diff options
author | Kawrakow <48489457+ikawrakow@users.noreply.github.com> | 2023-06-08 10:08:23 +0300 |
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committer | GitHub <noreply@github.com> | 2023-06-08 10:08:23 +0300 |
commit | 4161bdc04debb70bf5f275492b4d89fd9330087c (patch) | |
tree | 9b0c6325e720b101d67ec2415bc0d69e4fd89379 /ggml-metal.metal | |
parent | 0035858273ebe0694926bf4414d279f3e1cd109d (diff) |
metal : add Q4_K implementation (#1733)
* Metal implementation for Q4_K
Very slow for now:
42 ms / token, Q4_0 runs in 28 ms/token on my
30-core M2 Max GPU.
* Optimizing Q4_K on metal
The first token always takes longer, I guess because
the metal kernel is being jit-compiled.
So, using n = 128 to measure time.
At this point Q4_K takes 29.5 ms / token
compared to 27.2 ms / token for Q4_0.
Quite a bit better than the initial attempt,
but still not good enough.
* Optimizing q4_K metal dot some more
For n = 256 it is now 28.1 ms/token compared to
27 ms/token for q4_0.
* Fix after merge with master
---------
Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
Diffstat (limited to 'ggml-metal.metal')
-rw-r--r-- | ggml-metal.metal | 162 |
1 files changed, 162 insertions, 0 deletions
diff --git a/ggml-metal.metal b/ggml-metal.metal index a359beb..cbcd59a 100644 --- a/ggml-metal.metal +++ b/ggml-metal.metal @@ -503,3 +503,165 @@ kernel void kernel_cpy_f32_f32( dst_data[i00] = src[0]; } } + +//============================================ k-quants ====================================================== + +#define QK_K 256 + +typedef struct { + half d; // super-block scale for quantized scales + half dmin; // super-block scale for quantized mins + uint8_t scales[3*QK_K/64]; // scales and mins, quantized with 6 bits + uint8_t qs[QK_K/2]; // 4--bit quants +} block_q4_k; + +static inline uchar4 get_scale_min_k4(int j, device const uint8_t * q) { + uchar4 r; + if (j < 4) { + r[0] = q[j+0] & 63; r[1] = q[j+4] & 63; + r[2] = q[j+1] & 63; r[3] = q[j+5] & 63; + } else { + r[0] = (q[j+4] & 0xF) | ((q[j-4] >> 6) << 4); + r[1] = (q[j+4] >> 4) | ((q[j-0] >> 6) << 4); + r[2] = (q[j+5] & 0xF) | ((q[j-3] >> 6) << 4); + r[3] = (q[j+5] >> 4) | ((q[j+1] >> 6) << 4); + } + return r; +} + +static void dequantize_row_q4_k(device const block_q4_k * x, device float * y, int k) { + assert(k % QK_K == 0); + const int nb = k / QK_K; + + for (int i = 0; i < nb; i++) { + + const float d = x[i].d; + const float min = x[i].dmin; + + device const uint8_t * q = x[i].qs; + device const uint8_t * scales = x[i].scales; + + int is = 0; + for (int j = 0; j < QK_K; j += 64) { + const uchar4 sc = get_scale_min_k4(is, scales); + const float d1 = d * sc[0]; const float m1 = min * sc[1]; + const float d2 = d * sc[2]; const float m2 = min * sc[3]; + for (int l = 0; l < 32; ++l) *y++ = d1 * (q[l] & 0xF) - m1; + for (int l = 0; l < 32; ++l) *y++ = d2 * (q[l] >> 4) - m2; + q += 32; is += 2; + } + + } +} + +kernel void kernel_get_rows_q4_k( + device const void * src0, + device const int * src1, + device float * dst, + constant int64_t & ne00, + constant uint64_t & nb01, + constant uint64_t & nb1, + uint tpig[[thread_position_in_grid]]) { + const int i = tpig; + const int r = ((device int32_t *) src1)[i]; + + dequantize_row_q4_k( + (device const block_q4_k *) ((device char *) src0 + r*nb01), + (device float *) ((device char *) dst + i*nb1), ne00); +} + +kernel void kernel_mul_mat_q4_k_f32( + device const void * src0, + device const float * src1, + device float * dst, + constant int64_t & ne00, + constant int64_t & ne01, + constant uint64_t & nb00, + constant uint64_t & nb01, + constant uint64_t & nb02, + constant int64_t & ne10, + constant int64_t & ne11, + constant uint64_t & nb10, + constant uint64_t & nb11, + constant uint64_t & nb12, + constant int64_t & ne0, + constant int64_t & ne1, + threadgroup float * sum [[threadgroup(0)]], + uint2 tgpig[[threadgroup_position_in_grid]], + uint2 tpig[[thread_position_in_grid]], // we don't use this for now + uint2 tpitg[[thread_position_in_threadgroup]], + uint2 tptg[[threads_per_threadgroup]]) { + + const int nb = ne00/QK_K; + + const int64_t r0 = tgpig.x; + const int64_t r1 = tgpig.y; + + device const block_q4_k * x = (device const block_q4_k *) src0 + r0*nb; + device const float * yy = (device const float *) src1 + r1*ne10; + + const uint nth = tptg.x*tptg.y; + const uint ith = tptg.y*tpitg.x + tpitg.y; + + const int tid = tpitg.y; // 0...16 + const int il = tid/4; // 0...3 + const int ir = tid%4; // 0...3 + const int n = 8; + const int is = 2*il; + + sum[ith] = 0.0f; + + float sumf = 0; + for (int i = tpitg.x; i < nb; i += tptg.x) { + + device const uint8_t * q = (x + i)->qs + 32*il + n*ir; + device const float * y = yy + i*QK_K + 64*il + n*ir; + device const uint8_t * scales = (x + i)->scales; + + const float dall = (float)((x + i)->d); + const float dmin = (float)((x + i)->dmin); + + const uchar4 sc = get_scale_min_k4(is, scales); + + float4 s = {0.f, 0.f, 0.f, 0.f}; + for (int l = 0; l < n; ++l) { + s[0] += y[l+ 0] * (q[l] & 0xF); s[1] += y[l+ 0]; + s[2] += y[l+32] * (q[l] >> 4); s[3] += y[l+32]; + } + sumf += dall * (s[0] * sc[0] + s[2] * sc[2]) - dmin * (s[1] * sc[1] + s[3] * sc[3]); + + } + sum[ith] = sumf; + + // + // Accumulate the sum from all threads in the threadgroup + // This version is slightly faster than the commented out one below, + // which I copy-pasted from ggerganov's q4_0 dot product for metal. + // + threadgroup_barrier(mem_flags::mem_threadgroup); + if (ith%4 == 0) { + for (int i = 1; i < 4; ++i) sum[ith] += sum[ith + i]; + } + threadgroup_barrier(mem_flags::mem_threadgroup); + if (ith%16 == 0) { + for (int i = 4; i < 16; i += 4) sum[ith] += sum[ith + i]; + } + threadgroup_barrier(mem_flags::mem_threadgroup); + if (ith == 0) { + for (int i = 16; i < nth; i += 16) sum[0] += sum[i]; + dst[r1*ne0 + r0] = sum[0]; + } + + //// accumulate the sum from all threads in the threadgroup + //threadgroup_barrier(mem_flags::mem_threadgroup); + //for (uint i = nth/2; i > 0; i /= 2) { + // if (ith < i) { + // sum[ith] += sum[ith + i]; + // } + // threadgroup_barrier(mem_flags::mem_threadgroup); + //} + + //if (ith == 0) { + // dst[r1*ne0 + r0] = sum[0]; + //} +} |