Skip to content

Commit

Permalink
metal : add Q2_K implementation (ggerganov#1762)
Browse files Browse the repository at this point in the history 
* metal : add Q2_K implementation

27.1 ms / token on M2 Max 30-core GPU, so about the
same speed as Q4_0. Memory throughput is ~156 GB/s.

The access pattern used in the Q2_K
CUDA implementation resulted in significantly lower
performance (~31 ms/token).

* Fixing merge conflicts

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
  • Loading branch information
@ikawrakow @Kawrakow
ikawrakow and Kawrakow authored Jun 8, 2023
1 parent 0bf7cf1 commit 72ff528
Show file tree
Hide file tree
Showing 2 changed files with 200 additions and 18 deletions.
17 changes: 17 additions & 0 deletions ggml-metal.m
View file
Original file line number Diff line number Diff line change
Expand Up @@ -49,11 +49,13 @@
GGML_METAL_DECL_KERNEL(diag_mask_inf);
GGML_METAL_DECL_KERNEL(get_rows_f16);
GGML_METAL_DECL_KERNEL(get_rows_q4_0);
GGML_METAL_DECL_KERNEL(get_rows_q2_k);
GGML_METAL_DECL_KERNEL(get_rows_q4_k);
GGML_METAL_DECL_KERNEL(get_rows_q6_k);
GGML_METAL_DECL_KERNEL(rms_norm);
GGML_METAL_DECL_KERNEL(mul_mat_f16_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q4_0_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q2_k_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q4_k_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q6_k_f32);
GGML_METAL_DECL_KERNEL(rope);
Expand Down Expand Up @@ -137,11 +139,13 @@
GGML_METAL_ADD_KERNEL(diag_mask_inf);
GGML_METAL_ADD_KERNEL(get_rows_f16);
GGML_METAL_ADD_KERNEL(get_rows_q4_0);
GGML_METAL_ADD_KERNEL(get_rows_q2_k);
GGML_METAL_ADD_KERNEL(get_rows_q4_k);
GGML_METAL_ADD_KERNEL(get_rows_q6_k);
GGML_METAL_ADD_KERNEL(rms_norm);
GGML_METAL_ADD_KERNEL(mul_mat_f16_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q4_0_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q2_k_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q4_k_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q6_k_f32);
GGML_METAL_ADD_KERNEL(rope);
Expand Down Expand Up @@ -525,6 +529,15 @@ void ggml_metal_graph_compute(
nth1 = 4;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_0_f32];
} break;
case GGML_TYPE_Q2_K:
{
GGML_ASSERT(ne02 == 1);
GGML_ASSERT(ne12 == 1);

nth0 = 4;
nth1 = 16;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q2_k_f32];
} break;
case GGML_TYPE_Q4_K:
{
GGML_ASSERT(ne02 == 1);
Expand Down Expand Up @@ -570,6 +583,9 @@ void ggml_metal_graph_compute(
if (src0t == GGML_TYPE_Q4_0) {
[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} else if (src0t == GGML_TYPE_Q2_K) {
[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake(ne01, 1, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
} else if (src0t == GGML_TYPE_Q4_K) {
[encoder setThreadgroupMemoryLength:nth0*nth1*sizeof(float) atIndex:0];
[encoder dispatchThreadgroups:MTLSizeMake(ne01, ne11, 1) threadsPerThreadgroup:MTLSizeMake(nth0, nth1, 1)];
Expand All @@ -591,6 +607,7 @@ void ggml_metal_graph_compute(
switch (src0->type) {
case GGML_TYPE_F16: [encoder setComputePipelineState:ctx->pipeline_get_rows_f16]; break;
case GGML_TYPE_Q4_0: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_0]; break;
case GGML_TYPE_Q2_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q2_k]; break;
case GGML_TYPE_Q4_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_k]; break;
case GGML_TYPE_Q6_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q6_k]; break;
default: GGML_ASSERT(false && "not implemented");
Expand Down
201 changes: 183 additions & 18 deletions ggml-metal.metal
View file
Original file line number Diff line number Diff line change
Expand Up @@ -527,6 +527,13 @@ kernel void kernel_cpy_f32_f32(

#define QK_K 256

typedef struct {
uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits
uint8_t qs[QK_K/4]; // quants
half d; // super-block scale for quantized scales
half dmin; // super-block scale for quantized mins
} block_q2_k;

typedef struct {
half d; // super-block scale for quantized scales
half dmin; // super-block scale for quantized mins
Expand Down Expand Up @@ -555,6 +562,41 @@ static inline uchar4 get_scale_min_k4(int j, device const uint8_t * q) {
return r;
}

//========================================== dequantization =============================

static void dequantize_row_q2_k(device const block_q2_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;

int is = 0;
float dl, ml;
for (int n = 0; n < QK_K; n += 128) {
int shift = 0;
for (int j = 0; j < 4; ++j) {

uint8_t sc = x[i].scales[is++];
dl = d * (sc & 0xF); ml = min * (sc >> 4);
for (int l = 0; l < 16; ++l) *y++ = dl * ((int8_t)((q[l] >> shift) & 3)) - ml;

sc = x[i].scales[is++];
dl = d * (sc & 0xF); ml = min * (sc >> 4);
for (int l = 0; l < 16; ++l) *y++ = dl * ((int8_t)((q[l+16] >> shift) & 3)) - ml;

shift += 2;
}
q += 32;
}

}
}

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;
Expand Down Expand Up @@ -586,12 +628,12 @@ static void dequantize_row_q6_k(device const block_q6_k * x, device float * y, i

for (int i = 0; i < nb; i++) {

const float d = x[i].d;

device const uint8_t * ql = x[i].ql;
device const uint8_t * qh = x[i].qh;
device const int8_t * sc = x[i].scales;

const float d = x[i].d;

for (int n = 0; n < QK_K; n += 128) {
for (int l = 0; l < 32; ++l) {
int is = l/16;
Expand All @@ -612,6 +654,22 @@ static void dequantize_row_q6_k(device const block_q6_k * x, device float * y, i
}
}

kernel void kernel_get_rows_q2_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_q2_k(
(device const block_q2_k *) ((device char *) src0 + r*nb01),
(device float *) ((device char *) dst + i*nb1), ne00);
}

kernel void kernel_get_rows_q4_k(
device const void * src0,
device const int * src1,
Expand All @@ -628,6 +686,129 @@ kernel void kernel_get_rows_q4_k(
(device float *) ((device char *) dst + i*nb1), ne00);
}

kernel void kernel_get_rows_q6_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_q6_k(
(device const block_q6_k *) ((device char *) src0 + r*nb01),
(device float *) ((device char *) dst + i*nb1), ne00);
}

//====================================== dot products =========================

kernel void kernel_mul_mat_q2_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_q2_k * x = (device const block_q2_k *) src0 + r0*nb;
device const float * yy = (device const float *) src1 + r1*ne10;

const int nth = tptg.x*tptg.y;
const int 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 ip = il/2; // 0 or 1
const int shift1 = 4*(il%2);// 0 or 4
const int shift2 = shift1+2;// 2 or 6
const int n = 8;
const int is = 4*il + (n*ir)/16;

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*ip + n*ir;
device const uint8_t * scales = x[i].scales + is;

uint8_t d1 = scales[0] & 0xF;
uint8_t m1 = scales[0] >> 4;
uint8_t d2 = scales[2] & 0xF;
uint8_t m2 = scales[2] >> 4;

device const float * y = yy + i*QK_K + 64*il + n*ir;

const float dall = (float)x[i].d;
const float dmin = (float)x[i].dmin;

float4 s = {0.f, 0.f, 0.f, 0.f};
for (int l = 0; l < n; ++l) {
s[0] += y[l+ 0] * ((q[l] >> shift1) & 3); s[1] += y[l+ 0];
s[2] += y[l+32] * ((q[l] >> shift2) & 3); s[3] += y[l+32];
}
sumf += dall * (s[0] * d1 + s[2] * d2) - dmin * (s[1] * m1 + s[3] * m2);


}
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];
//}
}

kernel void kernel_mul_mat_q4_k_f32(
device const void * src0,
device const float * src1,
Expand Down Expand Up @@ -724,22 +905,6 @@ kernel void kernel_mul_mat_q4_k_f32(
//}
}

kernel void kernel_get_rows_q6_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_q6_k(
(device const block_q6_k *) ((device char *) src0 + r*nb01),
(device float *) ((device char *) dst + i*nb1), ne00);
}

kernel void kernel_mul_mat_q6_k_f32(
device const void * src0,
device const float * src1,
Expand Down

0 comments on commit 72ff528

Please sign in to comment.