llama.cpp/ggml-cuda.cu
slaren 7fc50c051a
cuBLAS: use host pinned memory and dequantize while copying (#1207)
* cuBLAS: dequantize simultaneously while copying memory

* cuBLAS: use host pinned memory

* cuBLAS: improve ggml_compute_forward_mul_mat_f16_f32 with pinned memory

* cuBLAS: also pin kv cache

* fix rebase
2023-04-29 02:04:18 +02:00

365 lines
10 KiB
Text

#include <stdint.h>
#include <stdio.h>
#include <cuda_fp16.h>
#include <atomic>
#include "ggml-cuda.h"
typedef uint16_t ggml_fp16_t;
static_assert(sizeof(__half) == sizeof(ggml_fp16_t), "wrong fp16 size");
#define QK4_0 32
typedef struct {
float d; // delta
uint8_t qs[QK4_0 / 2]; // nibbles / quants
} block_q4_0;
static_assert(sizeof(block_q4_0) == sizeof(float) + QK4_0 / 2, "wrong q4_0 block size/padding");
#define QK4_1 32
typedef struct {
float d; // delta
float m; // min
uint8_t qs[QK4_1 / 2]; // nibbles / quants
} block_q4_1;
static_assert(sizeof(block_q4_1) == sizeof(float) * 2 + QK4_1 / 2, "wrong q4_1 block size/padding");
#define QK4_2 16
typedef struct {
__half d; // delta
uint8_t qs[QK4_2 / 2]; // nibbles / quants
} block_q4_2;
static_assert(sizeof(block_q4_2) == sizeof(ggml_fp16_t) + QK4_2 / 2, "wrong q4_2 block size/padding");
#define QK5_0 32
typedef struct {
__half d; // delta
uint8_t qh[4]; // 5-th bit of quants
uint8_t qs[QK5_0 / 2]; // nibbles / quants
} block_q5_0;
static_assert(sizeof(block_q5_0) == sizeof(ggml_fp16_t) + sizeof(uint32_t) + QK5_0 / 2, "wrong q5_0 block size/padding");
#define QK5_1 32
typedef struct {
__half d; // delta
__half m; // min
uint32_t qh; // 5-th bit of quants
uint8_t qs[QK5_1 / 2]; // nibbles / quants
} block_q5_1;
static_assert(sizeof(block_q5_1) == 2 * sizeof(ggml_fp16_t) + sizeof(uint32_t) + QK5_1 / 2, "wrong q5_1 block size/padding");
#define QK8_0 32
typedef struct {
float d; // delta
int8_t qs[QK8_0]; // quants
} block_q8_0;
static_assert(sizeof(block_q8_0) == sizeof(float) + QK8_0, "wrong q8_0 block size/padding");
static __global__ void dequantize_block_q4_0(const void * vx, float * y) {
const block_q4_0 * x = (const block_q4_0 *) vx;
const int i = blockIdx.x;
const float d = x[i].d;
const uint8_t * pp = x[i].qs;
for (int l = 0; l < QK4_0; l += 2) {
const uint8_t vi = pp[l/2];
const int8_t vi0 = vi & 0xf;
const int8_t vi1 = vi >> 4;
const float v0 = (vi0 - 8)*d;
const float v1 = (vi1 - 8)*d;
y[i*QK4_0 + l + 0] = v0;
y[i*QK4_0 + l + 1] = v1;
}
}
static __global__ void dequantize_block_q4_1(const void * vx, float * y) {
const block_q4_1 * x = (const block_q4_1 *) vx;
const int i = blockIdx.x;
const float d = x[i].d;
const float m = x[i].m;
const uint8_t * pp = x[i].qs;
for (int l = 0; l < QK4_1; l += 2) {
const uint8_t vi = pp[l/2];
const int8_t vi0 = vi & 0xf;
const int8_t vi1 = vi >> 4;
const float v0 = vi0*d + m;
const float v1 = vi1*d + m;
y[i*QK4_1 + l + 0] = v0;
y[i*QK4_1 + l + 1] = v1;
}
}
static __global__ void dequantize_block_q4_2(const void * vx, float * y) {
const block_q4_2 * x = (const block_q4_2 *) vx;
const int i = blockIdx.x;
const float d = x[i].d;
const uint8_t * pp = x[i].qs;
for (int l = 0; l < QK4_2; l += 2) {
const uint8_t vi = pp[l/2];
const int8_t vi0 = vi & 0xf;
const int8_t vi1 = vi >> 4;
const float v0 = (vi0 - 8)*d;
const float v1 = (vi1 - 8)*d;
y[i*QK4_2 + l + 0] = v0;
y[i*QK4_2 + l + 1] = v1;
}
}
static __global__ void dequantize_block_q5_0(const void * vx, float * y) {
const block_q5_0 * x = (const block_q5_0 *) vx;
const int i = blockIdx.x;
const float d = x[i].d;
const uint8_t * pp = x[i].qs;
uint32_t qh;
memcpy(&qh, x[i].qh, sizeof(qh));
for (int l = 0; l < QK5_0; l += 2) {
const uint8_t vi = pp[l/2];
const int8_t vh0 = ((qh & (1 << (l + 0))) >> (l + 0)) << 4;
const int8_t vh1 = ((qh & (1 << (l + 1))) >> (l + 1)) << 4;
const int8_t vi0 = ((vi & 0xf) | vh0);
const int8_t vi1 = ((vi >> 4) | vh1);
const float v0 = (vi0 - 16)*d;
const float v1 = (vi1 - 16)*d;
y[i*QK5_0 + l + 0] = v0;
y[i*QK5_0 + l + 1] = v1;
}
}
static __global__ void dequantize_block_q5_1(const void * vx, float * y) {
const block_q5_1 * x = (const block_q5_1 *) vx;
const int i = blockIdx.x;
const float d = x[i].d;
const float m = x[i].m;
const uint8_t * pp = x[i].qs;
const uint32_t qh = x[i].qh;
for (int l = 0; l < QK5_1; l += 2) {
const uint8_t vi = pp[l/2];
const int8_t vh0 = ((qh & (1 << (l + 0))) >> (l + 0)) << 4;
const int8_t vh1 = ((qh & (1 << (l + 1))) >> (l + 1)) << 4;
const int8_t vi0 = (vi & 0xf) | vh0;
const int8_t vi1 = (vi >> 4) | vh1;
const float v0 = vi0*d + m;
const float v1 = vi1*d + m;
y[i*QK5_1 + l + 0] = v0;
y[i*QK5_1 + l + 1] = v1;
}
}
static __global__ void dequantize_block_q8_0(const void * vx, float * y) {
const block_q8_0 * x = (const block_q8_0 *) vx;
const int i = blockIdx.x;
const float d = x[i].d;
const int8_t * pp = x[i].qs;
for (int l = 0; l < QK8_0; l++) {
const int8_t vi = pp[l];
y[i*QK8_0 + l] = vi*d;
}
}
void dequantize_row_q4_0_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
const int nb = k / QK4_0;
dequantize_block_q4_0<<<nb, 1, 0, stream>>>(vx, y);
}
void dequantize_row_q4_1_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
const int nb = k / QK4_1;
dequantize_block_q4_1<<<nb, 1, 0, stream>>>(vx, y);
}
void dequantize_row_q4_2_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
const int nb = k / QK4_2;
dequantize_block_q4_2<<<nb, 1, 0, stream>>>(vx, y);
}
void dequantize_row_q5_0_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
const int nb = k / QK5_0;
dequantize_block_q5_0<<<nb, 1, 0, stream>>>(vx, y);
}
void dequantize_row_q5_1_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
const int nb = k / QK5_1;
dequantize_block_q5_1<<<nb, 1, 0, stream>>>(vx, y);
}
void dequantize_row_q8_0_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
const int nb = k / QK8_0;
dequantize_block_q8_0<<<nb, 1, 0, stream>>>(vx, y);
}
dequantize_row_q_cuda_t ggml_get_dequantize_row_q_cuda(ggml_type type) {
switch (type) {
case GGML_TYPE_Q4_0:
return dequantize_row_q4_0_cuda;
case GGML_TYPE_Q4_1:
return dequantize_row_q4_1_cuda;
case GGML_TYPE_Q4_2:
return dequantize_row_q4_2_cuda;
case GGML_TYPE_Q5_0:
return dequantize_row_q5_0_cuda;
case GGML_TYPE_Q5_1:
return dequantize_row_q5_1_cuda;
case GGML_TYPE_Q8_0:
return dequantize_row_q8_0_cuda;
default:
return nullptr;
}
}
// buffer pool for cuda
#define MAX_CUDA_BUFFERS 16
struct scoped_spin_lock {
std::atomic_flag& lock;
scoped_spin_lock(std::atomic_flag& lock) : lock(lock) {
while (lock.test_and_set(std::memory_order_acquire)) {
; // spin
}
}
~scoped_spin_lock() {
lock.clear(std::memory_order_release);
}
scoped_spin_lock(const scoped_spin_lock&) = delete;
scoped_spin_lock& operator=(const scoped_spin_lock&) = delete;
};
struct cuda_buffer {
void * ptr = nullptr;
size_t size = 0;
};
static cuda_buffer g_cuda_buffer_pool[MAX_CUDA_BUFFERS];
static std::atomic_flag g_cuda_pool_lock = ATOMIC_FLAG_INIT;
void * ggml_cuda_pool_malloc(size_t size, size_t * actual_size) {
scoped_spin_lock lock(g_cuda_pool_lock);
for (int i = 0; i < MAX_CUDA_BUFFERS; ++i) {
cuda_buffer& b = g_cuda_buffer_pool[i];
if (b.size >= size && b.ptr != nullptr) {
void * ptr = b.ptr;
*actual_size = b.size;
b.ptr = nullptr;
b.size = 0;
return ptr;
}
}
void * ptr;
CUDA_CHECK(cudaMalloc((void **) &ptr, size));
*actual_size = size;
return ptr;
}
void ggml_cuda_pool_free(void * ptr, size_t size) {
scoped_spin_lock lock(g_cuda_pool_lock);
for (int i = 0; i < MAX_CUDA_BUFFERS; ++i) {
cuda_buffer& b = g_cuda_buffer_pool[i];
if (b.ptr == nullptr) {
b.ptr = ptr;
b.size = size;
return;
}
}
fprintf(stderr, "WARNING: cuda buffer pool full, increase MAX_CUDA_BUFFERS\n");
CUDA_CHECK(cudaFree(ptr));
}
cublasHandle_t g_cublasH = nullptr;
cudaStream_t g_cudaStream = nullptr;
cudaStream_t g_cudaStream2 = nullptr;
cudaEvent_t g_cudaEvent = nullptr;
void ggml_init_cublas() {
if (g_cublasH == nullptr) {
// create cublas handle, bind a stream
CUBLAS_CHECK(cublasCreate(&g_cublasH));
CUDA_CHECK(cudaStreamCreateWithFlags(&g_cudaStream, cudaStreamNonBlocking));
CUBLAS_CHECK(cublasSetStream(g_cublasH, g_cudaStream));
// create additional stream and event for synchronization
CUDA_CHECK(cudaStreamCreateWithFlags(&g_cudaStream2, cudaStreamNonBlocking));
CUDA_CHECK(cudaEventCreateWithFlags(&g_cudaEvent, cudaEventDisableTiming));
// configure logging to stdout
// CUBLAS_CHECK(cublasLoggerConfigure(1, 1, 0, NULL));
}
}
cudaError_t ggml_cuda_h2d_tensor_2d(void * dst, const struct ggml_tensor * src, uint64_t i3, uint64_t i2, cudaStream_t stream) {
const uint64_t ne0 = src->ne[0];
const uint64_t ne1 = src->ne[1];
const uint64_t nb0 = src->nb[0];
const uint64_t nb1 = src->nb[1];
const uint64_t nb2 = src->nb[2];
const uint64_t nb3 = src->nb[3];
const enum ggml_type type = src->type;
const size_t ts = ggml_type_size(type);
const size_t bs = ggml_blck_size(type);
const void * x = (const void *) ((const char *) src->data + i2*nb2 + i3*nb3);
if (nb0 == ts && nb1 == ts*ne0/bs) {
return cudaMemcpyAsync(dst, x, ne1*nb1, cudaMemcpyHostToDevice, stream);
} else if (nb0 == ts) {
return cudaMemcpy2DAsync(dst, ts*ne0/bs, x, nb1, ts*ne0/bs, ne1, cudaMemcpyHostToDevice, stream);
} else {
for (uint64_t i1 = 0; i1 < ne1; i1++) {
const void * rx = (const void *) ((const char *) x + i1*nb1);
void * rd = (void *) ((char *) dst + i1*ts*ne0/bs);
// pretend the row is a matrix with cols=1
cudaError_t r = cudaMemcpy2DAsync(rd, ts/bs, rx, nb0, ts/bs, ne0, cudaMemcpyHostToDevice, stream);
if (r != cudaSuccess) return r;
}
return cudaSuccess;
}
}
void * ggml_cuda_host_malloc(size_t size) {
void * ptr;
CUDA_CHECK(cudaMallocHost((void **) &ptr, size));
return ptr;
}
void ggml_cuda_host_free(void * ptr) {
CUDA_CHECK(cudaFreeHost(ptr));
}