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authorslaren <2141330+slaren@users.noreply.github.com>2023-04-21 21:59:17 +0200
committerGitHub <noreply@github.com>2023-04-21 21:59:17 +0200
commit50cb666b8a2e35a49b08c0f6bc81138c8f6f2ac1 (patch)
tree80370baa4d8b17d2cb44a134bed6b1a088b1cfc1
parent25d7abbd1f73582b7e0fdc422a936e8541c0780b (diff)
Improve cuBLAS performance by using a memory pool (#1094)
* Improve cuBLAS performance by using a memory pool * Move cuda specific definitions to ggml-cuda.h/cu * Add CXX flags to nvcc * Change memory pool synchronization mechanism to a spin lock General code cleanup
-rw-r--r--Makefile10
-rw-r--r--ggml-cuda.cu112
-rw-r--r--ggml-cuda.h29
-rw-r--r--ggml.c124
4 files changed, 168 insertions, 107 deletions
diff --git a/Makefile b/Makefile
index f267d08..3b48eec 100644
--- a/Makefile
+++ b/Makefile
@@ -101,11 +101,13 @@ ifdef LLAMA_OPENBLAS
LDFLAGS += -lopenblas
endif
ifdef LLAMA_CUBLAS
- CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include
- LDFLAGS += -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64
- OBJS += ggml-cuda.o
+ CFLAGS += -DGGML_USE_CUBLAS -I/usr/local/cuda/include
+ LDFLAGS += -lcublas -lculibos -lcudart -lcublasLt -lpthread -ldl -lrt -L/usr/local/cuda/lib64
+ OBJS += ggml-cuda.o
+ NVCC = nvcc
+ NVCCFLAGS = --forward-unknown-to-host-linker -arch=native
ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
- nvcc -arch=native -c -o $@ $<
+ $(NVCC) $(NVCCFLAGS) $(CXXFLAGS) -c $< -o $@
endif
ifdef LLAMA_GPROF
CFLAGS += -pg
diff --git a/ggml-cuda.cu b/ggml-cuda.cu
index 0baa989..fa511c1 100644
--- a/ggml-cuda.cu
+++ b/ggml-cuda.cu
@@ -1,5 +1,7 @@
#include <stdint.h>
+#include <stdio.h>
#include <cuda_fp16.h>
+#include <atomic>
#include "ggml-cuda.h"
typedef uint16_t ggml_fp16_t;
@@ -29,14 +31,12 @@ static_assert(sizeof(block_q4_2) == sizeof(ggml_fp16_t) + QK4_2 / 2, "wrong q4_2
#define QK4_3 16
typedef struct {
- __half d; // delta
- __half m; // min
- uint8_t qs[QK4_3 / 2]; // nibbles / quants
+ __half d; // delta
+ __half m; // min
+ uint8_t qs[QK4_3 / 2]; // nibbles / quants
} block_q4_3;
static_assert(sizeof(block_q4_3) == 2 * sizeof(ggml_fp16_t) + QK4_3 / 2, "wrong q4_3 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;
@@ -131,24 +131,98 @@ static __global__ void dequantize_block_q4_3(const void * vx, float * y) {
}
}
-extern "C" {
- __host__ 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_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_q4_3_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
+ const int nb = k / QK4_3;
+ dequantize_block_q4_3<<<nb, 1, 0, stream>>>(vx, y);
+}
- __host__ 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);
+// 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);
- __host__ 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);
+ 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 = NULL;
+cudaStream_t g_cudaStream = NULL;
+
+void ggml_init_cublas(void) {
+ if (g_cublasH == NULL) {
+ // create cublas handle, bind a stream
+ CUBLAS_CHECK(cublasCreate(&g_cublasH));
+
+ CUDA_CHECK(cudaStreamCreateWithFlags(&g_cudaStream, cudaStreamNonBlocking));
+
+ CUBLAS_CHECK(cublasSetStream(g_cublasH, g_cudaStream));
- __host__ void dequantize_row_q4_3_cuda(const void * vx, float * y, int k, cudaStream_t stream) {
- const int nb = k / QK4_3;
- dequantize_block_q4_3<<<nb, 1, 0, stream>>>(vx, y);
+ // configure logging to stdout
+ // CUBLAS_CHECK(cublasLoggerConfigure(1, 1, 0, NULL));
}
}
diff --git a/ggml-cuda.h b/ggml-cuda.h
index be14060..370bbc7 100644
--- a/ggml-cuda.h
+++ b/ggml-cuda.h
@@ -1,7 +1,36 @@
+#include <cublas_v2.h>
+#include <cuda_runtime.h>
+
#ifdef __cplusplus
extern "C" {
#endif
+#define CUDA_CHECK(err) \
+ do { \
+ cudaError_t err_ = (err); \
+ if (err_ != cudaSuccess) { \
+ fprintf(stderr, "CUDA error %d at %s:%d: %s\n", err_, __FILE__, __LINE__, \
+ cudaGetErrorString(err_)); \
+ exit(1); \
+ } \
+ } while (0)
+
+#define CUBLAS_CHECK(err) \
+ do { \
+ cublasStatus_t err_ = (err); \
+ if (err_ != CUBLAS_STATUS_SUCCESS) { \
+ fprintf(stderr, "cuBLAS error %d at %s:%d\n", err_, __FILE__, __LINE__); \
+ exit(1); \
+ } \
+ } while (0)
+
+extern cublasHandle_t g_cublasH;
+extern cudaStream_t g_cudaStream;
+
+void ggml_init_cublas(void);
+void * ggml_cuda_pool_malloc(size_t size, size_t * actual_size);
+void ggml_cuda_pool_free(void * ptr, size_t size);
+
void dequantize_row_q4_0_cuda(const void * vx, float * y, int k, cudaStream_t stream);
void dequantize_row_q4_1_cuda(const void * vx, float * y, int k, cudaStream_t stream);
void dequantize_row_q4_2_cuda(const void * vx, float * y, int k, cudaStream_t stream);
diff --git a/ggml.c b/ggml.c
index 6cea937..2ea4e68 100644
--- a/ggml.c
+++ b/ggml.c
@@ -148,44 +148,7 @@ inline static void* ggml_aligned_malloc(size_t size) {
#elif defined(GGML_USE_OPENBLAS)
#include <cblas.h>
#elif defined(GGML_USE_CUBLAS)
-#include <cublas_v2.h>
-#include <cuda_runtime.h>
#include "ggml-cuda.h"
-
-#define CUDA_CHECK(err) \
- do { \
- cudaError_t err_ = (err); \
- if (err_ != cudaSuccess) { \
- printf("CUDA error %d at %s:%d: %s\n", err_, __FILE__, __LINE__, \
- cudaGetErrorString(err_)); \
- exit(1); \
- } \
- } while (0)
-
-#define CUBLAS_CHECK(err) \
- do { \
- cublasStatus_t err_ = (err); \
- if (err_ != CUBLAS_STATUS_SUCCESS) { \
- printf("cuBLAS error %d at %s:%d\n", err_, __FILE__, __LINE__); \
- exit(1); \
- } \
- } while (0)
-
-static cublasHandle_t cublasH = NULL;
-static cudaStream_t cudaStream = NULL;
-static void init_cublas(void) {
- if (cublasH == NULL) {
- // create cublas handle, bind a stream
- CUBLAS_CHECK(cublasCreate(&cublasH));
-
- CUDA_CHECK(cudaStreamCreateWithFlags(&cudaStream, cudaStreamNonBlocking));
-
- CUBLAS_CHECK(cublasSetStream(cublasH, cudaStream));
-
- // configure logging to stdout
- // CUBLAS_CHECK(cublasLoggerConfigure(1, 1, 0, NULL));
- }
-}
#endif
#undef MIN
@@ -3748,7 +3711,7 @@ struct ggml_context * ggml_init(struct ggml_init_params params) {
// initialize cuBLAS
#if defined(GGML_USE_CUBLAS)
- init_cublas();
+ ggml_init_cublas();
#endif
is_first_call = false;
@@ -7594,18 +7557,16 @@ static void ggml_compute_forward_mul_mat_f32(
}
#if defined(GGML_USE_CUBLAS)
- float *d_X = NULL;
- float *d_Y = NULL;
- float *d_D = NULL;
const float alpha = 1.0f;
const float beta = 0.0f;
const int x_ne = ne01 * ne10;
const int y_ne = ne11 * ne10;
const int d_ne = ne11 * ne01;
- CUDA_CHECK(cudaMalloc((void **)(&d_X), sizeof(float) * x_ne));
- CUDA_CHECK(cudaMalloc((void **)(&d_Y), sizeof(float) * y_ne));
- CUDA_CHECK(cudaMalloc((void **)(&d_D), sizeof(float) * d_ne));
+ size_t x_size, y_size, d_size;
+ float *d_X = ggml_cuda_pool_malloc(sizeof(float) * x_ne, &x_size);
+ float *d_Y = ggml_cuda_pool_malloc(sizeof(float) * y_ne, &y_size);
+ float *d_D = ggml_cuda_pool_malloc(sizeof(float) * d_ne, &d_size);
#endif
for (int64_t i03 = 0; i03 < ne03; i03++) {
@@ -7617,19 +7578,19 @@ static void ggml_compute_forward_mul_mat_f32(
#if defined(GGML_USE_CUBLAS)
// copy data to device
- CUDA_CHECK(cudaMemcpyAsync(d_X, x, sizeof(float) * x_ne, cudaMemcpyHostToDevice, cudaStream));
- CUDA_CHECK(cudaMemcpyAsync(d_Y, y, sizeof(float) * y_ne, cudaMemcpyHostToDevice, cudaStream));
+ CUDA_CHECK(cudaMemcpyAsync(d_X, x, sizeof(float) * x_ne, cudaMemcpyHostToDevice, g_cudaStream));
+ CUDA_CHECK(cudaMemcpyAsync(d_Y, y, sizeof(float) * y_ne, cudaMemcpyHostToDevice, g_cudaStream));
// compute
CUBLAS_CHECK(
- cublasSgemm(cublasH, CUBLAS_OP_T, CUBLAS_OP_N,
+ cublasSgemm(g_cublasH, CUBLAS_OP_T, CUBLAS_OP_N,
ne01, ne11, ne10,
&alpha, d_X, ne00,
d_Y, ne10,
&beta, d_D, ne01));
// copy data to host
- CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, cudaStream));
+ CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, g_cudaStream));
#else
// zT = y * xT
cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasTrans,
@@ -7641,10 +7602,10 @@ static void ggml_compute_forward_mul_mat_f32(
}
}
#if defined(GGML_USE_CUBLAS)
- CUDA_CHECK(cudaStreamSynchronize(cudaStream));
- CUDA_CHECK(cudaFree(d_X));
- CUDA_CHECK(cudaFree(d_Y));
- CUDA_CHECK(cudaFree(d_D));
+ CUDA_CHECK(cudaStreamSynchronize(g_cudaStream));
+ ggml_cuda_pool_free(d_X, x_size);
+ ggml_cuda_pool_free(d_Y, y_size);
+ ggml_cuda_pool_free(d_D, d_size);
#endif
//printf("CBLAS F32 = %f ms, %d x %d x %d x %d\n", (ggml_perf_time_us() - t0)/1000.0, ne0, ne1, ne2, ne3);
@@ -7794,18 +7755,16 @@ static void ggml_compute_forward_mul_mat_f16_f32(
#if defined(GGML_USE_CUBLAS)
ggml_fp16_t * const wdata = params->wdata;
- float *d_X = NULL;
- float *d_Y = NULL;
- float *d_D = NULL;
const float alpha = 1.0f;
const float beta = 0.0f;
const int x_ne = ne01 * ne10;
const int y_ne = ne11 * ne10;
const int d_ne = ne11 * ne01;
- CUDA_CHECK(cudaMalloc((void **)(&d_X), sizeof(ggml_fp16_t) * x_ne));
- CUDA_CHECK(cudaMalloc((void **)(&d_Y), sizeof(float) * y_ne));
- CUDA_CHECK(cudaMalloc((void **)(&d_D), sizeof(float) * d_ne));
+ size_t x_size, y_size, d_size;
+ float *d_X = ggml_cuda_pool_malloc(sizeof(float) * x_ne, &x_size);
+ float *d_Y = ggml_cuda_pool_malloc(sizeof(float) * y_ne, &y_size);
+ float *d_D = ggml_cuda_pool_malloc(sizeof(float) * d_ne, &d_size);
#else
float * const wdata = params->wdata;
#endif
@@ -7839,12 +7798,12 @@ static void ggml_compute_forward_mul_mat_f16_f32(
float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
// copy data to device
- CUDA_CHECK(cudaMemcpyAsync(d_X, x, sizeof(ggml_fp16_t) * x_ne, cudaMemcpyHostToDevice, cudaStream));
- CUDA_CHECK(cudaMemcpyAsync(d_Y, y, sizeof(ggml_fp16_t) * y_ne, cudaMemcpyHostToDevice, cudaStream));
+ CUDA_CHECK(cudaMemcpyAsync(d_X, x, sizeof(ggml_fp16_t) * x_ne, cudaMemcpyHostToDevice, g_cudaStream));
+ CUDA_CHECK(cudaMemcpyAsync(d_Y, y, sizeof(ggml_fp16_t) * y_ne, cudaMemcpyHostToDevice, g_cudaStream));
// compute
CUBLAS_CHECK(
- cublasGemmEx(cublasH, CUBLAS_OP_T, CUBLAS_OP_N,
+ cublasGemmEx(g_cublasH, CUBLAS_OP_T, CUBLAS_OP_N,
ne01, ne11, ne10,
&alpha, d_X, CUDA_R_16F, ne00,
d_Y, CUDA_R_16F, ne10,
@@ -7853,7 +7812,7 @@ static void ggml_compute_forward_mul_mat_f16_f32(
CUBLAS_GEMM_DEFAULT));
// copy data to host
- CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, cudaStream));
+ CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, g_cudaStream));
#else
const float * x = wdata;
const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
@@ -7871,10 +7830,10 @@ static void ggml_compute_forward_mul_mat_f16_f32(
}
#if defined(GGML_USE_CUBLAS)
- CUDA_CHECK(cudaStreamSynchronize(cudaStream));
- CUDA_CHECK(cudaFree(d_X));
- CUDA_CHECK(cudaFree(d_Y));
- CUDA_CHECK(cudaFree(d_D));
+ CUDA_CHECK(cudaStreamSynchronize(g_cudaStream));
+ ggml_cuda_pool_free(d_X, x_size);
+ ggml_cuda_pool_free(d_Y, y_size);
+ ggml_cuda_pool_free(d_D, d_size);
#endif
/*printf("CBLAS F16 = %f ms, %d x %d x %d x %d\n", (ggml_perf_time_us() - t0)/1000.0, ne0, ne1, ne2, ne3);*/
@@ -8042,20 +8001,17 @@ static void ggml_compute_forward_mul_mat_q_f32(
}
#if defined(GGML_USE_CUBLAS)
- float *d_X = NULL;
- float *d_Y = NULL;
- float *d_D = NULL;
- float *d_Q = NULL;
const float alpha = 1.0f;
const float beta = 0.0f;
const int x_ne = ne01 * ne10;
const int y_ne = ne11 * ne10;
const int d_ne = ne11 * ne01;
- CUDA_CHECK(cudaMalloc((void **)(&d_X), sizeof(float) * x_ne));
- CUDA_CHECK(cudaMalloc((void **)(&d_Y), sizeof(float) * y_ne));
- CUDA_CHECK(cudaMalloc((void **)(&d_D), sizeof(float) * d_ne));
- CUDA_CHECK(cudaMalloc((void **)(&d_Q), GGML_TYPE_SIZE[type] * x_ne / GGML_BLCK_SIZE[type]));
+ size_t x_size, y_size, d_size, q_size;
+ float *d_X = ggml_cuda_pool_malloc(sizeof(float) * x_ne, &x_size);
+ float *d_Y = ggml_cuda_pool_malloc(sizeof(float) * y_ne, &y_size);
+ float *d_D = ggml_cuda_pool_malloc(sizeof(float) * d_ne, &d_size);
+ float *d_Q = ggml_cuda_pool_malloc(GGML_TYPE_SIZE[type] * x_ne / GGML_BLCK_SIZE[type], &q_size);
void (*dequantize_row_q_cuda)(const void * x, float * y, int k, cudaStream_t stream) = NULL;
if (type == GGML_TYPE_Q4_0) {
@@ -8085,9 +8041,9 @@ static void ggml_compute_forward_mul_mat_q_f32(
// copy and dequantize on device
CUDA_CHECK(
cudaMemcpyAsync(d_Q, (char *) src0->data + i03*nb03 + i02*nb02,
- GGML_TYPE_SIZE[type] * x_ne / GGML_BLCK_SIZE[type], cudaMemcpyHostToDevice, cudaStream));
+ GGML_TYPE_SIZE[type] * x_ne / GGML_BLCK_SIZE[type], cudaMemcpyHostToDevice, g_cudaStream));
- dequantize_row_q_cuda(d_Q, d_X, ne01 * ne00, cudaStream);
+ dequantize_row_q_cuda(d_Q, d_X, ne01 * ne00, g_cudaStream);
CUDA_CHECK(cudaGetLastError());
#else
{
@@ -8103,18 +8059,18 @@ static void ggml_compute_forward_mul_mat_q_f32(
#if defined(GGML_USE_CUBLAS)
// copy data to device
- CUDA_CHECK(cudaMemcpyAsync(d_Y, y, sizeof(float) * y_ne, cudaMemcpyHostToDevice, cudaStream));
+ CUDA_CHECK(cudaMemcpyAsync(d_Y, y, sizeof(float) * y_ne, cudaMemcpyHostToDevice, g_cudaStream));
// compute
CUBLAS_CHECK(
- cublasSgemm(cublasH, CUBLAS_OP_T, CUBLAS_OP_N,
+ cublasSgemm(g_cublasH, CUBLAS_OP_T, CUBLAS_OP_N,
ne01, ne11, ne10,
&alpha, d_X, ne00,
d_Y, ne10,
&beta, d_D, ne01));
// copy data to host
- CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, cudaStream));
+ CUDA_CHECK(cudaMemcpyAsync(d, d_D, sizeof(float) * d_ne, cudaMemcpyDeviceToHost, g_cudaStream));
#else
// zT = y * xT
cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasTrans,
@@ -8127,11 +8083,11 @@ static void ggml_compute_forward_mul_mat_q_f32(
}
#if defined(GGML_USE_CUBLAS)
- CUDA_CHECK(cudaStreamSynchronize(cudaStream));
- CUDA_CHECK(cudaFree(d_X));
- CUDA_CHECK(cudaFree(d_Y));
- CUDA_CHECK(cudaFree(d_D));
- CUDA_CHECK(cudaFree(d_Q));
+ CUDA_CHECK(cudaStreamSynchronize(g_cudaStream));
+ ggml_cuda_pool_free(d_X, x_size);
+ ggml_cuda_pool_free(d_Y, y_size);
+ ggml_cuda_pool_free(d_D, d_size);
+ ggml_cuda_pool_free(d_Q, q_size);
#endif
//printf("CBLAS = %f ms, %d x %d x %d x %d\n", (ggml_perf_time_us() - t0)/1000.0, ne0, ne1, ne2, ne3);