aditya/llama.cpp
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k-quants : support for super-block size of 64 (#2001)

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* k_quants: WIP super-blocks with 64 weights

* k_quants: WIP super-blocks with 64 weights

Q6_K scalar and AVX2 works

* k_quants: WIP super-blocks with 64 weights

Q4_K scalar and AVX2 works

* k_quants: WIP super-blocks with 64 weights

Q2_K scalar and AVX2 works. Q2_K is way too slow (it is actually slower
than the scalar implementation)

* k_quants: WIP super-blocks with 64 weights

Q3_K scalar and AVX2 works.

* k_quants: WIP super-blocks with 64 weights

Q5_K scalar and AVX2 works, and with that all
k_quants are done on AVX2 and scalar

* k_quants: WIP super-blocks with 64 weights

Q6_K working on CUDA. Cannot make it run quite as gast as
with super-blocks with 256 weigths: 8% slower on 4080,
20% slower on the 1660 (but there we fit 1 less layer on the
GPU because pf the larger model size), so some fraction of
these 20% is due to that,

* k_quants: WIP super-blocks with 64 weights

Q4_K working on CUDA. ~10% slower on GTX-1660,
16% slower on 4080.

* k_quants: WIP super-blocks with 64 weights

Q2_K working on CUDA. ~3% slower on GTX-1660,
10% slower on 4080.

* k_quants: WIP super-blocks with 64 weights

Q3_K working on CUDA.

* k_quants: WIP super-blocks with 64 weights

Q5_K working on CUDA, and with this CUDA is done.

* k_quants: WIP super-blocks with 64 weights

Q6_K working on ARM_NEON

* k_quants: WIP super-blocks with 64 weights

Q4_K working on ARM_NEON, but quite a bit slower than 256 weights

* k_quants: WIP super-blocks with 64 weights

Q2_K working on ARM_NEON, but quite a bit slower than 256 weights

* k_quants: WIP super-blocks with 64 weights

Q3_K working on ARM_NEON, but quite a bit slower than 256 weights.

* k_quants: WIP super-blocks with 64 weights

Q5_K working on ARM_NEON, but quite a bit slower than 256 weights.

With that, we have full support for ARM_NEON, although
performance is not quite there.

* k_quants: WIP super-blocks with 64 weights

Slightly more efficient Q3_K and Q5_K

* k_quants: WIP super-blocks with 64 weights

Another small improvement for Q3_K and Q5_K on ARM_NEON

* k_quants: WIP super-blocks with 64 weights

Yet another speedup for Q5_K on ARM_NEON.
We are now within 10% of the QK_K = 256 version.

* k_quants: WIP super-blocks with 64 weights

* We are able to pass preprocessor macros to the Metal
  compiler
* Q6_K works and is actually slightly more efficient than
  the QK_K = 256 version (25.2 ms vs 25.8 ms)

* k_quants: WIP super-blocks with 64 weights

Q4_K works on Metal and is actually slightly faster
than QK_K = 256 (21.95 ms vs 24.0 ms).

* k_quants: WIP super-blocks with 64 weights

Q2_K works on Metal and is very slightly faster
than QK_K = 256 (23.8 ms vs 24.2 ms).

* k_quants: WIP super-blocks with 64 weights

Q3_K works on Metal and is slightly faster
than QK_K = 256 (26.6 ms vs 28.3 ms).

* k_quants: WIP super-blocks with 64 weights

Q5_K works on Metal and is slightly faster
than QK_K = 256 (23.7 ms vs 26.3 ms).

* k_quants: call them _K, not _k, also on Metal

* k_quants: correctly define QK_K in llama.cpp

* Fixed bug in q4_K quantization added with the 64-block addition

* Simplify via lambda

* k_quants: swicth Q3_K to 4-bit scales when QK_K = 64

Otherwise there isn't much benefit from this
quantization type. There is some very slight loss
in accuracy, but we reduce size by ~7%.
E.g., for OpenLLaMA-3B, Q3_K_S perplexity is
8.6131 with 8-bit scales and 8.6352 with 4-bit,
while file size decreases from 1.53G to 1.44G.

* k_quants: switch Q4_K to 4-bit scales when QK_K = 64

 Here the loss in accuracy is greater than for Q3_K,
 but the Q4_K points still move further to the left on
 the perplexity vs size curve.

* k_quants: forgot to add the Metal changes in last commit

* k_quants: change Q5_K to be type 0 when QK_K = 64

Still needs AVX2 implementation

* k_quants: AVX2 implementation for new 64-weight Q5_K

* k_quants: 10% faster ARM_NEON Q5_K dot product

* k_quants: fixed issue caused by merging with master

---------

Co-authored-by: Iwan Kawrakow <iwan.kawrakow@gmail.com>
This commit is contained in:
Kawrakow 2023-06-26 19:43:07 +03:00 committed by GitHub
parent cbebf61ca7
commit 6769e944c7
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
8 changed files with 1880 additions and 201 deletions
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14
CMakeLists.txt
View file

@ -75,6 +75,7 @@ set(LLAMA_CUDA_KQUANTS_ITER "2" CACHE STRING "llama: iters./thread per block for
option(LLAMA_CLBLAST "llama: use CLBlast" OFF)
option(LLAMA_METAL "llama: use Metal" OFF)
option(LLAMA_K_QUANTS "llama: use k-quants" ON)
option(LLAMA_QKK_64 "llama: use super-block size of 64 for k-quants" OFF)
option(LLAMA_BUILD_TESTS "llama: build tests" ${LLAMA_STANDALONE})
option(LLAMA_BUILD_EXAMPLES "llama: build examples" ${LLAMA_STANDALONE})
@ -225,6 +226,14 @@ if (LLAMA_BLAS)
endif()
endif()
if (LLAMA_K_QUANTS)
set(GGML_SOURCES_EXTRA ${GGML_SOURCES_EXTRA} k_quants.c k_quants.h)
add_compile_definitions(GGML_USE_K_QUANTS)
if (LLAMA_QKK_64)
add_compile_definitions(GGML_QKK_64)
endif()
endif()
if (LLAMA_CUBLAS)
cmake_minimum_required(VERSION 3.17)
@ -289,11 +298,6 @@ if (LLAMA_METAL)
)
endif()
if (LLAMA_K_QUANTS)
set(GGML_SOURCES_EXTRA ${GGML_SOURCES_EXTRA} k_quants.c k_quants.h)
add_compile_definitions(GGML_USE_K_QUANTS)
endif()
if (LLAMA_CLBLAST)
find_package(CLBlast)
if (CLBlast_FOUND)

9
Makefile
View file

@ -43,8 +43,11 @@ endif
# keep standard at C11 and C++11
# -Ofast tends to produce faster code, but may not be available for some compilers.
#OPT = -Ofast
ifdef LLAMA_FAST
OPT = -Ofast
else
OPT = -O3
endif
CFLAGS = -I. $(OPT) -std=c11 -fPIC
CXXFLAGS = -I. -I./examples $(OPT) -std=c++11 -fPIC
LDFLAGS =
@ -131,6 +134,10 @@ ifndef LLAMA_NO_K_QUANTS
CFLAGS += -DGGML_USE_K_QUANTS
CXXFLAGS += -DGGML_USE_K_QUANTS
OBJS += k_quants.o
ifdef LLAMA_QKK_64
CFLAGS += -DGGML_QKK_64
CXXFLAGS += -DGGML_QKK_64
endif
endif
ifndef LLAMA_NO_ACCELERATE

370
ggml-cuda.cu
View file

@ -117,7 +117,13 @@ static_assert(sizeof(block_q8_0) == sizeof(ggml_fp16_t) + QK8_0, "wrong q8_0 blo
//================================= k-quants
#ifdef GGML_QKK_64
#define QK_K 64
#define K_SCALE_SIZE 4
#else
#define QK_K 256
#define K_SCALE_SIZE 12
#endif
typedef struct {
uint8_t scales[QK_K/16]; // scales and mins, quantized with 4 bits
@ -128,13 +134,25 @@ typedef struct {
static_assert(sizeof(block_q2_K) == 2*sizeof(ggml_fp16_t) + QK_K/16 + QK_K/4, "wrong q2_K block size/padding");
typedef struct {
uint8_t hmask[QK_K/8];
uint8_t qs[QK_K/4]; // nibbles / quants
uint8_t scales[3*QK_K/64];
half d;
uint8_t hmask[QK_K/8]; // quants - high bit
uint8_t qs[QK_K/4]; // quants - low 2 bits
#ifdef GGML_QKK_64
uint8_t scales[2]; // scales, quantized with 8 bits
#else
uint8_t scales[K_SCALE_SIZE]; // scales, quantized with 6 bits
#endif
half d; // super-block scale
} block_q3_K;
static_assert(sizeof(block_q3_K) == sizeof(ggml_fp16_t) + QK_K / 4 + 11 * QK_K / 64, "wrong q3_K block size/padding");
//static_assert(sizeof(block_q3_K) == sizeof(ggml_fp16_t) + QK_K / 4 + QK_K / 8 + K_SCALE_SIZE, "wrong q3_K block size/padding");
#ifdef GGML_QKK_64
typedef struct {
half d[2]; // super-block scales/mins
uint8_t scales[2]; // 4-bit block scales/mins
uint8_t qs[QK_K/2]; // 4--bit quants
} block_q4_K;
static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + QK_K/2 + 2, "wrong q4_K block size/padding");
#else
typedef struct {
half d; // super-block scale for quantized scales
half dmin; // super-block scale for quantized mins
@ -142,15 +160,26 @@ typedef struct {
uint8_t qs[QK_K/2]; // 4--bit quants
} block_q4_K;
static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + 3*QK_K/64 + QK_K/2, "wrong q4_K block size/padding");
#endif
#ifdef GGML_QKK_64
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, quantized with 6 bits
half d; // super-block scale
int8_t scales[QK_K/16]; // block scales
uint8_t qh[QK_K/8]; // quants, high bit
uint8_t qs[QK_K/2]; // quants, low 4 bits
} block_q5_K;
static_assert(sizeof(block_q5_K) == sizeof(ggml_fp16_t) + QK_K/2 + QK_K/8 + QK_K/16, "wrong q5_K block size/padding");
#else
typedef struct {
half d; // super-block scale for quantized scales
half dmin; // super-block scale for quantized mins
uint8_t scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits
uint8_t qh[QK_K/8]; // quants, high bit
uint8_t qs[QK_K/2]; // quants, low 4 bits
} block_q5_K;
static_assert(sizeof(block_q5_K) == 2*sizeof(ggml_fp16_t) + 3*QK_K/64 + QK_K/2 + QK_K/8, "wrong q5_K block size/padding");
static_assert(sizeof(block_q5_K) == 2*sizeof(ggml_fp16_t) + K_SCALE_SIZE + QK_K/2 + QK_K/8, "wrong q5_K block size/padding");
#endif
typedef struct {
uint8_t ql[QK_K/2]; // quants, lower 4 bits
@ -349,13 +378,14 @@ static __device__ __forceinline__ void dequantize_q8_0(const void * vx, const in
static __global__ void dequantize_block_q2_K(const void * vx, float * yy) {
const int i = blockIdx.x;
const block_q2_K * x = (const block_q2_K *) vx;
const int tid = threadIdx.x;
#if QK_K == 256
const int n = tid/32;
const int l = tid - 32*n;
const int is = 8*n + l/16;
const block_q2_K * x = (const block_q2_K *) vx;
const uint8_t q = x[i].qs[32*n + l];
float * y = yy + i*QK_K + 128*n;
@ -365,21 +395,32 @@ static __global__ void dequantize_block_q2_K(const void * vx, float * yy) {
y[l+32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 2) & 3) - dmin * (x[i].scales[is+2] >> 4);
y[l+64] = dall * (x[i].scales[is+4] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+4] >> 4);
y[l+96] = dall * (x[i].scales[is+6] & 0xF) * ((q >> 6) & 3) - dmin * (x[i].scales[is+6] >> 4);
#else
const int is = tid/16; // 0 or 1
const int il = tid%16; // 0...15
const uint8_t q = x[i].qs[il] >> (2*is);
float * y = yy + i*QK_K + 16*is + il;
float dall = x[i].d;
float dmin = x[i].dmin;
y[ 0] = dall * (x[i].scales[is+0] & 0xF) * ((q >> 0) & 3) - dmin * (x[i].scales[is+0] >> 4);
y[32] = dall * (x[i].scales[is+2] & 0xF) * ((q >> 4) & 3) - dmin * (x[i].scales[is+2] >> 4);
#endif
}
static __global__ void dequantize_block_q3_K(const void * vx, float * yy) {
int r = threadIdx.x/4;
int i = blockIdx.x;
int tid = r/2;
int is0 = r%2;
int l0 = 16*is0 + 4*(threadIdx.x%4);
int n = tid / 4;
int j = tid - 4*n;
const int i = blockIdx.x;
const block_q3_K * x = (const block_q3_K *) vx;
#if QK_K == 256
const int r = threadIdx.x/4;
const int tid = r/2;
const int is0 = r%2;
const int l0 = 16*is0 + 4*(threadIdx.x%4);
const int n = tid / 4;
const int j = tid - 4*n;
uint8_t m = 1 << (4*n + j);
int is = 8*n + 2*j + is0;
int shift = 2*j;
@ -396,9 +437,31 @@ static __global__ void dequantize_block_q3_K(const void * vx, float * yy) {
const uint8_t * hm = x[i].hmask;
for (int l = l0; l < l0+4; ++l) y[l] = dl * ((int8_t)((q[l] >> shift) & 3) - ((hm[l] & m) ? 0 : 4));
#else
const int tid = threadIdx.x;
const int is = tid/16; // 0 or 1
const int il = tid%16; // 0...15
const int im = il/8; // 0...1
const int in = il%8; // 0...7
float * y = yy + i*QK_K + 16*is + il;
const uint8_t q = x[i].qs[il] >> (2*is);
const uint8_t h = x[i].hmask[in] >> (2*is + im);
const float d = (float)x[i].d;
if (is == 0) {
y[ 0] = d * ((x[i].scales[0] & 0xF) - 8) * ((int8_t)((q >> 0) & 3) - ((h >> 0) & 1 ? 0 : 4));
y[32] = d * ((x[i].scales[1] & 0xF) - 8) * ((int8_t)((q >> 4) & 3) - ((h >> 4) & 1 ? 0 : 4));
} else {
y[ 0] = d * ((x[i].scales[0] >> 4) - 8) * ((int8_t)((q >> 0) & 3) - ((h >> 0) & 1 ? 0 : 4));
y[32] = d * ((x[i].scales[1] >> 4) - 8) * ((int8_t)((q >> 4) & 3) - ((h >> 4) & 1 ? 0 : 4));
}
#endif
}
#if QK_K == 256
static inline __device__ void get_scale_min_k4(int j, const uint8_t * q, uint8_t & d, uint8_t & m) {
if (j < 4) {
d = q[j] & 63; m = q[j + 4] & 63;
@ -407,19 +470,14 @@ static inline __device__ void get_scale_min_k4(int j, const uint8_t * q, uint8_t
m = (q[j+4] >> 4) | ((q[j-0] >> 6) << 4);
}
}
#endif
static __global__ void dequantize_block_q4_K(const void * vx, float * yy) {
const block_q4_K * x = (const block_q4_K *) vx;
const int i = blockIdx.x;
//// assume 64 threads - this is very slightly better than the one below
//const int tid = threadIdx.x;
//const int il = tid/16;
//const int ir = tid%16;
//const int is = 2*il;
//const int n = 2;
#if QK_K == 256
// assume 32 threads
const int tid = threadIdx.x;
const int il = tid/8;
@ -443,6 +501,15 @@ static __global__ void dequantize_block_q4_K(const void * vx, float * yy) {
y[l + 0] = d1 * (q[l] & 0xF) - m1;
y[l +32] = d2 * (q[l] >> 4) - m2;
}
#else
const int tid = threadIdx.x;
const uint8_t * q = x[i].qs;
float * y = yy + i*QK_K;
const float d = (float)x[i].d[0];
const float m = (float)x[i].d[1];
y[tid+ 0] = d * (x[i].scales[0] & 0xF) * (q[tid] & 0xF) - m * (x[i].scales[0] >> 4);
y[tid+32] = d * (x[i].scales[1] & 0xF) * (q[tid] >> 4) - m * (x[i].scales[1] >> 4);
#endif
}
static __global__ void dequantize_block_q5_K(const void * vx, float * yy) {
@ -450,6 +517,7 @@ static __global__ void dequantize_block_q5_K(const void * vx, float * yy) {
const int i = blockIdx.x;
#if QK_K == 256
// assume 64 threads - this is very slightly better than the one below
const int tid = threadIdx.x;
const int il = tid/16; // il is in 0...3
@ -476,12 +544,25 @@ static __global__ void dequantize_block_q5_K(const void * vx, float * yy) {
hm <<= 1;
y[32] = d2 * ((ql[ 0] >> 4) + (qh[ 0] & hm ? 16 : 0)) - m2;
y[33] = d2 * ((ql[ 1] >> 4) + (qh[ 1] & hm ? 16 : 0)) - m2;
#else
const int tid = threadIdx.x;
const uint8_t q = x[i].qs[tid];
const int im = tid/8; // 0...3
const int in = tid%8; // 0...7
const int is = tid/16; // 0 or 1
const uint8_t h = x[i].qh[in] >> im;
const float d = x[i].d;
float * y = yy + i*QK_K + tid;
y[ 0] = d * x[i].scales[is+0] * ((q & 0xF) - ((h >> 0) & 1 ? 0 : 16));
y[32] = d * x[i].scales[is+2] * ((q >> 4) - ((h >> 4) & 1 ? 0 : 16));
#endif
}
static __global__ void dequantize_block_q6_K(const void * vx, float * yy) {
const block_q6_K * x = (const block_q6_K *) vx;
const int i = blockIdx.x;
#if QK_K == 256
// assume 64 threads - this is very slightly better than the one below
const int tid = threadIdx.x;
@ -501,6 +582,24 @@ static __global__ void dequantize_block_q6_K(const void * vx, float * yy) {
y[32] = d * sc[2] * ((int8_t)((ql[32] & 0xF) | (((qh >> 2) & 3) << 4)) - 32);
y[64] = d * sc[4] * ((int8_t)((ql[ 0] >> 4) | (((qh >> 4) & 3) << 4)) - 32);
y[96] = d * sc[6] * ((int8_t)((ql[32] >> 4) | (((qh >> 6) & 3) << 4)) - 32);
#else
// assume 32 threads
const int tid = threadIdx.x;
const int ip = tid/16; // 0 or 1
const int il = tid - 16*ip; // 0...15
float * y = yy + i*QK_K + 16*ip + il;
const float d = x[i].d;
const uint8_t ql = x[i].ql[16*ip + il];
const uint8_t qh = x[i].qh[il] >> (2*ip);
const int8_t * sc = x[i].scales;
y[ 0] = d * sc[ip+0] * ((int8_t)((ql & 0xF) | (((qh >> 0) & 3) << 4)) - 32);
y[32] = d * sc[ip+2] * ((int8_t)((ql >> 4) | (((qh >> 4) & 3) << 4)) - 32);
#endif
}
static __global__ void dequantize_mul_mat_vec_q2_k(const void * vx, const float * yy, float * dst, const int ncols, int nrows) {
@ -515,6 +614,9 @@ static __global__ void dequantize_mul_mat_vec_q2_k(const void * vx, const float
const block_q2_K * x = (const block_q2_K *)vx + ib0;
float tmp = 0; // partial sum for thread in warp
#if QK_K == 256
const int tid = threadIdx.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...15
const int ix = threadIdx.x%K_QUANTS_PER_ITERATION; // 0 or 0,1
@ -528,8 +630,6 @@ static __global__ void dequantize_mul_mat_vec_q2_k(const void * vx, const float
const int s_offset = 8*im;
const int y_offset = 128*im + l0;
float tmp = 0; // partial sum for thread in warp
uint32_t aux[4];
const uint8_t * d = (const uint8_t *)aux;
const uint8_t * m = (const uint8_t *)(aux + 2);
@ -565,6 +665,39 @@ static __global__ void dequantize_mul_mat_vec_q2_k(const void * vx, const float
tmp += dall * sum1 - dmin * sum2;
}
#else
const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION); // 0...15 or 0...7
const int ix = threadIdx.x%(2*K_QUANTS_PER_ITERATION); // 0....1 or 0...3
const int offset = tid * K_QUANTS_PER_ITERATION;
uint32_t uaux[2];
const uint8_t * d = (const uint8_t *)uaux;
for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
const float * y = yy + i * QK_K + offset;
const uint8_t * q = x[i].qs + offset;
const uint32_t * s = (const uint32_t *)x[i].scales;
uaux[0] = s[0] & 0x0f0f0f0f;
uaux[1] = (s[0] >> 4) & 0x0f0f0f0f;
const half2 * dh = (const half2 *)&x[i].d;
const float2 dall = __half22float2(dh[0]);
float sum1 = 0, sum2 = 0;
for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) {
const uint8_t ql = q[l];
sum1 += y[l+ 0] * d[0] * ((ql >> 0) & 3)
+ y[l+16] * d[1] * ((ql >> 2) & 3)
+ y[l+32] * d[2] * ((ql >> 4) & 3)
+ y[l+48] * d[3] * ((ql >> 6) & 3);
sum2 += y[l+0] * d[4] + y[l+16] * d[5] + y[l+32] * d[6] + y[l+48] * d[7];
}
tmp += dall.x * sum1 - dall.y * sum2;
}
#endif
// sum up partial sums and write back result
__syncthreads();
@ -573,16 +706,13 @@ static __global__ void dequantize_mul_mat_vec_q2_k(const void * vx, const float
tmp += __shfl_xor_sync(0xffffffff, tmp, mask, 32);
}
if (tid == 0) {
if (threadIdx.x == 0) {
dst[row] = tmp;
}
}
static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float * yy, float * dst, const int ncols, int nrows) {
const uint16_t kmask1 = 0x0303;
const uint16_t kmask2 = 0x0f0f;
const int row = blockIdx.y*blockDim.y + threadIdx.y;
if (row > nrows) return;
@ -591,6 +721,13 @@ static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float
const block_q3_K * x = (const block_q3_K *)vx + ib0;
float tmp = 0; // partial sum for thread in warp
#if QK_K == 256
const uint16_t kmask1 = 0x0303;
const uint16_t kmask2 = 0x0f0f;
const int tid = threadIdx.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16
const int ix = threadIdx.x%K_QUANTS_PER_ITERATION; // 0 or 0,1
@ -610,8 +747,6 @@ static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float
const uint16_t s_shift = 4*im;
float tmp = 0; // partial sum for thread in warp
for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
const float * y = yy + i * QK_K + y_offset;
@ -640,6 +775,34 @@ static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float
tmp += d * sum;
}
#else
const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION); // 0...15 or 0...7
const int ix = threadIdx.x%(2*K_QUANTS_PER_ITERATION); // 0....1 or 0...3
const int offset = tid * K_QUANTS_PER_ITERATION; // 0...15 or 0...14
const int in = offset/8; // 0 or 1
const int im = offset%8; // 0...7
for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
const float * y = yy + i * QK_K + offset;
const uint8_t * q = x[i].qs + offset;
const uint8_t * s = x[i].scales;
const float dall = (float)x[i].d;
float sum = 0;
for (int l = 0; l < K_QUANTS_PER_ITERATION; ++l) {
const uint8_t hl = x[i].hmask[im+l] >> in;
const uint8_t ql = q[l];
sum += y[l+ 0] * dall * ((s[0] & 0xF) - 8) * ((int8_t)((ql >> 0) & 3) - ((hl >> 0) & 1 ? 0 : 4))
+ y[l+16] * dall * ((s[0] >> 4) - 8) * ((int8_t)((ql >> 2) & 3) - ((hl >> 2) & 1 ? 0 : 4))
+ y[l+32] * dall * ((s[1] & 0xF) - 8) * ((int8_t)((ql >> 4) & 3) - ((hl >> 4) & 1 ? 0 : 4))
+ y[l+48] * dall * ((s[1] >> 4) - 8) * ((int8_t)((ql >> 6) & 3) - ((hl >> 6) & 1 ? 0 : 4));
}
tmp += sum;
}
#endif
// sum up partial sums and write back result
__syncthreads();
@ -648,22 +811,25 @@ static __global__ void dequantize_mul_mat_vec_q3_k(const void * vx, const float
tmp += __shfl_xor_sync(0xffffffff, tmp, mask, 32);
}
if (tid == 0) {
if (threadIdx.x == 0) {
dst[row] = tmp;
}
}
static __global__ void dequantize_mul_mat_vec_q4_k(const void * vx, const float * yy, float * dst, const int ncols, int nrows) {
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
const int row = blockIdx.y*blockDim.y + threadIdx.y;
if (row > nrows) return;
const int num_blocks_per_row = ncols / QK_K;
const int ib0 = row*num_blocks_per_row;
const block_q4_K * x = (const block_q4_K *)vx + ib0;
#if QK_K == 256
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
const int tid = threadIdx.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16
const int ix = threadIdx.x%K_QUANTS_PER_ITERATION; // 0 or 0,1
@ -683,8 +849,6 @@ static __global__ void dequantize_mul_mat_vec_q4_k(const void * vx, const float
uint16_t aux[4];
const uint8_t * sc = (const uint8_t *)aux;
const block_q4_K * x = (const block_q4_K *)vx + ib0;
float tmp = 0; // partial sum for thread in warp
for (int i = ix; i < num_blocks_per_row; i += K_QUANTS_PER_ITERATION) {
@ -713,6 +877,36 @@ static __global__ void dequantize_mul_mat_vec_q4_k(const void * vx, const float
tmp += dall * (s.x * sc[0] + s.y * sc[1] + s.z * sc[4] + s.w * sc[5]) - dmin * smin;
}
#else
const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION); // 0...15
const int ix = threadIdx.x%(2*K_QUANTS_PER_ITERATION);
const int step = tid * K_QUANTS_PER_ITERATION;
uint16_t aux16[2];
const uint8_t * s = (const uint8_t *)aux16;
float tmp = 0;
for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
const uint8_t * q = x[i].qs + step;
const float * y = yy + i*QK_K + step;
const uint16_t * a = (const uint16_t *)x[i].scales;
aux16[0] = a[0] & 0x0f0f;
aux16[1] = (a[0] >> 4) & 0x0f0f;
const float d = (float)x[i].d[0];
const float m = (float)x[i].d[1];
float sum = 0.f;
for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
sum += y[j+ 0] * (d * s[0] * (q[j+ 0] & 0xF) - m * s[2])
+ y[j+16] * (d * s[0] * (q[j+16] & 0xF) - m * s[2])
+ y[j+32] * (d * s[1] * (q[j+ 0] >> 4) - m * s[3])
+ y[j+48] * (d * s[1] * (q[j+16] >> 4) - m * s[3]);
}
tmp += sum;
}
#endif
// sum up partial sums and write back result
__syncthreads();
@ -728,15 +922,19 @@ static __global__ void dequantize_mul_mat_vec_q4_k(const void * vx, const float
static __global__ void dequantize_mul_mat_vec_q5_k(const void * vx, const float * yy, float * dst, const int ncols) {
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
//const int row = blockIdx.x*blockDim.y + threadIdx.y;
const int row = blockIdx.x;
const int num_blocks_per_row = ncols / QK_K;
const int ib0 = row*num_blocks_per_row;
const block_q5_K * x = (const block_q5_K *)vx + ib0;
float tmp = 0; // partial sum for thread in warp
#if QK_K == 256
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
const int tid = threadIdx.x/2; // 0...15
const int ix = threadIdx.x%2;
@ -757,10 +955,6 @@ static __global__ void dequantize_mul_mat_vec_q5_k(const void * vx, const float
uint16_t aux[4];
const uint8_t * sc = (const uint8_t *)aux;
const block_q5_K * x = (const block_q5_K *)vx + ib0;
float tmp = 0; // partial sum for thread in warp
for (int i = ix; i < num_blocks_per_row; i += 2) {
const uint8_t * ql1 = x[i].qs + q_offset;
@ -793,9 +987,32 @@ static __global__ void dequantize_mul_mat_vec_q5_k(const void * vx, const float
+ (y2[l] + y2[l+16]) * sc[6] + (y2[l+32] + y2[l+48]) * sc[7];
}
tmp += dall * (sum.x * sc[0] + sum.y * sc[1] + sum.z * sc[4] + sum.w * sc[5]) - dmin * smin;
}
#else
const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION); // 0...15
const int ix = threadIdx.x%(2*K_QUANTS_PER_ITERATION);
const int step = tid * K_QUANTS_PER_ITERATION;
const int im = step/8;
const int in = step%8;
for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
const uint8_t * q = x[i].qs + step;
const int8_t * s = x[i].scales;
const float * y = yy + i*QK_K + step;
const float d = x[i].d;
float sum = 0.f;
for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
const uint8_t h = x[i].qh[in+j] >> im;
sum += y[j+ 0] * d * s[0] * ((q[j+ 0] & 0xF) - ((h >> 0) & 1 ? 0 : 16))
+ y[j+16] * d * s[1] * ((q[j+16] & 0xF) - ((h >> 2) & 1 ? 0 : 16))
+ y[j+32] * d * s[2] * ((q[j+ 0] >> 4) - ((h >> 4) & 1 ? 0 : 16))
+ y[j+48] * d * s[3] * ((q[j+16] >> 4) - ((h >> 6) & 1 ? 0 : 16));
}
tmp += sum;
}
#endif
// sum up partial sums and write back result
__syncthreads();
#pragma unroll
@ -803,7 +1020,7 @@ static __global__ void dequantize_mul_mat_vec_q5_k(const void * vx, const float
tmp += __shfl_xor_sync(0xffffffff, tmp, mask, 32);
}
if (tid == 0) {
if (threadIdx.x == 0) {
dst[row] = tmp;
}
}
@ -820,6 +1037,8 @@ static __global__ void dequantize_mul_mat_vec_q6_k(const void * vx, const float
const block_q6_K * x = (const block_q6_K *)vx + ib0;
#if QK_K == 256
const int tid = threadIdx.x/K_QUANTS_PER_ITERATION; // 0...31 or 0...16
const int ix = threadIdx.x%K_QUANTS_PER_ITERATION; // 0 or 0, 1
@ -874,6 +1093,37 @@ static __global__ void dequantize_mul_mat_vec_q6_k(const void * vx, const float
}
#else
const int tid = threadIdx.x/(2*K_QUANTS_PER_ITERATION); // 0...7
const int ix = threadIdx.x%(2*K_QUANTS_PER_ITERATION); // 0...3
const int step = tid * K_QUANTS_PER_ITERATION;
float tmp = 0; // partial sum for thread in warp
for (int i = ix; i < num_blocks_per_row; i += 2*K_QUANTS_PER_ITERATION) {
const float * y = yy + i * QK_K + step;
const uint8_t * ql = x[i].ql + step;
const uint8_t * qh = x[i].qh + step;
const int8_t * s = x[i].scales;
const float d = x[i+0].d;
float sum = 0;
for (int j = 0; j < K_QUANTS_PER_ITERATION; ++j) {
sum += y[j+ 0] * s[0] * d * ((int8_t)((ql[j+ 0] & 0xF) | ((qh[j] & 0x03) << 4)) - 32)
+ y[j+16] * s[1] * d * ((int8_t)((ql[j+16] & 0xF) | ((qh[j] & 0x0c) << 2)) - 32)
+ y[j+32] * s[2] * d * ((int8_t)((ql[j+ 0] >> 4) | ((qh[j] & 0x30) >> 0)) - 32)
+ y[j+48] * s[3] * d * ((int8_t)((ql[j+16] >> 4) | ((qh[j] & 0xc0) >> 2)) - 32);
}
tmp += sum;
}
#endif
// sum up partial sums and write back result
__syncthreads();
#pragma unroll
@ -1252,12 +1502,20 @@ static void dequantize_row_q8_0_cuda(const void * vx, float * y, const int k, cu
static void dequantize_row_q2_K_cuda(const void * vx, float * y, const int k, cudaStream_t stream) {
const int nb = k / QK_K;
#if QK_K == 256
dequantize_block_q2_K<<<nb, 64, 0, stream>>>(vx, y);
#else
dequantize_block_q2_K<<<nb, 32, 0, stream>>>(vx, y);
#endif
}
static void dequantize_row_q3_K_cuda(const void * vx, float * y, const int k, cudaStream_t stream) {
const int nb = k / QK_K;
#if QK_K == 256
dequantize_block_q3_K<<<nb, 64, 0, stream>>>(vx, y);
#else
dequantize_block_q3_K<<<nb, 32, 0, stream>>>(vx, y);
#endif
}
static void dequantize_row_q4_K_cuda(const void * vx, float * y, const int k, cudaStream_t stream) {
@ -1267,12 +1525,20 @@ static void dequantize_row_q4_K_cuda(const void * vx, float * y, const int k, cu
static void dequantize_row_q5_K_cuda(const void * vx, float * y, const int k, cudaStream_t stream) {
const int nb = k / QK_K;
#if QK_K == 256
dequantize_block_q5_K<<<nb, 64, 0, stream>>>(vx, y);
#else
dequantize_block_q5_K<<<nb, 32, 0, stream>>>(vx, y);
#endif
}
static void dequantize_row_q6_K_cuda(const void * vx, float * y, const int k, cudaStream_t stream) {
const int nb = k / QK_K;
#if QK_K == 256
dequantize_block_q6_K<<<nb, 64, 0, stream>>>(vx, y);
#else
dequantize_block_q6_K<<<nb, 32, 0, stream>>>(vx, y);
#endif
}
static void dequantize_mul_mat_vec_q4_0_cuda(const void * vx, const dfloat * y, float * dst, const int ncols, const int nrows, cudaStream_t stream) {

66
ggml-metal.m
View file

@ -51,21 +51,21 @@ struct ggml_metal_context {
GGML_METAL_DECL_KERNEL(get_rows_f16);
GGML_METAL_DECL_KERNEL(get_rows_q4_0);
GGML_METAL_DECL_KERNEL(get_rows_q4_1);
GGML_METAL_DECL_KERNEL(get_rows_q2_k);
GGML_METAL_DECL_KERNEL(get_rows_q3_k);
GGML_METAL_DECL_KERNEL(get_rows_q4_k);
GGML_METAL_DECL_KERNEL(get_rows_q5_k);
GGML_METAL_DECL_KERNEL(get_rows_q6_k);
GGML_METAL_DECL_KERNEL(get_rows_q2_K);
GGML_METAL_DECL_KERNEL(get_rows_q3_K);
GGML_METAL_DECL_KERNEL(get_rows_q4_K);
GGML_METAL_DECL_KERNEL(get_rows_q5_K);
GGML_METAL_DECL_KERNEL(get_rows_q6_K);
GGML_METAL_DECL_KERNEL(rms_norm);
GGML_METAL_DECL_KERNEL(norm);
GGML_METAL_DECL_KERNEL(mul_mat_f16_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q4_0_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q4_1_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q2_k_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q3_k_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q4_k_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q5_k_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q6_k_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q2_K_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q3_K_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q4_K_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q5_K_f32);
GGML_METAL_DECL_KERNEL(mul_mat_q6_K_f32);
GGML_METAL_DECL_KERNEL(rope);
GGML_METAL_DECL_KERNEL(alibi_f32);
GGML_METAL_DECL_KERNEL(cpy_f32_f16);
@ -132,7 +132,13 @@ struct ggml_metal_context * ggml_metal_init(void) {
exit(1);
}
#ifdef GGML_QKK_64
MTLCompileOptions* options = [MTLCompileOptions new];
options.preprocessorMacros = @{ @"QK_K" : @(64) };
ctx->library = [ctx->device newLibraryWithSource:src options:options error:&error];
#else
ctx->library = [ctx->device newLibraryWithSource:src options:nil error:&error];
#endif
if (error) {
fprintf(stderr, "%s: error: %s\n", __func__, [[error description] UTF8String]);
exit(1);
@ -159,21 +165,21 @@ struct ggml_metal_context * ggml_metal_init(void) {
GGML_METAL_ADD_KERNEL(get_rows_f16);
GGML_METAL_ADD_KERNEL(get_rows_q4_0);
GGML_METAL_ADD_KERNEL(get_rows_q4_1);
GGML_METAL_ADD_KERNEL(get_rows_q2_k);
GGML_METAL_ADD_KERNEL(get_rows_q3_k);
GGML_METAL_ADD_KERNEL(get_rows_q4_k);
GGML_METAL_ADD_KERNEL(get_rows_q5_k);
GGML_METAL_ADD_KERNEL(get_rows_q6_k);
GGML_METAL_ADD_KERNEL(get_rows_q2_K);
GGML_METAL_ADD_KERNEL(get_rows_q3_K);
GGML_METAL_ADD_KERNEL(get_rows_q4_K);
GGML_METAL_ADD_KERNEL(get_rows_q5_K);
GGML_METAL_ADD_KERNEL(get_rows_q6_K);
GGML_METAL_ADD_KERNEL(rms_norm);
GGML_METAL_ADD_KERNEL(norm);
GGML_METAL_ADD_KERNEL(mul_mat_f16_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q4_0_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q4_1_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q2_k_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q3_k_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q4_k_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q5_k_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q6_k_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q2_K_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q3_K_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q4_K_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q5_K_f32);
GGML_METAL_ADD_KERNEL(mul_mat_q6_K_f32);
GGML_METAL_ADD_KERNEL(rope);
GGML_METAL_ADD_KERNEL(alibi_f32);
GGML_METAL_ADD_KERNEL(cpy_f32_f16);
@ -662,7 +668,7 @@ void ggml_metal_graph_compute(
nth0 = 4;
nth1 = 16;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q2_k_f32];
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q2_K_f32];
} break;
case GGML_TYPE_Q3_K:
{
@ -671,7 +677,7 @@ void ggml_metal_graph_compute(
nth0 = 4;
nth1 = 16;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q3_k_f32];
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q3_K_f32];
} break;
case GGML_TYPE_Q4_K:
{
@ -680,7 +686,7 @@ void ggml_metal_graph_compute(
nth0 = 4;
nth1 = 16;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_k_f32];
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q4_K_f32];
} break;
case GGML_TYPE_Q5_K:
{
@ -689,7 +695,7 @@ void ggml_metal_graph_compute(
nth0 = 4;
nth1 = 16;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q5_k_f32];
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q5_K_f32];
} break;
case GGML_TYPE_Q6_K:
{
@ -698,7 +704,7 @@ void ggml_metal_graph_compute(
nth0 = 4;
nth1 = 16;
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q6_k_f32];
[encoder setComputePipelineState:ctx->pipeline_mul_mat_q6_K_f32];
} break;
default:
{
@ -750,11 +756,11 @@ void ggml_metal_graph_compute(
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_Q4_1: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_1]; break;
case GGML_TYPE_Q2_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q2_k]; break;
case GGML_TYPE_Q3_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q3_k]; break;
case GGML_TYPE_Q4_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_k]; break;
case GGML_TYPE_Q5_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q5_k]; break;
case GGML_TYPE_Q6_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q6_k]; break;
case GGML_TYPE_Q2_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q2_K]; break;
case GGML_TYPE_Q3_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q3_K]; break;
case GGML_TYPE_Q4_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q4_K]; break;
case GGML_TYPE_Q5_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q5_K]; break;
case GGML_TYPE_Q6_K: [encoder setComputePipelineState:ctx->pipeline_get_rows_q6_K]; break;
default: GGML_ASSERT(false && "not implemented");
}

414
ggml-metal.metal
View file

@ -428,7 +428,7 @@ kernel void kernel_mul_mat_q4_0_f32(
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (ith == 0) {
for (uint i = 16; i < nth; i += 16) sum[0] += sum[i];
for (int i = 16; i < nth; i += 16) sum[0] += sum[i];
dst[r1*ne0 + r0] = sum[0];
}
}
@ -497,7 +497,7 @@ kernel void kernel_mul_mat_q4_1_f32(
}
threadgroup_barrier(mem_flags::mem_threadgroup);
if (ith == 0) {
for (int i = 16; i < nth; i += 16) sum[0] += sum[i];
for (uint i = 16; i < nth; i += 16) sum[0] += sum[i];
dst[r1*ne0 + r0] = sum[0];
}
}
@ -775,47 +775,76 @@ kernel void kernel_cpy_f32_f32(
//============================================ k-quants ======================================================
#ifndef QK_K
#define QK_K 256
#else
static_assert(QK_K == 256 || QK_K == 64, "QK_K must be 256 or 64");
#endif
#if QK_K == 256
#define K_SCALE_SIZE 12
#else
#define K_SCALE_SIZE 4
#endif
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;
} block_q2_K;
// 84 bytes / block
typedef struct {
uint8_t hmask[QK_K/8]; // quants - high bit
uint8_t qs[QK_K/4]; // quants - low 2 bits
uint8_t scales[3*QK_K/64]; // scales, quantized with 6 bits
half d; // super-block scale
} block_q3_k;
// 110 bytes / block
#if QK_K == 64
uint8_t scales[2];
#else
uint8_t scales[K_SCALE_SIZE]; // scales, quantized with 6 bits
#endif
half d; // super-block scale
} block_q3_K;
#if QK_K == 64
typedef struct {
half d[2]; // super-block scales/mins
uint8_t scales[2];
uint8_t qs[QK_K/2]; // 4-bit quants
} block_q4_K;
#else
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 scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits
uint8_t qs[QK_K/2]; // 4--bit quants
} block_q4_k;
// 144 bytes / block
} block_q4_K;
#endif
#if QK_K == 64
typedef struct {
half d; // super-block scales/mins
int8_t scales[QK_K/16]; // 8-bit block scales
uint8_t qh[QK_K/8]; // quants, high bit
uint8_t qs[QK_K/2]; // quants, low 4 bits
} block_q5_K;
#else
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 qh[QK_K/8]; // quants, high bit
uint8_t qs[QK_K/2]; // quants, low 4 bits
} block_q5_k;
} block_q5_K;
// 176 bytes / block
#endif
typedef struct {
uint8_t ql[QK_K/2]; // quants, lower 4 bits
uint8_t qh[QK_K/4]; // quants, upper 2 bits
int8_t scales[QK_K/16]; // scales, quantized with 8 bits
half d; // super-block scale
} block_q6_k;
} block_q6_K;
// 210 bytes / block
static inline uchar4 get_scale_min_k4(int j, device const uint8_t * q) {
@ -836,7 +865,7 @@ static inline uchar4 get_scale_min_k4(int j, device const uint8_t * q) {
//========================================== dequantization =============================
static void dequantize_row_q2_k(device const block_q2_k * x, device float * y, int k) {
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;
@ -847,6 +876,7 @@ static void dequantize_row_q2_k(device const block_q2_k * x, device float * y, i
device const uint8_t * q = x[i].qs;
#if QK_K == 256
int is = 0;
float dl, ml;
for (int n = 0; n < QK_K; n += 128) {
@ -865,14 +895,29 @@ static void dequantize_row_q2_k(device const block_q2_k * x, device float * y, i
}
q += 32;
}
#else
float dl1 = d * (x[i].scales[0] & 0xF), ml1 = min * (x[i].scales[0] >> 4);
float dl2 = d * (x[i].scales[1] & 0xF), ml2 = min * (x[i].scales[1] >> 4);
float dl3 = d * (x[i].scales[2] & 0xF), ml3 = min * (x[i].scales[2] >> 4);
float dl4 = d * (x[i].scales[3] & 0xF), ml4 = min * (x[i].scales[3] >> 4);
for (int l = 0; l < 16; ++l) {
y[l+ 0] = dl1 * ((q[l] >> 0) & 3) - ml1;
y[l+16] = dl2 * ((q[l] >> 2) & 3) - ml2;
y[l+32] = dl3 * ((q[l] >> 4) & 3) - ml3;
y[l+48] = dl4 * ((q[l] >> 6) & 3) - ml4;
}
y += QK_K;
#endif
}
}
static void dequantize_row_q3_k(device const block_q3_k * x, device float * y, int k) {
static void dequantize_row_q3_K(device const block_q3_K * x, device float * y, int k) {
assert(k % QK_K == 0);
const int nb = k / QK_K;
#if QK_K == 256
const uint16_t kmask1 = 0x0303;
const uint16_t kmask2 = 0x0f0f;
@ -918,22 +963,49 @@ static void dequantize_row_q3_k(device const block_q3_k * x, device float * y, i
}
q += 32;
}
}
#else
for (int i = 0; i < nb; i++) {
const float d_all = (float)(x[i].d);
device const uint8_t * q = x[i].qs;
device const uint8_t * hm = x[i].hmask;
const float d1 = d_all * ((x[i].scales[0] & 0xF) - 8);
const float d2 = d_all * ((x[i].scales[0] >> 4) - 8);
const float d3 = d_all * ((x[i].scales[1] & 0xF) - 8);
const float d4 = d_all * ((x[i].scales[1] >> 4) - 8);
for (int l = 0; l < 8; ++l) {
uint8_t h = hm[l];
y[l+ 0] = d1 * ((int8_t)((q[l+0] >> 0) & 3) - ((h & 0x01) ? 0 : 4));
y[l+ 8] = d1 * ((int8_t)((q[l+8] >> 0) & 3) - ((h & 0x02) ? 0 : 4));
y[l+16] = d2 * ((int8_t)((q[l+0] >> 2) & 3) - ((h & 0x04) ? 0 : 4));
y[l+24] = d2 * ((int8_t)((q[l+8] >> 2) & 3) - ((h & 0x08) ? 0 : 4));
y[l+32] = d3 * ((int8_t)((q[l+0] >> 4) & 3) - ((h & 0x10) ? 0 : 4));
y[l+40] = d3 * ((int8_t)((q[l+8] >> 4) & 3) - ((h & 0x20) ? 0 : 4));
y[l+48] = d4 * ((int8_t)((q[l+0] >> 6) & 3) - ((h & 0x40) ? 0 : 4));
y[l+56] = d4 * ((int8_t)((q[l+8] >> 6) & 3) - ((h & 0x80) ? 0 : 4));
}
y += QK_K;
}
#endif
}
static void dequantize_row_q4_k(device const block_q4_k * x, device float * y, int k) {
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++) {
device const uint8_t * q = x[i].qs;
#if QK_K == 256
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;
@ -945,14 +1017,29 @@ static void dequantize_row_q4_k(device const block_q4_k * x, device float * y, i
for (int l = 0; l < 32; ++l) *y++ = d2 * (q[l] >> 4) - m2;
q += 32; is += 2;
}
#else
device const uint8_t * s = x[i].scales;
device const half2 * dh = (device const half2 *)x[i].d;
const float2 d = (float2)dh[0];
const float d1 = d[0] * (s[0] & 0xF);
const float d2 = d[0] * (s[1] & 0xF);
const float m1 = d[1] * (s[0] >> 4);
const float m2 = d[1] * (s[1] >> 4);
for (int l = 0; l < 32; ++l) {
y[l+ 0] = d1 * (q[l] & 0xF) - m1;
y[l+32] = d2 * (q[l] >> 4) - m2;
}
y += QK_K;
#endif
}
}
static void dequantize_row_q5_k(device const block_q5_k * x, device float * y, int k) {
static void dequantize_row_q5_K(device const block_q5_K * x, device float * y, int k) {
assert(k % QK_K == 0);
const int nb = k / QK_K;
#if QK_K == 256
for (int i = 0; i < nb; i++) {
const float d = (float)(x[i].d);
@ -973,10 +1060,32 @@ static void dequantize_row_q5_k(device const block_q5_k * x, device float * y, i
u1 <<= 2; u2 <<= 2;
}
}
#else
for (int i = 0; i < nb; i++) {
const float d = (float)x[i].d;
device const uint8_t * ql = x[i].qs;
device const uint8_t * qh = x[i].qh;
device const int8_t * sc = x[i].scales;
for (int l = 0; l < 8; ++l) {
y[l+ 0] = d * sc[0] * ((ql[l+ 0] & 0xF) - (qh[l] & 0x01 ? 0 : 16));
y[l+ 8] = d * sc[0] * ((ql[l+ 8] & 0xF) - (qh[l] & 0x02 ? 0 : 16));
y[l+16] = d * sc[1] * ((ql[l+16] & 0xF) - (qh[l] & 0x04 ? 0 : 16));
y[l+24] = d * sc[1] * ((ql[l+24] & 0xF) - (qh[l] & 0x08 ? 0 : 16));
y[l+32] = d * sc[2] * ((ql[l+ 0] >> 4) - (qh[l] & 0x10 ? 0 : 16));
y[l+40] = d * sc[2] * ((ql[l+ 8] >> 4) - (qh[l] & 0x20 ? 0 : 16));
y[l+48] = d * sc[3] * ((ql[l+16] >> 4) - (qh[l] & 0x40 ? 0 : 16));
y[l+56] = d * sc[3] * ((ql[l+24] >> 4) - (qh[l] & 0x80 ? 0 : 16));
}
y += QK_K;
}
#endif
}
static void dequantize_row_q6_k(device const block_q6_k * x, device float * y, int k) {
static void dequantize_row_q6_K(device const block_q6_K * x, device float * y, int k) {
assert(k % QK_K == 0);
const int nb = k / QK_K;
@ -988,6 +1097,7 @@ static void dequantize_row_q6_k(device const block_q6_k * x, device float * y, i
const float d = x[i].d;
#if QK_K == 256
for (int n = 0; n < QK_K; n += 128) {
for (int l = 0; l < 32; ++l) {
int is = l/16;
@ -1005,10 +1115,23 @@ static void dequantize_row_q6_k(device const block_q6_k * x, device float * y, i
qh += 32;
sc += 8;
}
#else
for (int l = 0; l < 16; ++l) {
const int8_t q1 = (int8_t)((ql[l+ 0] & 0xF) | (((qh[l] >> 0) & 3) << 4)) - 32;
const int8_t q2 = (int8_t)((ql[l+16] & 0xF) | (((qh[l] >> 2) & 3) << 4)) - 32;
const int8_t q3 = (int8_t)((ql[l+ 0] >> 4) | (((qh[l] >> 4) & 3) << 4)) - 32;
const int8_t q4 = (int8_t)((ql[l+16] >> 4) | (((qh[l] >> 6) & 3) << 4)) - 32;
y[l+ 0] = d * sc[0] * q1;
y[l+16] = d * sc[1] * q2;
y[l+32] = d * sc[2] * q3;
y[l+48] = d * sc[3] * q4;
}
y += 64;
#endif
}
}
kernel void kernel_get_rows_q2_k(
kernel void kernel_get_rows_q2_K(
device const void * src0,
device const int * src1,
device float * dst,
@ -1019,12 +1142,12 @@ kernel void kernel_get_rows_q2_k(
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),
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_q3_k(
kernel void kernel_get_rows_q3_K(
device const void * src0,
device const int * src1,
device float * dst,
@ -1035,12 +1158,12 @@ kernel void kernel_get_rows_q3_k(
const int i = tpig;
const int r = ((device int32_t *) src1)[i];
dequantize_row_q3_k(
(device const block_q3_k *) ((device char *) src0 + r*nb01),
dequantize_row_q3_K(
(device const block_q3_K *) ((device char *) src0 + r*nb01),
(device float *) ((device char *) dst + i*nb1), ne00);
}
kernel void kernel_get_rows_q4_k(
kernel void kernel_get_rows_q4_K(
device const void * src0,
device const int * src1,
device float * dst,
@ -1051,12 +1174,12 @@ kernel void kernel_get_rows_q4_k(
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),
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_get_rows_q5_k(
kernel void kernel_get_rows_q5_K(
device const void * src0,
device const int * src1,
device float * dst,
@ -1067,12 +1190,12 @@ kernel void kernel_get_rows_q5_k(
const int i = tpig;
const int r = ((device int32_t *) src1)[i];
dequantize_row_q5_k(
(device const block_q5_k *) ((device char *) src0 + r*nb01),
dequantize_row_q5_K(
(device const block_q5_K *) ((device char *) src0 + r*nb01),
(device float *) ((device char *) dst + i*nb1), ne00);
}
kernel void kernel_get_rows_q6_k(
kernel void kernel_get_rows_q6_K(
device const void * src0,
device const int * src1,
device float * dst,
@ -1083,14 +1206,14 @@ kernel void kernel_get_rows_q6_k(
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),
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(
kernel void kernel_mul_mat_q2_K_f32(
device const void * src0,
device const float * src1,
device float * dst,
@ -1107,12 +1230,15 @@ kernel void kernel_mul_mat_q2_k_f32(
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 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;
float sumf = 0;
#if QK_K == 256
const int tid = tpitg.y; // 0...16
const int il = tid/4; // 0...3
const int ir = tid%4; // 0...3
@ -1125,9 +1251,6 @@ kernel void kernel_mul_mat_q2_k_f32(
const int y_offset = 64*il + n*ir;
const int q_offset = 32*ip + n*ir;
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 + q_offset;
@ -1140,7 +1263,6 @@ kernel void kernel_mul_mat_q2_k_f32(
device const float * y = yy + i*QK_K + y_offset;
//float4 s = {0.f, 0.f, 0.f, 0.f};
float2 s = {0.f, 0.f};
float smin = 0;
for (int l = 0; l < n; ++l) {
@ -1155,25 +1277,38 @@ kernel void kernel_mul_mat_q2_k_f32(
sumf += dall * (s[0] * d1 + s[1] * d2) - dmin * smin;
}
#else
const int il = 4 * tpitg.x;
uint32_t aux[2];
thread const uint8_t * d = (thread const uint8_t *)aux;
thread const uint8_t * m = (thread const uint8_t *)aux + 4;
for (int i = tpitg.y; i < nb; i += tptg.y) {
device const uint8_t * q = x[i].qs + il;
device const float * y = yy + i*QK_K + il;
const float dall = (float)x[i].d;
const float dmin = (float)x[i].dmin;
device const uint32_t * a = (device const uint32_t *)x[i].scales;
aux[0] = a[0] & 0x0f0f0f0f;
aux[1] = (a[0] >> 4) & 0x0f0f0f0f;
for (int l = 0; l < 4; ++l) {
sumf += y[l+ 0] * (dall * d[0] * ((q[l] >> 0) & 3) - dmin * m[0])
+ y[l+16] * (dall * d[1] * ((q[l] >> 2) & 3) - dmin * m[1])
+ y[l+32] * (dall * d[2] * ((q[l] >> 4) & 3) - dmin * m[2])
+ y[l+48] * (dall * d[3] * ((q[l] >> 6) & 3) - dmin * m[3]);
}
}
#endif
sum[ith] = sumf;
//int mask1 = (ith%4 == 0);
//int mask2 = (ith%16 == 0);
//threadgroup_barrier(mem_flags::mem_threadgroup);
//for (int i = 1; i < 4; ++i) sum[ith] += mask1 * sum[ith + i];
//threadgroup_barrier(mem_flags::mem_threadgroup);
//for (int i = 4; i < 16; i += 4) sum[ith] += mask2 * 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
// 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) {
@ -1190,7 +1325,7 @@ kernel void kernel_mul_mat_q2_k_f32(
}
}
kernel void kernel_mul_mat_q3_k_f32(
kernel void kernel_mul_mat_q3_K_f32(
device const void * src0,
device const float * src1,
device float * dst,
@ -1203,23 +1338,25 @@ kernel void kernel_mul_mat_q3_k_f32(
uint2 tpitg[[thread_position_in_threadgroup]],
uint2 tptg[[threads_per_threadgroup]]) {
const uint16_t kmask1 = 0x0303;
const uint16_t kmask2 = 0x0f0f;
const uint8_t m3 = 3;
const int8_t m4 = 4;
const int nb = ne00/QK_K;
const int64_t r0 = tgpig.x;
const int64_t r1 = tgpig.y;
device const block_q3_k * x = (device const block_q3_k *) src0 + r0*nb;
device const block_q3_K * x = (device const block_q3_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;
#if QK_K == 256
const uint8_t m3 = 3;
const int8_t m4 = 4;
const uint16_t kmask1 = 0x0303;
const uint16_t kmask2 = 0x0f0f;
const int tid = tpitg.y; // expecting 16
const int ip = tid/8; // 0 or 1
const int il = tid/2 - 4*ip; // 0...3
@ -1273,6 +1410,39 @@ kernel void kernel_mul_mat_q3_k_f32(
//sum[ith] = sumf;
sum[ith] = sumf1 - 32.f*sumf2;
#else
const int il = 4 * tpitg.x; // 0, 4, 8, 12
const int im = il/8; // 0, 0, 1, 1
const int in = il%8; // 0, 4, 0, 4
float sumf = 0;
for (int i = tpitg.y; i < nb; i += tptg.y) {
const float d_all = (float)(x[i].d);
device const uint8_t * q = x[i].qs + il;
device const uint8_t * h = x[i].hmask + in;
device const float * y = yy + i * QK_K + il;
const float d1 = d_all * ((x[i].scales[0] & 0xF) - 8);
const float d2 = d_all * ((x[i].scales[0] >> 4) - 8);
const float d3 = d_all * ((x[i].scales[1] & 0xF) - 8);
const float d4 = d_all * ((x[i].scales[1] >> 4) - 8);
for (int l = 0; l < 4; ++l) {
const uint8_t hm = h[l] >> im;
sumf += y[l+ 0] * d1 * ((int8_t)((q[l+0] >> 0) & 3) - ((hm & 0x01) ? 0 : 4))
+ y[l+16] * d2 * ((int8_t)((q[l+0] >> 2) & 3) - ((hm & 0x04) ? 0 : 4))
+ y[l+32] * d3 * ((int8_t)((q[l+0] >> 4) & 3) - ((hm & 0x10) ? 0 : 4))
+ y[l+48] * d4 * ((int8_t)((q[l+0] >> 6) & 3) - ((hm & 0x40) ? 0 : 4));
}
}
sum[ith] = sumf;
#endif
//
// Accumulate the sum from all threads in the threadgroup
@ -1293,7 +1463,7 @@ kernel void kernel_mul_mat_q3_k_f32(
}
kernel void kernel_mul_mat_q4_k_f32(
kernel void kernel_mul_mat_q4_K_f32(
device const void * src0,
device const float * src1,
device float * dst,
@ -1305,21 +1475,25 @@ kernel void kernel_mul_mat_q4_k_f32(
uint2 tpitg[[thread_position_in_threadgroup]],
uint2 tptg[[threads_per_threadgroup]]) {
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
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 int nth = tptg.x*tptg.y;
const int ith = tptg.y*tpitg.x + tpitg.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;
float sumf = 0;
#if QK_K == 256
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
const int tid = tpitg.y; // 0...16
const int il = tid/4; // 0...3
const int ir = tid - 4*il;// 0...3
@ -1332,11 +1506,8 @@ kernel void kernel_mul_mat_q4_k_f32(
const int q_offset = 32*im + l0;
const int y_offset = 64*im + l0;
sum[ith] = 0.0f;
uchar2 sc1, sc2, sc3, sc4;
float sumf = 0;
for (int i = tpitg.x; i < nb; i += tptg.x) {
device const uint8_t * q1 = (x + i)->qs + q_offset;
@ -1365,6 +1536,30 @@ kernel void kernel_mul_mat_q4_k_f32(
sumf += dall * (s[0] * sc1[0] + s[1] * sc1[1] + s[2] * sc3[0] + s[3] * sc3[1]) - dmin * smin;
}
#else
uint16_t aux16[2];
thread const uint8_t * scales = (thread const uint8_t *)aux16;
const int il = 4*tpitg.x;
for (int i = tpitg.y; i < nb; i += tptg.y) {
device const uint8_t * q = x[i].qs + il;
device const float * y = yy + i * QK_K + il;
const float d = (float)x[i].d[0];
const float m = (float)x[i].d[1];
device const uint16_t * a = (device const uint16_t *)x[i].scales;
aux16[0] = a[0] & 0x0f0f;
aux16[1] = (a[0] >> 4) & 0x0f0f;
for (int l = 0; l < 4; ++l) {
sumf += d * scales[0] * (y[l+ 0] * (q[l] & 0xF) + y[l+16] * (q[l+16] & 0xF)) - m * scales[2] * (y[l+ 0] + y[l+16])
+ d * scales[1] * (y[l+32] * (q[l] >> 4) + y[l+48] * (q[l+16] >> 4)) - m * scales[3] * (y[l+32] + y[l+48]);
}
}
#endif
sum[ith] = sumf;
@ -1401,7 +1596,7 @@ kernel void kernel_mul_mat_q4_k_f32(
//}
}
kernel void kernel_mul_mat_q5_k_f32(
kernel void kernel_mul_mat_q5_K_f32(
device const void * src0,
device const float * src1,
device float * dst,
@ -1413,21 +1608,25 @@ kernel void kernel_mul_mat_q5_k_f32(
uint2 tpitg[[thread_position_in_threadgroup]],
uint2 tptg[[threads_per_threadgroup]]) {
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
const int nb = ne00/QK_K;
const int64_t r0 = tgpig.x;
const int64_t r1 = tgpig.y;
device const block_q5_k * x = (device const block_q5_k *) src0 + r0*nb;
device const block_q5_K * x = (device const block_q5_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;
float sumf = 0;
#if QK_K == 256
const uint16_t kmask1 = 0x3f3f;
const uint16_t kmask2 = 0x0f0f;
const uint16_t kmask3 = 0xc0c0;
const int tid = tpitg.y; // 0...16
const int il = tid/4; // 0...3
const int ir = tid - 4*il;// 0...3
@ -1447,7 +1646,6 @@ kernel void kernel_mul_mat_q5_k_f32(
uchar2 sc1, sc2, sc3, sc4;
float sumf = 0;
for (int i = tpitg.x; i < nb; i += tptg.x) {
device const uint8_t * q1 = (x + i)->qs + q_offset;
@ -1479,6 +1677,28 @@ kernel void kernel_mul_mat_q5_k_f32(
sumf += dall * (s[0] * sc1[0] + s[1] * sc1[1] + s[2] * sc3[0] + s[3] * sc3[1]) - dmin * smin;
}
#else
const int il = 4 * tpitg.x; // 0, 4, 8, 12
const int im = il/8; // 0, 0, 1, 1
const int in = il%8; // 0, 4, 0, 4
for (int i = tpitg.y; i < nb; i += tptg.y) {
const float d = (float)x[i].d;
device const uint8_t * q = x[i].qs + il;
device const uint8_t * h = x[i].qh + in;
device const int8_t * s = x[i].scales;
device const float * y = yy + i*QK_K + il;
for (int l = 0; l < 4; ++l) {
const uint8_t hl = h[l] >> im;
sumf += y[l+ 0] * d * s[0] * ((q[l+ 0] & 0xF) - (hl & 0x01 ? 0 : 16))
+ y[l+16] * d * s[1] * ((q[l+16] & 0xF) - (hl & 0x04 ? 0 : 16))
+ y[l+32] * d * s[2] * ((q[l+ 0] >> 4) - (hl & 0x10 ? 0 : 16))
+ y[l+48] * d * s[3] * ((q[l+16] >> 4) - (hl & 0x40 ? 0 : 16));
}
}
#endif
sum[ith] = sumf;
//
@ -1500,7 +1720,7 @@ kernel void kernel_mul_mat_q5_k_f32(
}
kernel void kernel_mul_mat_q6_k_f32(
kernel void kernel_mul_mat_q6_K_f32(
device const void * src0,
device const float * src1,
device float * dst,
@ -1522,12 +1742,15 @@ kernel void kernel_mul_mat_q6_k_f32(
const int64_t r0 = tgpig.x;
const int64_t r1 = tgpig.y;
device const block_q6_k * x = (device const block_q6_k *) src0 + r0*nb;
device const block_q6_K * x = (device const block_q6_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;
float sumf = 0;
#if QK_K == 256
// Note: we absolutely assume that tptg.y = 16 and QK_K = 256!
const int iqs = 16 * tpitg.y;
const int ip = iqs / 128; // 0 or 1
@ -1540,7 +1763,6 @@ kernel void kernel_mul_mat_q6_k_f32(
const int q_offset_l = 64*ip + l0;
const int q_offset_h = 32*ip + l0;
float sumf = 0;
for (int i = tpitg.x; i < nb; i += tptg.x) {
device const uint8_t * ql = x[i].ql + q_offset_l;
@ -1562,6 +1784,28 @@ kernel void kernel_mul_mat_q6_k_f32(
sumf += dall * (sums[0] * sc[0] + sums[1] * sc[2] + sums[2] * sc[4] + sums[3] * sc[6]);
}
#else
const int il = 4*tpitg.x; // 0, 4, 8, 12
for (int i = tpitg.y; i < nb; i += tptg.y) {
device const float * y = yy + i * QK_K + il;
device const uint8_t * ql = x[i].ql + il;
device const uint8_t * qh = x[i].qh + il;
device const int8_t * s = x[i].scales;
const float d = x[i].d;
float4 sums = {0.f, 0.f, 0.f, 0.f};
for (int l = 0; l < 4; ++l) {
sums[0] += y[l+ 0] * ((int8_t)((ql[l+ 0] & 0xF) | ((qh[l] & kmask1) << 4)) - 32);
sums[1] += y[l+16] * ((int8_t)((ql[l+16] & 0xF) | ((qh[l] & kmask2) << 2)) - 32);
sums[2] += y[l+32] * ((int8_t)((ql[l+ 0] >> 4) | ((qh[l] & kmask3) >> 0)) - 32);
sums[3] += y[l+48] * ((int8_t)((ql[l+16] >> 4) | ((qh[l] & kmask4) >> 2)) - 32);
}
sumf += d * (sums[0] * s[0] + sums[1] * s[1] + sums[2] * s[2] + sums[3] * s[3]);
}
#endif
sum[ith] = sumf;

1140
k_quants.c
View file

File diff suppressed because it is too large Load diff

51
k_quants.h
View file

@ -7,7 +7,13 @@
#include <stddef.h>
// Super-block size
#ifdef GGML_QKK_64
#define QK_K 64
#define K_SCALE_SIZE 4
#else
#define QK_K 256
#define K_SCALE_SIZE 12
#endif
//
// Super-block quantization structures
@ -29,38 +35,67 @@ static_assert(sizeof(block_q2_K) == 2*sizeof(ggml_fp16_t) + QK_K/16 + QK_K/4, "w
// weight is represented as x = a * q
// 16 blocks of 16 elemenets each
// Effectively 3.4375 bits per weight
#ifdef GGML_QKK_64
typedef struct {
uint8_t hmask[QK_K/8]; // quants - high bit
uint8_t qs[QK_K/4]; // quants - low 2 bits
uint8_t scales[3*QK_K/64]; // scales, quantized with 6 bits
uint8_t scales[2];
ggml_fp16_t d; // super-block scale
} block_q3_K;
static_assert(sizeof(block_q3_K) == sizeof(ggml_fp16_t) + QK_K / 4 + 11 * QK_K / 64, "wrong q3_K block size/padding");
static_assert(sizeof(block_q3_K) == sizeof(ggml_fp16_t) + QK_K / 4 + QK_K / 8 + 2, "wrong q3_K block size/padding");
#else
typedef struct {
uint8_t hmask[QK_K/8]; // quants - high bit
uint8_t qs[QK_K/4]; // quants - low 2 bits
uint8_t scales[12]; // scales, quantized with 6 bits
ggml_fp16_t d; // super-block scale
} block_q3_K;
static_assert(sizeof(block_q3_K) == sizeof(ggml_fp16_t) + QK_K / 4 + QK_K / 8 + 12, "wrong q3_K block size/padding");
#endif
// 4-bit quantization
// 16 blocks of 32 elements each
// weight is represented as x = a * q + b
// Effectively 4.5 bits per weight
#ifdef GGML_QKK_64
typedef struct {
ggml_fp16_t d[2]; // super-block scales/mins
uint8_t scales[2]; // 4-bit block scales/mins
uint8_t qs[QK_K/2]; // 4--bit quants
} block_q4_K;
static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + QK_K/2 + 2, "wrong q4_K block size/padding");
#else
typedef struct {
ggml_fp16_t d; // super-block scale for quantized scales
ggml_fp16_t dmin; // super-block scale for quantized mins
uint8_t scales[3*QK_K/64]; // scales and mins, quantized with 6 bits
uint8_t scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits
uint8_t qs[QK_K/2]; // 4--bit quants
} block_q4_K;
static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + 3*QK_K/64 + QK_K/2, "wrong q4_K block size/padding");
static_assert(sizeof(block_q4_K) == 2*sizeof(ggml_fp16_t) + K_SCALE_SIZE + QK_K/2, "wrong q4_K block size/padding");
#endif
// 5-bit quantization
// 16 blocks of 32 elements each
// weight is represented as x = a * q + b
// Effectively 5.5 bits per weight
#ifdef GGML_QKK_64
typedef struct {
ggml_fp16_t d; // super-block scale for quantized scales
ggml_fp16_t dmin; // super-block scale for quantized mins
uint8_t scales[3*QK_K/64]; // scales and mins, quantized with 6 bits
ggml_fp16_t d; // super-block scale
int8_t scales[QK_K/16]; // 8-bit block scales
uint8_t qh[QK_K/8]; // quants, high bit
uint8_t qs[QK_K/2]; // quants, low 4 bits
} block_q5_K;
static_assert(sizeof(block_q5_K) == 2*sizeof(ggml_fp16_t) + 3*QK_K/64 + QK_K/2 + QK_K/8, "wrong q5_K block size/padding");
static_assert(sizeof(block_q5_K) == sizeof(ggml_fp16_t) + QK_K/2 + QK_K/8 + QK_K/16, "wrong q5_K block size/padding");
#else
typedef struct {
ggml_fp16_t d; // super-block scale for quantized scales
ggml_fp16_t dmin; // super-block scale for quantized mins
uint8_t scales[K_SCALE_SIZE]; // scales and mins, quantized with 6 bits
uint8_t qh[QK_K/8]; // quants, high bit
uint8_t qs[QK_K/2]; // quants, low 4 bits
} block_q5_K;
static_assert(sizeof(block_q5_K) == 2*sizeof(ggml_fp16_t) + K_SCALE_SIZE + QK_K/2 + QK_K/8, "wrong q5_K block size/padding");
#endif
// 6-bit quantization
// weight is represented as x = a * q

17
llama.cpp
View file

@ -21,9 +21,13 @@
#endif
#ifdef GGML_USE_K_QUANTS
#ifndef QK_K
#ifdef GGML_QKK_64
#define QK_K 64
#else
#define QK_K 256
#endif
#endif
#endif
#include <array>
#include <ctime>
@ -2470,6 +2474,10 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
std::vector<std::thread> workers;
std::mutex mutex;
auto use_more_bits = [] (int i_layer, int num_layers) -> bool {
return i_layer < num_layers/8 || i_layer >= 7*num_layers/8 || (i_layer - num_layers/8)%3 == 2;
};
size_t idx = 0;
for (llama_load_tensor & tensor : model_loader->tensors_map.tensors) {
llama_buffer read_data;
@ -2524,15 +2532,16 @@ static void llama_model_quantize_internal(const std::string & fname_inp, const s
if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q4_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) new_type = GGML_TYPE_Q5_K;
else if ((ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) &&
(i_attention_wv < n_attention_wv/8 || i_attention_wv >= 7*n_attention_wv/8 ||
(i_attention_wv - n_attention_wv/8)%3 == 2)) new_type = GGML_TYPE_Q6_K;
use_more_bits(i_attention_wv, n_attention_wv)) new_type = GGML_TYPE_Q6_K;
else if (QK_K == 64 && (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_S || ftype == LLAMA_FTYPE_MOSTLY_Q3_K_S) &&
(i_attention_wv < n_attention_wv/8 || i_attention_wv >= 7*n_attention_wv/8)) new_type = GGML_TYPE_Q6_K;
++i_attention_wv;
} else if (tensor.name.find("feed_forward.w2.weight") != std::string::npos) {
if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q4_K;
else if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_L) new_type = GGML_TYPE_Q5_K;
else if ((ftype == LLAMA_FTYPE_MOSTLY_Q4_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q5_K_M) &&
(i_feed_forward_w2 < n_feed_forward_w2/8 || i_feed_forward_w2 >= 7*n_feed_forward_w2/8 ||
(i_feed_forward_w2 - n_feed_forward_w2/8)%3 == 2)) new_type = GGML_TYPE_Q6_K;
use_more_bits(i_feed_forward_w2, n_feed_forward_w2)) new_type = GGML_TYPE_Q6_K;
//else if (ftype == LLAMA_FTYPE_MOSTLY_Q4_K_S && i_feed_forward_w2 < n_feed_forward_w2/8) new_type = GGML_TYPE_Q6_K;
++i_feed_forward_w2;
} else if (tensor.name.find("attention.wo.weight") != std::string::npos) {
if (ftype == LLAMA_FTYPE_MOSTLY_Q3_K_M || ftype == LLAMA_FTYPE_MOSTLY_Q2_K) new_type = GGML_TYPE_Q4_K;