernel_mul_mm_id_map0_ne20_5" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<5>;
template [[host_name("kernel_mul_mm_id_map0_ne20_6" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<6>;
template [[host_name("kernel_mul_mm_id_map0_ne20_8" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<8>;
template [[host_name("kernel_mul_mm_id_map0_ne20_10")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<10>;
template [[host_name("kernel_mul_mm_id_map0_ne20_16")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<16>;
template [[host_name("kernel_mul_mm_id_map0_ne20_22")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<22>;

// Batched routed-expert matmul. It reads the expert-major map produced above,
// loads selected expert weights, and writes results back to token-major slots
// so the DS4 FFN can apply SwiGLU, weighting, and the down projection.
template<typename S0, typename S0_4x4, typename S0_8x8, typename S1, typename S1_2x4, typename S1_8x8, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread S0_4x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
        constant ds4_metal_args_mul_mm_id & args,
        device const char * src0,
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
}
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        for (short t = 0; t < ntg; t++) {
            if (i21 + t >= args.ne21) {
                break;
            }

            threadgroup const uint16_t * sids = (threadgroup const uint16_t *) shmem + t*ne20;

            short sel = 0;
            #pragma unroll(ne20)
            for (short i20 = 0; i20 < ne20; i20++) {
                sel += (sids[i20] == ide)*(i20 + 1);
            }

            ids_i32[n_all] = (i21 + t)*ne20 + sel - 1;

            n_all += sel > 0;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);
    }

    device uint32_t * tpe_u32 = (device uint32_t *) (htpe);
    tpe_u32[ide] = n_all;
}

typedef decltype(kernel_mul_mm_id_map0<1>) kernel_mul_mm_id_map0_t;

// Host-visible map builders for the routed-expert counts used by DS4 graph
// shapes. Some arities are generic leftovers retained for nearby batch sizes.
template [[host_name("kernel_mul_mm_id_map0_ne20_1" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<1>;
template [[host_name("kernel_mul_mm_id_map0_ne20_2" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<2>;
template [[host_name("kernel_mul_mm_id_map0_ne20_4" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<4>;
template [[host_name("kernel_mul_mm_id_map0_ne20_5" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<5>;
template [[host_name("kernel_mul_mm_id_map0_ne20_6" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<6>;
template [[host_name("kernel_mul_mm_id_map0_ne20_8" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<8>;
template [[host_name("kernel_mul_mm_id_map0_ne20_10")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<10>;
template [[host_name("kernel_mul_mm_id_map0_ne20_16")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<16>;
template [[host_name("kernel_mul_mm_id_map0_ne20_22")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<22>;

// Batched routed-expert matmul. It reads the expert-major map produced above,
// loads selected expert weights, and writes results back to token-major slots
// so the DS4 FFN can apply SwiGLU, weighting, and the down projection.
template<typename S0, typename S0_4x4, typename S0_8x8, typename S1, typename S1_2x4, typename S1_8x8, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread S0_4x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
        constant ds4_metal_args_mul_mm_id & args,
        device const char * src0,
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
}
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);

        for (short t = 0; t < ntg; t++) {
            if (i21 + t >= args.ne21) {
                break;
            }

            threadgroup const uint16_t * sids = (threadgroup const uint16_t *) shmem + t*ne20;

            short sel = 0;
            #pragma unroll(ne20)
            for (short i20 = 0; i20 < ne20; i20++) {
                sel += (sids[i20] == ide)*(i20 + 1);
            }

            ids_i32[n_all] = (i21 + t)*ne20 + sel - 1;

            n_all += sel > 0;
        }

        threadgroup_barrier(mem_flags::mem_threadgroup);
    }

    device uint32_t * tpe_u32 = (device uint32_t *) (htpe);
    tpe_u32[ide] = n_all;
}

typedef decltype(kernel_mul_mm_id_map0<1>) kernel_mul_mm_id_map0_t;

// Host-visible map builders for the routed-expert counts used by DS4 graph
// shapes. Some arities are generic leftovers retained for nearby batch sizes.
template [[host_name("kernel_mul_mm_id_map0_ne20_1" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<1>;
template [[host_name("kernel_mul_mm_id_map0_ne20_2" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<2>;
template [[host_name("kernel_mul_mm_id_map0_ne20_4" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<4>;
template [[host_name("kernel_mul_mm_id_map0_ne20_5" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<5>;
template [[host_name("kernel_mul_mm_id_map0_ne20_6" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<6>;
template [[host_name("kernel_mul_mm_id_map0_ne20_8" )]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<8>;
template [[host_name("kernel_mul_mm_id_map0_ne20_10")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<10>;
template [[host_name("kernel_mul_mm_id_map0_ne20_16")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<16>;
template [[host_name("kernel_mul_mm_id_map0_ne20_22")]] kernel kernel_mul_mm_id_map0_t kernel_mul_mm_id_map0<22>;

// Batched routed-expert matmul. It reads the expert-major map produced above,
// loads selected expert weights, and writes results back to token-major slots
// so the DS4 FFN can apply SwiGLU, weighting, and the down projection.
template<typename S0, typename S0_4x4, typename S0_8x8, typename S1, typename S1_2x4, typename S1_8x8, typename block_q, short nl, void (*dequantize_func)(device const block_q *, short, thread S0_4x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
        constant ds4_metal_args_mul_mm_id & args,
        device const char * src0,
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: metal/moe.metal

```metal
x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
        constant ds4_metal_args_mul_mm_id & args,
        device const char * src0,
        device const char * src1,
        device const char * htpe,
        device const char * hids,
        device       char * dst,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3  tgpig[[threadgroup_position_in_grid]],
        ushort tiitg[[thread_index_in_threadgroup]],
        ushort tiisg[[thread_index_in_simdgroup]],
        ushort sgitg[[simdgroup_index_in_threadgroup]]) {
    threadgroup S0 * sa = (threadgroup S0 *)(shmem);
    threadgroup S1 * sb = (threadgroup S1 *)(shmem + 4096);

    constexpr int NR0 = 64;
    constexpr int NR1 = 32;

    constexpr int NK  = 32;
    constexpr int NL0 = NK/16;
    constexpr int NL1 = NK/8;

    const int im = tgpig.z;
    const int r0 = tgpig.y*NR0;
    const int r1 = tgpig.x*NR1;

    device const uint32_t * tpe_u32 = (device const uint32_t *) (htpe);
    device const int32_t  * ids_i32 = (device const int32_t  *) (hids);

    const int32_t neh1 = tpe_u32[im];

    if (r1 >= neh1) {
        return;
    }

    const short nr0 = (args.ne0 - r0 < NR0) ? (args.ne0 - r0) : NR0;
    const short nr1 = (    neh1 - r1 < NR1) ? (    neh1 - r1) : NR1;

    const short lr0 = ((short)tiitg/NL0) < nr0 ? ((short)tiitg/NL0) : nr0 - 1;
    const short lr1 = ((short)tiitg/NL1) < nr1 ? ((short)tiitg/NL1) : nr1 - 1;

    const short il0 = (tiitg % NL0);

    short il = il0;

    const int id = ids_i32[im*args.ne21 + r1 + lr1];

    const short i11 = (id % args.ne20) % args.ne11;
    const short i12 = (id / args.ne20);
    const short i13 = 0;

    const uint64_t offset0 = im*args.nb02 + i13*args.nb03;
    const short    offset1 = il0/nl;

    device const block_q * x = (device const block_q *)(src0 + args.nb01*(r0 + lr0) + offset0) + offset1;

    const short iy = 8*(tiitg % NL1);

    device const T1 * y = (device const T1 *)(src1
        + args.nb13*i13
        + args.nb12*i12
        + args.nb11*i11
        + args.nb10*iy);

    S0_8x8 ma[4];
    S1_8x8 mb[2];

    simdgroup_float8x8 mc[8];

    for (short i = 0; i < 8; i++){
        mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
    }

    for (int loop_k = 0; loop_k < args.ne00; loop_k += NK) {
        if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
            threadgroup_barrier(mem_flags::mem_threadgroup);

            for (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: metal/moe.metal

```metal
x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
        constant ds4_metal_args_mul_mm_id & args,
        device const char * src0,
        device const char * src1,
        device const char * htpe,
        device const char * hids,
        device       char * dst,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3  tgpig[[threadgroup_position_in_grid]],
        ushort tiitg[[thread_index_in_threadgroup]],
        ushort tiisg[[thread_index_in_simdgroup]],
        ushort sgitg[[simdgroup_index_in_threadgroup]]) {
    threadgroup S0 * sa = (threadgroup S0 *)(shmem);
    threadgroup S1 * sb = (threadgroup S1 *)(shmem + 4096);

    constexpr int NR0 = 64;
    constexpr int NR1 = 32;

    constexpr int NK  = 32;
    constexpr int NL0 = NK/16;
    constexpr int NL1 = NK/8;

    const int im = tgpig.z;
    const int r0 = tgpig.y*NR0;
    const int r1 = tgpig.x*NR1;

    device const uint32_t * tpe_u32 = (device const uint32_t *) (htpe);
    device const int32_t  * ids_i32 = (device const int32_t  *) (hids);

    const int32_t neh1 = tpe_u32[im];

    if (r1 >= neh1) {
        return;
    }

    const short nr0 = (args.ne0 - r0 < NR0) ? (args.ne0 - r0) : NR0;
    const short nr1 = (    neh1 - r1 < NR1) ? (    neh1 - r1) : NR1;

    const short lr0 = ((short)tiitg/NL0) < nr0 ? ((short)tiitg/NL0) : nr0 - 1;
    const short lr1 = ((short)tiitg/NL1) < nr1 ? ((short)tiitg/NL1) : nr1 - 1;

    const short il0 = (tiitg % NL0);

    short il = il0;

    const int id = ids_i32[im*args.ne21 + r1 + lr1];

    const short i11 = (id % args.ne20) % args.ne11;
    const short i12 = (id / args.ne20);
    const short i13 = 0;

    const uint64_t offset0 = im*args.nb02 + i13*args.nb03;
    const short    offset1 = il0/nl;

    device const block_q * x = (device const block_q *)(src0 + args.nb01*(r0 + lr0) + offset0) + offset1;

    const short iy = 8*(tiitg % NL1);

    device const T1 * y = (device const T1 *)(src1
        + args.nb13*i13
        + args.nb12*i12
        + args.nb11*i11
        + args.nb10*iy);

    S0_8x8 ma[4];
    S1_8x8 mb[2];

    simdgroup_float8x8 mc[8];

    for (short i = 0; i < 8; i++){
        mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
    }

    for (int loop_k = 0; loop_k < args.ne00; loop_k += NK) {
        if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
            threadgroup_barrier(mem_flags::mem_threadgroup);

            for (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: metal/moe.metal

```metal
x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
        constant ds4_metal_args_mul_mm_id & args,
        device const char * src0,
        device const char * src1,
        device const char * htpe,
        device const char * hids,
        device       char * dst,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3  tgpig[[threadgroup_position_in_grid]],
        ushort tiitg[[thread_index_in_threadgroup]],
        ushort tiisg[[thread_index_in_simdgroup]],
        ushort sgitg[[simdgroup_index_in_threadgroup]]) {
    threadgroup S0 * sa = (threadgroup S0 *)(shmem);
    threadgroup S1 * sb = (threadgroup S1 *)(shmem + 4096);

    constexpr int NR0 = 64;
    constexpr int NR1 = 32;

    constexpr int NK  = 32;
    constexpr int NL0 = NK/16;
    constexpr int NL1 = NK/8;

    const int im = tgpig.z;
    const int r0 = tgpig.y*NR0;
    const int r1 = tgpig.x*NR1;

    device const uint32_t * tpe_u32 = (device const uint32_t *) (htpe);
    device const int32_t  * ids_i32 = (device const int32_t  *) (hids);

    const int32_t neh1 = tpe_u32[im];

    if (r1 >= neh1) {
        return;
    }

    const short nr0 = (args.ne0 - r0 < NR0) ? (args.ne0 - r0) : NR0;
    const short nr1 = (    neh1 - r1 < NR1) ? (    neh1 - r1) : NR1;

    const short lr0 = ((short)tiitg/NL0) < nr0 ? ((short)tiitg/NL0) : nr0 - 1;
    const short lr1 = ((short)tiitg/NL1) < nr1 ? ((short)tiitg/NL1) : nr1 - 1;

    const short il0 = (tiitg % NL0);

    short il = il0;

    const int id = ids_i32[im*args.ne21 + r1 + lr1];

    const short i11 = (id % args.ne20) % args.ne11;
    const short i12 = (id / args.ne20);
    const short i13 = 0;

    const uint64_t offset0 = im*args.nb02 + i13*args.nb03;
    const short    offset1 = il0/nl;

    device const block_q * x = (device const block_q *)(src0 + args.nb01*(r0 + lr0) + offset0) + offset1;

    const short iy = 8*(tiitg % NL1);

    device const T1 * y = (device const T1 *)(src1
        + args.nb13*i13
        + args.nb12*i12
        + args.nb11*i11
        + args.nb10*iy);

    S0_8x8 ma[4];
    S1_8x8 mb[2];

    simdgroup_float8x8 mc[8];

    for (short i = 0; i < 8; i++){
        mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
    }

    for (int loop_k = 0; loop_k < args.ne00; loop_k += NK) {
        if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
            threadgroup_barrier(mem_flags::mem_threadgroup);

            for (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Review this excerpt for correctness risks, memory lifetime issues, and performance bottlenecks.

File: metal/moe.metal

```metal
x4 &), typename T0, typename T0_4x4, typename T1, typename T1_2x4>
kernel void kernel_mul_mm_id(
        constant ds4_metal_args_mul_mm_id & args,
        device const char * src0,
        device const char * src1,
        device const char * htpe,
        device const char * hids,
        device       char * dst,
        threadgroup  char * shmem [[threadgroup(0)]],
        uint3  tgpig[[threadgroup_position_in_grid]],
        ushort tiitg[[thread_index_in_threadgroup]],
        ushort tiisg[[thread_index_in_simdgroup]],
        ushort sgitg[[simdgroup_index_in_threadgroup]]) {
    threadgroup S0 * sa = (threadgroup S0 *)(shmem);
    threadgroup S1 * sb = (threadgroup S1 *)(shmem + 4096);

    constexpr int NR0 = 64;
    constexpr int NR1 = 32;

    constexpr int NK  = 32;
    constexpr int NL0 = NK/16;
    constexpr int NL1 = NK/8;

    const int im = tgpig.z;
    const int r0 = tgpig.y*NR0;
    const int r1 = tgpig.x*NR1;

    device const uint32_t * tpe_u32 = (device const uint32_t *) (htpe);
    device const int32_t  * ids_i32 = (device const int32_t  *) (hids);

    const int32_t neh1 = tpe_u32[im];

    if (r1 >= neh1) {
        return;
    }

    const short nr0 = (args.ne0 - r0 < NR0) ? (args.ne0 - r0) : NR0;
    const short nr1 = (    neh1 - r1 < NR1) ? (    neh1 - r1) : NR1;

    const short lr0 = ((short)tiitg/NL0) < nr0 ? ((short)tiitg/NL0) : nr0 - 1;
    const short lr1 = ((short)tiitg/NL1) < nr1 ? ((short)tiitg/NL1) : nr1 - 1;

    const short il0 = (tiitg % NL0);

    short il = il0;

    const int id = ids_i32[im*args.ne21 + r1 + lr1];

    const short i11 = (id % args.ne20) % args.ne11;
    const short i12 = (id / args.ne20);
    const short i13 = 0;

    const uint64_t offset0 = im*args.nb02 + i13*args.nb03;
    const short    offset1 = il0/nl;

    device const block_q * x = (device const block_q *)(src0 + args.nb01*(r0 + lr0) + offset0) + offset1;

    const short iy = 8*(tiitg % NL1);

    device const T1 * y = (device const T1 *)(src1
        + args.nb13*i13
        + args.nb12*i12
        + args.nb11*i11
        + args.nb10*iy);

    S0_8x8 ma[4];
    S1_8x8 mb[2];

    simdgroup_float8x8 mc[8];

    for (short i = 0; i < 8; i++){
        mc[i] = make_filled_simdgroup_matrix<float, 8>(0.f);
    }

    for (int loop_k = 0; loop_k < args.ne00; loop_k += NK) {
        if (is_same<T0_4x4, block_q>::value && FC_mul_mm_bc_inp) {
            threadgroup_barrier(mem_flags::mem_threadgroup);

            for (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: metal/moe.metal

```metal
up_barrier(mem_flags::mem_threadgroup);

            for (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;

                const short lx = (tiitg/NL0)%8;
                const short ly = i%8;

                const short ib = 8*sx + sy;

                *(sa + 64*ib + 8*ly + lx) = loop_k + 16*il + i < args.ne00 ? *((device T0 *) x + i) : 0;
            }
        } else {
            S0_4x4 temp_a;
            dequantize_func(x, il, temp_a);

            threadgroup_barrier(mem_flags::mem_threadgroup);

            FOR_UNROLL (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;

                const short lx = (tiitg/NL0)%8;
                const short ly = i%8;

                const short ib = 8*sx + sy;

                *(sa + 64*ib + 8*ly + lx) = temp_a[i/4][i%4];
            }
        }

        if (FC_mul_mm_bc_inp) {
            for (short i = 0; i < 8; ++i) {
                const short sx = (tiitg%NL1);
                const short sy = (tiitg/NL1)/8;

                const short lx = i;
                const short ly = (tiitg/NL1)%8;

                const short ib = 4*sx + sy;

                *(sb + 64*ib + 8*ly + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
            }
        } else {
            const short sx = (tiitg%NL1);
            const short sy = (tiitg/NL1)/8;

            const short ly = (tiitg/NL1)%8;

            const short ib = 4*sx + sy;

            *(threadgroup S1_2x4 *)(sb + 64*ib + 8*ly) = (S1_2x4)(*((device T1_2x4 *) y));
        }

        il = (il + 2 < nl) ? il + 2 : il % 2;
        x  = (il < 2) ? x + (2 + nl - 1)/nl : x;

        y += NK;

        threadgroup_barrier(mem_flags::mem_threadgroup);

        threadgroup const S0 * lsma = (sa + 4*64*(sgitg%2));
        threadgroup const S1 * lsmb = (sb + 2*64*(sgitg/2));

        FOR_UNROLL (short ik = 0; ik < NK/8; ik++) {
            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 4; i++) {
                simdgroup_load(ma[i], lsma + 64*i, 8, 0, false);
            }

            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 2; i++) {
                simdgroup_load(mb[i], lsmb + 64*i, 8, 0, false);
            }

            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 8; i++){
                simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
            }
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Explain what this code does and identify the inference stage it belongs to.

File: metal/moe.metal

```metal
up_barrier(mem_flags::mem_threadgroup);

            for (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;

                const short lx = (tiitg/NL0)%8;
                const short ly = i%8;

                const short ib = 8*sx + sy;

                *(sa + 64*ib + 8*ly + lx) = loop_k + 16*il + i < args.ne00 ? *((device T0 *) x + i) : 0;
            }
        } else {
            S0_4x4 temp_a;
            dequantize_func(x, il, temp_a);

            threadgroup_barrier(mem_flags::mem_threadgroup);

            FOR_UNROLL (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;

                const short lx = (tiitg/NL0)%8;
                const short ly = i%8;

                const short ib = 8*sx + sy;

                *(sa + 64*ib + 8*ly + lx) = temp_a[i/4][i%4];
            }
        }

        if (FC_mul_mm_bc_inp) {
            for (short i = 0; i < 8; ++i) {
                const short sx = (tiitg%NL1);
                const short sy = (tiitg/NL1)/8;

                const short lx = i;
                const short ly = (tiitg/NL1)%8;

                const short ib = 4*sx + sy;

                *(sb + 64*ib + 8*ly + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
            }
        } else {
            const short sx = (tiitg%NL1);
            const short sy = (tiitg/NL1)/8;

            const short ly = (tiitg/NL1)%8;

            const short ib = 4*sx + sy;

            *(threadgroup S1_2x4 *)(sb + 64*ib + 8*ly) = (S1_2x4)(*((device T1_2x4 *) y));
        }

        il = (il + 2 < nl) ? il + 2 : il % 2;
        x  = (il < 2) ? x + (2 + nl - 1)/nl : x;

        y += NK;

        threadgroup_barrier(mem_flags::mem_threadgroup);

        threadgroup const S0 * lsma = (sa + 4*64*(sgitg%2));
        threadgroup const S1 * lsmb = (sb + 2*64*(sgitg/2));

        FOR_UNROLL (short ik = 0; ik < NK/8; ik++) {
            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 4; i++) {
                simdgroup_load(ma[i], lsma + 64*i, 8, 0, false);
            }

            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 2; i++) {
                simdgroup_load(mb[i], lsmb + 64*i, 8, 0, false);
            }

            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 8; i++){
                simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
            }
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Explain what this code does and identify the inference stage it belongs to.

File: metal/moe.metal

```metal
up_barrier(mem_flags::mem_threadgroup);

            for (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;

                const short lx = (tiitg/NL0)%8;
                const short ly = i%8;

                const short ib = 8*sx + sy;

                *(sa + 64*ib + 8*ly + lx) = loop_k + 16*il + i < args.ne00 ? *((device T0 *) x + i) : 0;
            }
        } else {
            S0_4x4 temp_a;
            dequantize_func(x, il, temp_a);

            threadgroup_barrier(mem_flags::mem_threadgroup);

            FOR_UNROLL (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;

                const short lx = (tiitg/NL0)%8;
                const short ly = i%8;

                const short ib = 8*sx + sy;

                *(sa + 64*ib + 8*ly + lx) = temp_a[i/4][i%4];
            }
        }

        if (FC_mul_mm_bc_inp) {
            for (short i = 0; i < 8; ++i) {
                const short sx = (tiitg%NL1);
                const short sy = (tiitg/NL1)/8;

                const short lx = i;
                const short ly = (tiitg/NL1)%8;

                const short ib = 4*sx + sy;

                *(sb + 64*ib + 8*ly + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
            }
        } else {
            const short sx = (tiitg%NL1);
            const short sy = (tiitg/NL1)/8;

            const short ly = (tiitg/NL1)%8;

            const short ib = 4*sx + sy;

            *(threadgroup S1_2x4 *)(sb + 64*ib + 8*ly) = (S1_2x4)(*((device T1_2x4 *) y));
        }

        il = (il + 2 < nl) ? il + 2 : il % 2;
        x  = (il < 2) ? x + (2 + nl - 1)/nl : x;

        y += NK;

        threadgroup_barrier(mem_flags::mem_threadgroup);

        threadgroup const S0 * lsma = (sa + 4*64*(sgitg%2));
        threadgroup const S1 * lsmb = (sb + 2*64*(sgitg/2));

        FOR_UNROLL (short ik = 0; ik < NK/8; ik++) {
            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 4; i++) {
                simdgroup_load(ma[i], lsma + 64*i, 8, 0, false);
            }

            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 2; i++) {
                simdgroup_load(mb[i], lsmb + 64*i, 8, 0, false);
            }

            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 8; i++){
                simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
            }
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Explain what this code does and identify the inference stage it belongs to.

File: metal/moe.metal

```metal
up_barrier(mem_flags::mem_threadgroup);

            for (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;

                const short lx = (tiitg/NL0)%8;
                const short ly = i%8;

                const short ib = 8*sx + sy;

                *(sa + 64*ib + 8*ly + lx) = loop_k + 16*il + i < args.ne00 ? *((device T0 *) x + i) : 0;
            }
        } else {
            S0_4x4 temp_a;
            dequantize_func(x, il, temp_a);

            threadgroup_barrier(mem_flags::mem_threadgroup);

            FOR_UNROLL (short i = 0; i < 16; i++) {
                const short sx = 2*il0 + i/8;
                const short sy = (tiitg/NL0)/8;

                const short lx = (tiitg/NL0)%8;
                const short ly = i%8;

                const short ib = 8*sx + sy;

                *(sa + 64*ib + 8*ly + lx) = temp_a[i/4][i%4];
            }
        }

        if (FC_mul_mm_bc_inp) {
            for (short i = 0; i < 8; ++i) {
                const short sx = (tiitg%NL1);
                const short sy = (tiitg/NL1)/8;

                const short lx = i;
                const short ly = (tiitg/NL1)%8;

                const short ib = 4*sx + sy;

                *(sb + 64*ib + 8*ly + lx) = loop_k + iy + i < args.ne00 ? (S1) *((device T1 *) y + i) : 0;
            }
        } else {
            const short sx = (tiitg%NL1);
            const short sy = (tiitg/NL1)/8;

            const short ly = (tiitg/NL1)%8;

            const short ib = 4*sx + sy;

            *(threadgroup S1_2x4 *)(sb + 64*ib + 8*ly) = (S1_2x4)(*((device T1_2x4 *) y));
        }

        il = (il + 2 < nl) ? il + 2 : il % 2;
        x  = (il < 2) ? x + (2 + nl - 1)/nl : x;

        y += NK;

        threadgroup_barrier(mem_flags::mem_threadgroup);

        threadgroup const S0 * lsma = (sa + 4*64*(sgitg%2));
        threadgroup const S1 * lsmb = (sb + 2*64*(sgitg/2));

        FOR_UNROLL (short ik = 0; ik < NK/8; ik++) {
            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 4; i++) {
                simdgroup_load(ma[i], lsma + 64*i, 8, 0, false);
            }

            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 2; i++) {
                simdgroup_load(mb[i], lsmb + 64*i, 8, 0, false);
            }

            simdgroup_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 8; i++){
                simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
            }
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
group_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 8; i++){
                simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
            }

            lsma += 8*64;
            lsmb += 4*64;
        }
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    threadgroup float * temp_str = ((threadgroup float *) shmem) + 32*(sgitg&1) + (16*(sgitg >> 1))*NR0;

    for (short i = 0; i < 8; i++) {
        simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*NR0*(i/4), NR0, 0, false);
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    for (short j = sgitg; j < nr1; j += 4) {
        const int idj = ids_i32[im*args.ne21 + r1 + j];

        const short ide = idj % args.ne20;
        const short idt = idj / args.ne20;

        device float  * D  = (device float  *) dst + r0 + ide*args.ne0 + idt*args.ne1*args.ne0;
        device float4 * D4 = (device float4 *) D;

        threadgroup float  * C  = (threadgroup float  *) shmem + j*NR0;
        threadgroup float4 * C4 = (threadgroup float4 *) C;

        int i = tiisg;
        for (; i < nr0/4; i += 32) {
            *(D4 + i) = *(C4 + i);
        }

        i = (4*(nr0/4)) + tiisg;
        for (; i < nr0; i += 32) {
            *(D + i) = *(C + i);
        }
    }
}

typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, float, float2x4>) mul_mm_id;
typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, half, half4x4, half, half2x4>) mul_mm_id_f16_rhs;

// Host-visible batched MoE matmul variants for the DS4 quant formats.
template [[host_name("kernel_mul_mm_id_q8_0_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0,    2,     dequantize_q8_0,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K,    QK_NL, dequantize_q2_K,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    float, float4x4, float, float2x4>;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
group_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 8; i++){
                simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
            }

            lsma += 8*64;
            lsmb += 4*64;
        }
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    threadgroup float * temp_str = ((threadgroup float *) shmem) + 32*(sgitg&1) + (16*(sgitg >> 1))*NR0;

    for (short i = 0; i < 8; i++) {
        simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*NR0*(i/4), NR0, 0, false);
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    for (short j = sgitg; j < nr1; j += 4) {
        const int idj = ids_i32[im*args.ne21 + r1 + j];

        const short ide = idj % args.ne20;
        const short idt = idj / args.ne20;

        device float  * D  = (device float  *) dst + r0 + ide*args.ne0 + idt*args.ne1*args.ne0;
        device float4 * D4 = (device float4 *) D;

        threadgroup float  * C  = (threadgroup float  *) shmem + j*NR0;
        threadgroup float4 * C4 = (threadgroup float4 *) C;

        int i = tiisg;
        for (; i < nr0/4; i += 32) {
            *(D4 + i) = *(C4 + i);
        }

        i = (4*(nr0/4)) + tiisg;
        for (; i < nr0; i += 32) {
            *(D + i) = *(C + i);
        }
    }
}

typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, float, float2x4>) mul_mm_id;
typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, half, half4x4, half, half2x4>) mul_mm_id_f16_rhs;

// Host-visible batched MoE matmul variants for the DS4 quant formats.
template [[host_name("kernel_mul_mm_id_q8_0_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0,    2,     dequantize_q8_0,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K,    QK_NL, dequantize_q2_K,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    float, float4x4, float, float2x4>;
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
group_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 8; i++){
                simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
            }

            lsma += 8*64;
            lsmb += 4*64;
        }
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    threadgroup float * temp_str = ((threadgroup float *) shmem) + 32*(sgitg&1) + (16*(sgitg >> 1))*NR0;

    for (short i = 0; i < 8; i++) {
        simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*NR0*(i/4), NR0, 0, false);
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    for (short j = sgitg; j < nr1; j += 4) {
        const int idj = ids_i32[im*args.ne21 + r1 + j];

        const short ide = idj % args.ne20;
        const short idt = idj / args.ne20;

        device float  * D  = (device float  *) dst + r0 + ide*args.ne0 + idt*args.ne1*args.ne0;
        device float4 * D4 = (device float4 *) D;

        threadgroup float  * C  = (threadgroup float  *) shmem + j*NR0;
        threadgroup float4 * C4 = (threadgroup float4 *) C;

        int i = tiisg;
        for (; i < nr0/4; i += 32) {
            *(D4 + i) = *(C4 + i);
        }

        i = (4*(nr0/4)) + tiisg;
        for (; i < nr0; i += 32) {
            *(D + i) = *(C + i);
        }
    }
}

typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, float, float2x4>) mul_mm_id;
typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, half, half4x4, half, half2x4>) mul_mm_id_f16_rhs;

// Host-visible batched MoE matmul variants for the DS4 quant formats.
template [[host_name("kernel_mul_mm_id_q8_0_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0,    2,     dequantize_q8_0,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K,    QK_NL, dequantize_q2_K,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    float, float4x4, float, float2x4>;
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
group_barrier(mem_flags::mem_none);

            FOR_UNROLL (short i = 0; i < 8; i++){
                simdgroup_multiply_accumulate(mc[i], mb[i/4], ma[i%4], mc[i]);
            }

            lsma += 8*64;
            lsmb += 4*64;
        }
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    threadgroup float * temp_str = ((threadgroup float *) shmem) + 32*(sgitg&1) + (16*(sgitg >> 1))*NR0;

    for (short i = 0; i < 8; i++) {
        simdgroup_store(mc[i], temp_str + 8*(i%4) + 8*NR0*(i/4), NR0, 0, false);
    }

    threadgroup_barrier(mem_flags::mem_threadgroup);

    for (short j = sgitg; j < nr1; j += 4) {
        const int idj = ids_i32[im*args.ne21 + r1 + j];

        const short ide = idj % args.ne20;
        const short idt = idj / args.ne20;

        device float  * D  = (device float  *) dst + r0 + ide*args.ne0 + idt*args.ne1*args.ne0;
        device float4 * D4 = (device float4 *) D;

        threadgroup float  * C  = (threadgroup float  *) shmem + j*NR0;
        threadgroup float4 * C4 = (threadgroup float4 *) C;

        int i = tiisg;
        for (; i < nr0/4; i += 32) {
            *(D4 + i) = *(C4 + i);
        }

        i = (4*(nr0/4)) + tiisg;
        for (; i < nr0; i += 32) {
            *(D + i) = *(C + i);
        }
    }
}

typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, float, float4x4, float, float2x4>) mul_mm_id;
typedef decltype(kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K, QK_NL, dequantize_q2_K, half, half4x4, half, half2x4>) mul_mm_id_f16_rhs;

// Host-visible batched MoE matmul variants for the DS4 quant formats.
template [[host_name("kernel_mul_mm_id_q8_0_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0,    2,     dequantize_q8_0,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K,    QK_NL, dequantize_q2_K,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f32")]]    kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    float, float4x4, float, float2x4>;
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q8_0_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0,    2,     dequantize_q8_0,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K,    QK_NL, dequantize_q2_K,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f16")]] kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, half, half4x4, half, half2x4>;

#undef QK_NL
#undef kmask_iq2xs
#undef ksigns_iq2xs
#undef iq2xxs_grid
#undef QK_K
#undef N_R0_Q2_K
#undef N_R0_Q4_K
#undef N_R0_IQ2_XXS
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q8_0_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0,    2,     dequantize_q8_0,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K,    QK_NL, dequantize_q2_K,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f16")]] kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, half, half4x4, half, half2x4>;

#undef QK_NL
#undef kmask_iq2xs
#undef ksigns_iq2xs
#undef iq2xxs_grid
#undef QK_K
#undef N_R0_Q2_K
#undef N_R0_Q4_K
#undef N_R0_IQ2_XXS
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q8_0_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0,    2,     dequantize_q8_0,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K,    QK_NL, dequantize_q2_K,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f16")]] kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, half, half4x4, half, half2x4>;

#undef QK_NL
#undef kmask_iq2xs
#undef ksigns_iq2xs
#undef iq2xxs_grid
#undef QK_K
#undef N_R0_Q2_K
#undef N_R0_Q4_K
#undef N_R0_IQ2_XXS
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f32")]] kernel mul_mm_id kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, float, float4x4, float, float2x4>;
template [[host_name("kernel_mul_mm_id_q8_0_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q8_0,    2,     dequantize_q8_0,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q2_K_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q2_K,    QK_NL, dequantize_q2_K,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_q4_K_f16")]]    kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_q4_K,    QK_NL, dequantize_q4_K,    half, half4x4, half, half2x4>;
template [[host_name("kernel_mul_mm_id_iq2_xxs_f16")]] kernel mul_mm_id_f16_rhs kernel_mul_mm_id<half, half4x4, simdgroup_half8x8, half, half2x4, simdgroup_half8x8, block_iq2_xxs, QK_NL, dequantize_iq2_xxs, half, half4x4, half, half2x4>;

#undef QK_NL
#undef kmask_iq2xs
#undef ksigns_iq2xs
#undef iq2xxs_grid
#undef QK_K
#undef N_R0_Q2_K
#undef N_R0_Q4_K
#undef N_R0_IQ2_XXS
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
Normal inference
// does not consume gate/up after this point, so the fast path avoids writing the
// clamped intermediates back.  A diagnostic env switch can restore those writes
// when comparing the old multi-kernel intermediate tensors.
kernel void kernel_dsv4_moe_swiglu_weight(
        constant ds4_metal_dsv4_moe_swiglu_weight_args &args,
        device char *gate,
        device char *up,
        device char *mid,
        device const char *weights,
        uint row [[threadgroup_position_in_grid]],
        uint tid [[thread_position_in_threadgroup]],
        uint ntg [[threads_per_threadgroup]]) {
    if (row >= args.rows) return;

    device float *gate_row = (device float *)(gate + (uint64_t)row * args.gate_row_stride);
    device float *up_row   = (device float *)(up   + (uint64_t)row * args.up_row_stride);
    device float *mid_row  = (device float *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
    const float route_weight = w[0];
    const float c = args.clamp_value;

    for (uint i = tid; i < args.width; i += ntg) {
        float g = gate_row[i];
        float u = up_row[i];
        if (c > 1.0e-6f) {
            g = min(g, c);
            u = clamp(u, -c, c);
            if (args.write_clamped != 0) {
                gate_row[i] = g;
                up_row[i] = u;
            }
        }
        const float silu = g / (1.0f + exp(-g));
        mid_row[i] = silu * u * route_weight;
    }
}

// Same routed-MoE activation as above, but stores the down-projection input in
// half precision. The grouped matmul path converts F32 activations to half
// before MMA anyway, so this cuts the large mid write/read traffic without
// changing the effective matmul input precision.
kernel void kernel_dsv4_moe_swiglu_weight_f16(
        constant ds4_metal_dsv4_moe_swiglu_weight_args &args,
        device char *gate,
        device char *up,
        device char *mid,
        device const char *weights,
        uint row [[threadgroup_position_in_grid]],
        uint tid [[thread_position_in_threadgroup]],
        uint ntg [[threads_per_threadgroup]]) {
    if (row >= args.rows) return;

    device float *gate_row = (device float *)(gate + (uint64_t)row * args.gate_row_stride);
    device float *up_row   = (device float *)(up   + (uint64_t)row * args.up_row_stride);
    device half  *mid_row  = (device half  *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
Normal inference
// does not consume gate/up after this point, so the fast path avoids writing the
// clamped intermediates back.  A diagnostic env switch can restore those writes
// when comparing the old multi-kernel intermediate tensors.
kernel void kernel_dsv4_moe_swiglu_weight(
        constant ds4_metal_dsv4_moe_swiglu_weight_args &args,
        device char *gate,
        device char *up,
        device char *mid,
        device const char *weights,
        uint row [[threadgroup_position_in_grid]],
        uint tid [[thread_position_in_threadgroup]],
        uint ntg [[threads_per_threadgroup]]) {
    if (row >= args.rows) return;

    device float *gate_row = (device float *)(gate + (uint64_t)row * args.gate_row_stride);
    device float *up_row   = (device float *)(up   + (uint64_t)row * args.up_row_stride);
    device float *mid_row  = (device float *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
    const float route_weight = w[0];
    const float c = args.clamp_value;

    for (uint i = tid; i < args.width; i += ntg) {
        float g = gate_row[i];
        float u = up_row[i];
        if (c > 1.0e-6f) {
            g = min(g, c);
            u = clamp(u, -c, c);
            if (args.write_clamped != 0) {
                gate_row[i] = g;
                up_row[i] = u;
            }
        }
        const float silu = g / (1.0f + exp(-g));
        mid_row[i] = silu * u * route_weight;
    }
}

// Same routed-MoE activation as above, but stores the down-projection input in
// half precision. The grouped matmul path converts F32 activations to half
// before MMA anyway, so this cuts the large mid write/read traffic without
// changing the effective matmul input precision.
kernel void kernel_dsv4_moe_swiglu_weight_f16(
        constant ds4_metal_dsv4_moe_swiglu_weight_args &args,
        device char *gate,
        device char *up,
        device char *mid,
        device const char *weights,
        uint row [[threadgroup_position_in_grid]],
        uint tid [[thread_position_in_threadgroup]],
        uint ntg [[threads_per_threadgroup]]) {
    if (row >= args.rows) return;

    device float *gate_row = (device float *)(gate + (uint64_t)row * args.gate_row_stride);
    device float *up_row   = (device float *)(up   + (uint64_t)row * args.up_row_stride);
    device half  *mid_row  = (device half  *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
```<｜Assistant｜></think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
Normal inference
// does not consume gate/up after this point, so the fast path avoids writing the
// clamped intermediates back.  A diagnostic env switch can restore those writes
// when comparing the old multi-kernel intermediate tensors.
kernel void kernel_dsv4_moe_swiglu_weight(
        constant ds4_metal_dsv4_moe_swiglu_weight_args &args,
        device char *gate,
        device char *up,
        device char *mid,
        device const char *weights,
        uint row [[threadgroup_position_in_grid]],
        uint tid [[thread_position_in_threadgroup]],
        uint ntg [[threads_per_threadgroup]]) {
    if (row >= args.rows) return;

    device float *gate_row = (device float *)(gate + (uint64_t)row * args.gate_row_stride);
    device float *up_row   = (device float *)(up   + (uint64_t)row * args.up_row_stride);
    device float *mid_row  = (device float *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
    const float route_weight = w[0];
    const float c = args.clamp_value;

    for (uint i = tid; i < args.width; i += ntg) {
        float g = gate_row[i];
        float u = up_row[i];
        if (c > 1.0e-6f) {
            g = min(g, c);
            u = clamp(u, -c, c);
            if (args.write_clamped != 0) {
                gate_row[i] = g;
                up_row[i] = u;
            }
        }
        const float silu = g / (1.0f + exp(-g));
        mid_row[i] = silu * u * route_weight;
    }
}

// Same routed-MoE activation as above, but stores the down-projection input in
// half precision. The grouped matmul path converts F32 activations to half
// before MMA anyway, so this cuts the large mid write/read traffic without
// changing the effective matmul input precision.
kernel void kernel_dsv4_moe_swiglu_weight_f16(
        constant ds4_metal_dsv4_moe_swiglu_weight_args &args,
        device char *gate,
        device char *up,
        device char *mid,
        device const char *weights,
        uint row [[threadgroup_position_in_grid]],
        uint tid [[thread_position_in_threadgroup]],
        uint ntg [[threads_per_threadgroup]]) {
    if (row >= args.rows) return;

    device float *gate_row = (device float *)(gate + (uint64_t)row * args.gate_row_stride);
    device float *up_row   = (device float *)(up   + (uint64_t)row * args.up_row_stride);
    device half  *mid_row  = (device half  *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Suggest a minimal correctness-preserving optimization for this excerpt.

File: metal/moe.metal

```metal
Normal inference
// does not consume gate/up after this point, so the fast path avoids writing the
// clamped intermediates back.  A diagnostic env switch can restore those writes
// when comparing the old multi-kernel intermediate tensors.
kernel void kernel_dsv4_moe_swiglu_weight(
        constant ds4_metal_dsv4_moe_swiglu_weight_args &args,
        device char *gate,
        device char *up,
        device char *mid,
        device const char *weights,
        uint row [[threadgroup_position_in_grid]],
        uint tid [[thread_position_in_threadgroup]],
        uint ntg [[threads_per_threadgroup]]) {
    if (row >= args.rows) return;

    device float *gate_row = (device float *)(gate + (uint64_t)row * args.gate_row_stride);
    device float *up_row   = (device float *)(up   + (uint64_t)row * args.up_row_stride);
    device float *mid_row  = (device float *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
    const float route_weight = w[0];
    const float c = args.clamp_value;

    for (uint i = tid; i < args.width; i += ntg) {
        float g = gate_row[i];
        float u = up_row[i];
        if (c > 1.0e-6f) {
            g = min(g, c);
            u = clamp(u, -c, c);
            if (args.write_clamped != 0) {
                gate_row[i] = g;
                up_row[i] = u;
            }
        }
        const float silu = g / (1.0f + exp(-g));
        mid_row[i] = silu * u * route_weight;
    }
}

// Same routed-MoE activation as above, but stores the down-projection input in
// half precision. The grouped matmul path converts F32 activations to half
// before MMA anyway, so this cuts the large mid write/read traffic without
// changing the effective matmul input precision.
kernel void kernel_dsv4_moe_swiglu_weight_f16(
        constant ds4_metal_dsv4_moe_swiglu_weight_args &args,
        device char *gate,
        device char *up,
        device char *mid,
        device const char *weights,
        uint row [[threadgroup_position_in_grid]],
        uint tid [[thread_position_in_threadgroup]],
        uint ntg [[threads_per_threadgroup]]) {
    if (row >= args.rows) return;

    device float *gate_row = (device float *)(gate + (uint64_t)row * args.gate_row_stride);
    device float *up_row   = (device float *)(up   + (uint64_t)row * args.up_row_stride);
    device half  *mid_row  = (device half  *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
```<｜Assistant｜><think>


[System] You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.

[User]
Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
e half  *mid_row  = (device half  *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
    const float route_weight = w[0];
    const float c = args.clamp_value;

    for (uint i = tid; i < args.width; i += ntg) {
        float g = gate_row[i];
        float u = up_row[i];
        if (c > 1.0e-6f) {
            g = min(g, c);
            u = clamp(u, -c, c);
            if (args.write_clamped != 0) {
                gate_row[i] = g;
                up_row[i] = u;
            }
        }
        const float silu = g / (1.0f + exp(-g));
        mid_row[i] = (half)(silu * u * route_weight);
    }
}

template <typename type4x4>
void dequantize_q2_K(device const block_q2_K *xb, short il, thread type4x4 & reg) {
    const float d = xb->d;
    const float min = xb->dmin;
    device const uint8_t * q = (device const uint8_t *)xb->qs;
    float dl, ml;
    uint8_t sc = xb->scales[il];

    q = q + 32*(il/8) + 16*(il&1);
    il = (il/2)%4;

    half  coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
    uchar mask = il>1 ? (il>2 ? 192    : 48)     : (il>0 ? 12    : 3);
    dl = d * (sc & 0xF) * coef, ml = min * (sc >> 4);
    for (int i = 0; i < 16; ++i) {
        reg[i/4][i%4] = dl * (q[i] & mask) - ml;
    }
}

static inline uchar2 get_scale_min_k4_just2(int j, int k, device const uchar * q) {
    return j < 4 ? uchar2{uchar(q[j+0+k] & 63), uchar(q[j+4+k] & 63)}
                 : uchar2{uchar((q[j+4+k] & 0xF) | ((q[j-4+k] & 0xc0) >> 2)),
                          uchar((q[j+4+k] >> 4) | ((q[j-0+k] & 0xc0) >> 2))};
}

template <typename type4x4>
void dequantize_q4_K(device const block_q4_K *xb, short il, thread type4x4 &reg) {
    device const uchar *q = xb->qs;

    short is = (il / 4) * 2;
    q = q + (il / 4) * 32 + 16 * (il & 1);
    il = il & 3;
    const uchar2 sc = get_scale_min_k4_just2(is, il / 2, xb->scales);
    const float d = il < 2 ? xb->d : xb->d / 16.h;
    const float min = xb->dmin;
    const float dl = d * sc[0];
    const float ml = min * sc[1];

    const ushort mask = il < 2 ? 0x0F : 0xF0;
    for (int i = 0; i < 16; ++i) {
        reg[i / 4][i % 4] = dl * (q[i] & mask) - ml;
    }
}

template <typename type4x4>
void dequantize_iq2_xxs(device const block_iq2_xxs * xb, short il, thread type4x4 & reg) {
    const float d = xb->d;
    const int ib32 = il/2;
    il = il%2;
    device const uint16_t * q2 = xb->qs + 4*ib32;
    const uint32_t aux32_g = q2[0] | (q2[1] << 16);
    const uint32_t aux32_s = q2[2] | (q2[3] << 16);
```

<｜begin▁of▁sentence｜>You are DeepSeek V4 Flash running locally. Answer accurately, preserve technical details, and use tools only when the prompt asks for tool use.<｜User｜>Trova bug sottili e spiega quali invarianti dell'inferenza possono rompersi.

File: metal/moe.metal

```metal
e half  *mid_row  = (device half  *)(mid  + (uint64_t)row * args.mid_row_stride);
    device const float *w  = (device const float *)(weights + (uint64_t)row * args.weight_stride);
    const float route_weight = w[0];
    const float c = args.clamp_value;

    for (uint i = tid; i < args.width; i += ntg) {
        float g = gate_row[i];
        float u = up_row[i];
        if (c > 1.0e-6f) {
            g = min(g, c);
            u = clamp(u, -c, c);
            if (args.write_clamped != 0) {
                gate_row[i] = g;
                up_row[i] = u;
            }
        }
        const float silu = g / (1.0f + exp(-g));
        mid_row[i] = (half)(silu * u * route_weight);
    }
}

template <typename type4x4>
void dequantize_q2_K(device const block_q2_K *xb, short il, thread type4x4 & reg) {
    const float d = xb->d;
    const float min = xb->dmin;
    device const uint8_t * q = (device const uint8_t *)xb->qs;
    float dl, ml;
    uint8_t sc = xb->scales[il];

    q = q + 32*(il/8) + 16*(il&1);
    il = (il/2)%4;

    half  coef = il>1 ? (il>2 ? 1/64.h : 1/16.h) : (il>0 ? 1/4.h : 1.h);
    uchar mask = il>1 ? (il>2 ? 192    : 48)     : (il>0 ? 12    : 3);
    dl = d * (sc & 0xF) * coef, ml = min * (sc >> 4);
    for (int i = 0; i < 16; ++i) {
        reg[i/4][i%4] = dl * (q[i] & mask) - ml;
    }
}

static inline uchar2 get_scale_min_k4_just2(int j, int k, device const uchar * q) {
    return j < 4 ? uchar2{uchar(q[j+0+k] & 63), uchar(q[j+4+k] & 63)}
                 : uchar2{uchar((q[j+4+k] & 0xF) | ((q[j-4+k] & 0xc0) >> 2)),
                          uchar((q[j+4+k] >> 4) | ((q[j-0+k] & 0xc0) >> 2))};
}

template <typename type4x4>
void dequantize_q4_K(device const block_q4_K *xb, short il, thread type4x4 &reg) {
    device const uchar *q = xb->qs;

    short is = (il / 4) * 2;
    q = q + (il / 4) * 32 + 16 * (il & 1);
    il = il & 3;
    const uchar2 sc = get_scale_min_k4_just2(is, il / 2, xb->scales);
    const float d = il < 2 ? xb->d : xb->d / 16.h;
    const float min = xb->dmin;
    const float dl = d * sc[0];
    const float ml = min * sc[1];

    const ushort mask = il < 2 ? 0x0F : 0xF0;
    for (int i = 0; i < 16; ++i) {
        reg[i / 4][i % 4] = dl * (q[i] & mask) - ml;
    }
}

template <typename type4x4>
void dequantize_iq2_xxs(device const block_iq2_xxs * xb, short il, thread type4x4 & reg) {
    const float d = xb->d;
    const int ib32 = il/2;
    il = il%2;
    device const uint16_t * q2 = xb->qs + 4*ib32;
    const uint32_t aux32_g = q2[0] | (q2[1] << 16);
    const uint32_t aux32_s = q2[2] | (q2[3] << 16);
```<｜Assistant｜></think>