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-rw-r--r--CMakeLists.txt2
-rw-r--r--Makefile5
-rw-r--r--ggml-opencl.c474
-rw-r--r--ggml-opencl.cpp1034
-rw-r--r--ggml-opencl.h18
-rw-r--r--ggml.c83
-rw-r--r--ggml.h1
-rw-r--r--llama.cpp32
8 files changed, 1113 insertions, 536 deletions
diff --git a/CMakeLists.txt b/CMakeLists.txt
index 3471e44..39db2e3 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -201,7 +201,7 @@ if (LLAMA_CLBLAST)
if (CLBlast_FOUND)
message(STATUS "CLBlast found")
- set(GGML_OPENCL_SOURCES ggml-opencl.c ggml-opencl.h)
+ set(GGML_OPENCL_SOURCES ggml-opencl.cpp ggml-opencl.h)
add_compile_definitions(GGML_USE_CLBLAST)
diff --git a/Makefile b/Makefile
index 9e2f8aa..08e2503 100644
--- a/Makefile
+++ b/Makefile
@@ -138,6 +138,7 @@ ggml-cuda.o: ggml-cuda.cu ggml-cuda.h
endif
ifdef LLAMA_CLBLAST
CFLAGS += -DGGML_USE_CLBLAST
+ CXXFLAGS += -DGGML_USE_CLBLAST
# Mac provides OpenCL as a framework
ifeq ($(UNAME_S),Darwin)
LDFLAGS += -lclblast -framework OpenCL
@@ -145,8 +146,8 @@ ifdef LLAMA_CLBLAST
LDFLAGS += -lclblast -lOpenCL
endif
OBJS += ggml-opencl.o
-ggml-opencl.o: ggml-opencl.c ggml-opencl.h
- $(CC) $(CFLAGS) -c $< -o $@
+ggml-opencl.o: ggml-opencl.cpp ggml-opencl.h
+ $(CXX) $(CXXFLAGS) -c $< -o $@
endif
ifneq ($(filter aarch64%,$(UNAME_M)),)
# Apple M1, M2, etc.
diff --git a/ggml-opencl.c b/ggml-opencl.c
deleted file mode 100644
index e26631f..0000000
--- a/ggml-opencl.c
+++ /dev/null
@@ -1,474 +0,0 @@
-#include "ggml-opencl.h"
-
-#define CL_TARGET_OPENCL_VERSION 110
-#include <clblast_c.h>
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-
-#include "ggml.h"
-
-#define MULTILINE_QUOTE(...) #__VA_ARGS__
-static const char * program_source = MULTILINE_QUOTE(
-
-typedef char int8_t;
-typedef uchar uint8_t;
-typedef int int32_t;
-typedef uint uint32_t;
-
-struct __attribute__ ((packed)) block_q4_0
-{
- half d;
- uint8_t qs[16]; /* QK4_0 / 2 */
-};
-
-struct __attribute__ ((packed)) block_q4_1
-{
- half d;
- half m;
- uint8_t qs[16]; /* QK4_1 / 2 */
-};
-
-struct __attribute__ ((packed)) block_q5_0
-{
- half d;
- uint32_t qh;
- uint8_t qs[16]; /* QK5_0 / 2 */
-};
-
-struct __attribute__ ((packed)) block_q5_1
-{
- half d;
- half m;
- uint32_t qh;
- uint8_t qs[16]; /* QK5_1 / 2 */
-};
-
-struct __attribute__ ((packed)) block_q8_0
-{
- half d;
- int8_t qs[32]; /* QK8_0 */
-};
-
-
-__kernel void dequantize_row_q4_0(__global struct block_q4_0* x, __global float* y) {
- const uint i = get_global_id(0) / 32; /* QK4_0 */
- const uint j = get_local_id(0);
-
- const float d = vload_half(0, (__global half*) &x[i].d);
-
- const int x0 = (x[i].qs[j] & 0xf) - 8;
- const int x1 = (x[i].qs[j] >> 4) - 8;
-
- y[i*32 + j + 0 ] = x0*d;
- y[i*32 + j + 16] = x1*d;
-}
-
-__kernel void dequantize_row_q4_1(__global struct block_q4_1* x, __global float* y) {
- const uint i = get_global_id(0) / 32; /* QK4_1 */
- const uint j = get_local_id(0);
-
- const float d = vload_half(0, (__global half*) &x[i].d);
- const float m = vload_half(0, (__global half*) &x[i].m);
-
- const int x0 = (x[i].qs[j] & 0xf);
- const int x1 = (x[i].qs[j] >> 4);
-
- y[i*32 + j + 0 ] = x0*d + m;
- y[i*32 + j + 16] = x1*d + m;
-}
-
-__kernel void dequantize_row_q5_0(__global struct block_q5_0* x, __global float* y) {
- const uint i = get_global_id(0) / 32; /* QK5_0 */
- const uint j = get_local_id(0);
-
- const float d = vload_half(0, (__global half*) &x[i].d);
-
- uint32_t qh = x[i].qh;
-
- const uint8_t xh_0 = ((qh >> (j + 0)) << 4) & 0x10;
- const uint8_t xh_1 = ((qh >> (j + 12)) ) & 0x10;
-
- const int32_t x0 = ((x[i].qs[j] & 0xf) | xh_0) - 16;
- const int32_t x1 = ((x[i].qs[j] >> 4) | xh_1) - 16;
-
- y[i*32 + j + 0 ] = x0*d;
- y[i*32 + j + 16] = x1*d;
-}
-
-__kernel void dequantize_row_q5_1(__global struct block_q5_1* x, __global float* y) {
- const uint i = get_global_id(0) / 32; /* QK5_1 */
- const uint j = get_local_id(0);
-
- const float d = vload_half(0, (__global half*) &x[i].d);
- const float m = vload_half(0, (__global half*) &x[i].m);
-
- uint32_t qh = x[i].qh;
-
- const uint8_t xh_0 = ((qh >> (j + 0)) << 4) & 0x10;
- const uint8_t xh_1 = ((qh >> (j + 12)) ) & 0x10;
-
- const int x0 = (x[i].qs[j] & 0xf) | xh_0;
- const int x1 = (x[i].qs[j] >> 4) | xh_1;
-
- y[i*32 + j + 0 ] = x0*d + m;
- y[i*32 + j + 16] = x1*d + m;
-}
-
-__kernel void dequantize_row_q8_0(__global struct block_q8_0* x, __global float* y) {
- const uint i = get_global_id(0) / 32; /* QK8_0 */
- const uint j = get_local_id(0);
-
- const float d = vload_half(0, (__global half*) &x[i].d);
- y[i*32 + j] = x[i].qs[j]*d;
-}
-
-);
-
-#define CL_CHECK(err) \
- do { \
- cl_int err_ = (err); \
- if (err_ != CL_SUCCESS) { \
- fprintf(stderr, "ggml_opencl: %s error %d at %s:%d\n", \
- #err, err_, __FILE__, __LINE__); \
- exit(1); \
- } \
- } while (0)
-
-#define CLBLAST_CHECK(err) \
- do { \
- CLBlastStatusCode err_ = (err); \
- if (err_ != CLBlastSuccess) { \
- fprintf(stderr, "ggml_opencl: %s error %d at %s:%d\n", \
- #err, err_, __FILE__, __LINE__); \
- exit(1); \
- } \
- } while (0)
-
-static cl_platform_id platform;
-static cl_device_id device;
-static cl_context context;
-static cl_command_queue queue;
-static cl_program program;
-static cl_kernel kernel_q4_0, kernel_q4_1, kernel_q5_0, kernel_q5_1, kernel_q8_0;
-static cl_mem cl_buffer_a, cl_buffer_qb, cl_buffer_b, cl_buffer_c;
-static size_t cl_size_a = 0, cl_size_qb = 0, cl_size_b = 0, cl_size_c = 0;
-
-static cl_program build_program_from_source(cl_context ctx, cl_device_id dev, const char* program_buffer) {
- cl_program p;
- char *program_log;
- size_t program_size, log_size;
- int err;
-
- program_size = strlen(program_buffer);
-
- p = clCreateProgramWithSource(ctx, 1, (const char**)&program_buffer, &program_size, &err);
- if(err < 0) {
- fprintf(stderr, "OpenCL error creating program");
- exit(1);
- }
-
- err = clBuildProgram(p, 0, NULL, NULL, NULL, NULL);
- if(err < 0) {
-
- clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size);
- program_log = (char*) malloc(log_size + 1);
- program_log[log_size] = '\0';
- clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, log_size + 1, program_log, NULL);
- printf("%s\n", program_log);
- free(program_log);
- exit(1);
- }
-
- return p;
-}
-
-void ggml_cl_init(void) {
- cl_int err = 0;
-
- struct cl_device;
- struct cl_platform {
- cl_platform_id id;
- unsigned number;
- char name[128];
- char vendor[128];
- struct cl_device * devices;
- unsigned n_devices;
- struct cl_device * default_device;
- };
-
- struct cl_device {
- struct cl_platform * platform;
- cl_device_id id;
- unsigned number;
- cl_device_type type;
- char name[128];
- };
-
- enum { NPLAT = 16, NDEV = 16 };
-
- struct cl_platform platforms[NPLAT];
- unsigned n_platforms = 0;
- struct cl_device devices[NDEV];
- unsigned n_devices = 0;
- struct cl_device * default_device = NULL;
-
- platform = NULL;
- device = NULL;
-
- cl_platform_id platform_ids[NPLAT];
- CL_CHECK(clGetPlatformIDs(NPLAT, platform_ids, &n_platforms));
-
- for (unsigned i = 0; i < n_platforms; i++) {
- struct cl_platform * p = &platforms[i];
- p->number = i;
- p->id = platform_ids[i];
- CL_CHECK(clGetPlatformInfo(p->id, CL_PLATFORM_NAME, sizeof(p->name), &p->name, NULL));
- CL_CHECK(clGetPlatformInfo(p->id, CL_PLATFORM_VENDOR, sizeof(p->vendor), &p->vendor, NULL));
-
- cl_device_id device_ids[NDEV];
- cl_int clGetDeviceIDsError = clGetDeviceIDs(p->id, CL_DEVICE_TYPE_ALL, NDEV, device_ids, &p->n_devices);
- if (clGetDeviceIDsError == CL_DEVICE_NOT_FOUND) {
- p->n_devices = 0;
- } else {
- CL_CHECK(clGetDeviceIDsError);
- }
- p->devices = p->n_devices > 0 ? &devices[n_devices] : NULL;
- p->default_device = NULL;
-
- for (unsigned j = 0; j < p->n_devices; j++) {
- struct cl_device * d = &devices[n_devices];
- d->number = n_devices++;
- d->id = device_ids[j];
- d->platform = p;
- CL_CHECK(clGetDeviceInfo(d->id, CL_DEVICE_NAME, sizeof(d->name), &d->name, NULL));
- CL_CHECK(clGetDeviceInfo(d->id, CL_DEVICE_TYPE, sizeof(d->type), &d->type, NULL));
-
- if (p->default_device == NULL && d->type == CL_DEVICE_TYPE_GPU) {
- p->default_device = d;
- }
- }
-
- if (default_device == NULL && p->default_device != NULL) {
- default_device = p->default_device;
- }
- }
-
- if (n_devices == 0) {
- fprintf(stderr, "ggml_opencl: could find any OpenCL devices.\n");
- exit(1);
- }
-
- char * user_platform_string = getenv("GGML_OPENCL_PLATFORM");
- char * user_device_string = getenv("GGML_OPENCL_DEVICE");
- int user_platform_number = -1;
- int user_device_number = -1;
-
- unsigned n;
- if (user_platform_string != NULL && sscanf(user_platform_string, " %u", &n) == 1 && n < n_platforms) {
- user_platform_number = (int)n;
- }
- if (user_device_string != NULL && sscanf(user_device_string, " %u", &n) == 1 && n < n_devices) {
- user_device_number = (int)n;
- }
-
- struct cl_device * selected_devices = devices;
- unsigned n_selected_devices = n_devices;
-
- if (user_platform_number == -1 && user_platform_string != NULL && user_platform_string[0] != 0) {
- for (unsigned i = 0; i < n_platforms; i++) {
- struct cl_platform * p = &platforms[i];
- if (strstr(p->name, user_platform_string) != NULL ||
- strstr(p->vendor, user_platform_string) != NULL) {
- user_platform_number = (int)i;
- break;
- }
- }
- if (user_platform_number == -1) {
- fprintf(stderr, "ggml_opencl: no platform matching '%s' was found.\n", user_platform_string);
- exit(1);
- }
- }
- if (user_platform_number != -1) {
- struct cl_platform * p = &platforms[user_platform_number];
- selected_devices = p->devices;
- n_selected_devices = p->n_devices;
- default_device = p->default_device;
- if (n_selected_devices == 0) {
- fprintf(stderr, "ggml_opencl: selected platform '%s' does not have any devices.\n", p->name);
- exit(1);
- }
- }
-
- if (user_device_number == -1 && user_device_string != NULL && user_device_string[0] != 0) {
- for (unsigned i = 0; i < n_selected_devices; i++) {
- struct cl_device * d = &selected_devices[i];
- if (strstr(d->name, user_device_string) != NULL) {
- user_device_number = d->number;
- break;
- }
- }
- if (user_device_number == -1) {
- fprintf(stderr, "ggml_opencl: no device matching '%s' was found.\n", user_device_string);
- exit(1);
- }
- }
- if (user_device_number != -1) {
- selected_devices = &devices[user_device_number];
- n_selected_devices = 1;
- default_device = &selected_devices[0];
- }
-
- GGML_ASSERT(n_selected_devices > 0);
-
- if (default_device == NULL) {
- default_device = &selected_devices[0];
- }
-
- fprintf(stderr, "ggml_opencl: selecting platform: '%s'\n", default_device->platform->name);
- fprintf(stderr, "ggml_opencl: selecting device: '%s'\n", default_device->name);
- if (default_device->type != CL_DEVICE_TYPE_GPU) {
- fprintf(stderr, "ggml_opencl: warning, not a GPU: '%s'.\n", default_device->name);
- }
-
- platform = default_device->platform->id;
- device = default_device->id;
-
- cl_context_properties properties[] = {
- (intptr_t)CL_CONTEXT_PLATFORM, (intptr_t)platform, 0
- };
-
- CL_CHECK((context = clCreateContext(properties, 1, &device, NULL, NULL, &err), err));
-
- CL_CHECK((queue = clCreateCommandQueue(context, device, CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE, &err),
- (err != CL_INVALID_PROPERTY && err != CL_INVALID_VALUE ? err :
- (queue = clCreateCommandQueue(context, device, 0, &err), err)
- )));
-
- program = build_program_from_source(context, device, program_source);
-
- // Prepare dequantize kernels
- CL_CHECK((kernel_q4_0 = clCreateKernel(program, "dequantize_row_q4_0", &err), err));
- CL_CHECK((kernel_q4_1 = clCreateKernel(program, "dequantize_row_q4_1", &err), err));
- CL_CHECK((kernel_q5_0 = clCreateKernel(program, "dequantize_row_q5_0", &err), err));
- CL_CHECK((kernel_q5_1 = clCreateKernel(program, "dequantize_row_q5_1", &err), err));
- CL_CHECK((kernel_q8_0 = clCreateKernel(program, "dequantize_row_q8_0", &err), err));
-}
-
-static void ggml_cl_malloc(size_t req_size, size_t* cur_size, cl_mem_flags flags, cl_mem* buf) {
- if (req_size <= *cur_size) {
- return;
- }
-
- // Reallocate buffer with enough space
- if (*cur_size > 0) {
- clReleaseMemObject(*buf);
- }
- cl_int err;
- CL_CHECK((*buf = clCreateBuffer(context, flags, req_size, NULL, &err), err));
- *cur_size = req_size;
-}
-
-void ggml_cl_sgemm_wrapper(
- const enum ggml_blas_order order, const enum ggml_blas_op trans_a, const enum ggml_blas_op trans_b,
- const int m, const int n, const int k,
- const float alpha, const void *host_a, const int lda,
- const float *host_b, const int ldb, const float beta,
- float *host_c, const int ldc, const int btype) {
-
- cl_kernel kernel;
- size_t global = n * k, local, size_qb;
- bool dequant;
-
- switch (btype) {
- case GGML_TYPE_F32:
- dequant = false;
- break;
- case GGML_TYPE_Q4_0:
- dequant = true;
- kernel = kernel_q4_0;
- local = 16;
- size_qb = global * (sizeof(ggml_fp16_t) + local) / 32;
- break;
- case GGML_TYPE_Q4_1:
- dequant = true;
- kernel = kernel_q4_1;
- local = 16;
- size_qb = global * (sizeof(ggml_fp16_t) * 2 + local) / 32;
- break;
- case GGML_TYPE_Q5_0:
- dequant = true;
- kernel = kernel_q5_0;
- local = 16;
- size_qb = global * (sizeof(ggml_fp16_t) + sizeof(uint32_t) + local) / 32;
- break;
- case GGML_TYPE_Q5_1:
- dequant = true;
- kernel = kernel_q5_1;
- local = 16;
- size_qb = global * (sizeof(ggml_fp16_t) * 2 + sizeof(uint32_t) + local) / 32;
- break;
- case GGML_TYPE_Q8_0:
- dequant = true;
- kernel = kernel_q8_0;
- local = 32;
- size_qb = global * (sizeof(ggml_fp16_t) + local) / 32;
- break;
- default:
- fprintf(stderr, "Error: Unsupported OpenCL btype %d\n", btype);
- abort();
- }
-
- const size_t size_a = m * k * sizeof(float);
- const size_t size_b = n * k * sizeof(float);
- const size_t size_c = m * n * sizeof(float);
-
- // Prepare buffers
- ggml_cl_malloc(size_a, &cl_size_a, CL_MEM_READ_ONLY, &cl_buffer_a);
- if (dequant) {
- ggml_cl_malloc(size_qb, &cl_size_qb, CL_MEM_READ_ONLY, &cl_buffer_qb);
- }
- ggml_cl_malloc(size_b, &cl_size_b, CL_MEM_READ_WRITE, &cl_buffer_b);
- ggml_cl_malloc(size_c, &cl_size_c, CL_MEM_WRITE_ONLY, &cl_buffer_c);
-
- cl_event ev_a, ev_qb, ev_b;
-
- if (dequant) {
- CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &cl_buffer_qb));
- CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &cl_buffer_b));
- CL_CHECK(clEnqueueWriteBuffer(queue, cl_buffer_qb, CL_FALSE, 0, size_qb, host_b, 0, NULL, &ev_qb));
- } else {
- CL_CHECK(clEnqueueWriteBuffer(queue, cl_buffer_b, CL_FALSE, 0, size_b, host_b, 0, NULL, &ev_b));
- }
-
- CL_CHECK(clEnqueueWriteBuffer(queue, cl_buffer_a, CL_FALSE, 0, size_a, host_a, 0, NULL, &ev_a));
- if (dequant) {
- CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &global, &local, 1, &ev_qb, &ev_b));
- CL_CHECK(clReleaseEvent(ev_qb));
- }
- CL_CHECK(clWaitForEvents(1, &ev_a));
- CL_CHECK(clWaitForEvents(1, &ev_b));
- CL_CHECK(clReleaseEvent(ev_a));
- CL_CHECK(clReleaseEvent(ev_b));
-
- cl_event ev_sgemm;
- CLBLAST_CHECK(CLBlastSgemm(
- (CLBlastLayout)order,
- (CLBlastTranspose)trans_a, (CLBlastTranspose)trans_b,
- m, n, k,
- alpha,
- cl_buffer_a, 0, lda,
- cl_buffer_b, 0, ldb,
- beta,
- cl_buffer_c, 0, ldc,
- &queue, &ev_sgemm));
-
- cl_event ev_c;
- CL_CHECK(clEnqueueReadBuffer(queue, cl_buffer_c, CL_TRUE, 0, size_c, host_c, 1, &ev_sgemm, &ev_c));
-
- // Wait for completion
- CL_CHECK(clWaitForEvents(1, &ev_c));
- CL_CHECK(clReleaseEvent(ev_sgemm));
- CL_CHECK(clReleaseEvent(ev_c));
-}
diff --git a/ggml-opencl.cpp b/ggml-opencl.cpp
new file mode 100644
index 0000000..fb007dd
--- /dev/null
+++ b/ggml-opencl.cpp
@@ -0,0 +1,1034 @@
+#include "ggml-opencl.h"
+
+#include <array>
+#include <atomic>
+#include <sstream>
+
+#define CL_TARGET_OPENCL_VERSION 110
+#include <clblast.h>
+
+#include <stdlib.h>
+#include <stdio.h>
+#include <string.h>
+
+#include "ggml.h"
+
+#define CL_DMMV_BLOCK_SIZE 32;
+
+#define MULTILINE_QUOTE(...) #__VA_ARGS__
+static std::string program_source = MULTILINE_QUOTE(
+
+typedef char int8_t;
+typedef uchar uint8_t;
+typedef int int32_t;
+typedef uint uint32_t;
+
+struct __attribute__ ((packed)) block_q4_0
+{
+ half d;
+ uint8_t qs[QK4_0 / 2];
+};
+
+struct __attribute__ ((packed)) block_q4_1
+{
+ half d;
+ half m;
+ uint8_t qs[QK4_1 / 2];
+};
+
+struct __attribute__ ((packed)) block_q5_0
+{
+ half d;
+ uint32_t qh;
+ uint8_t qs[QK5_0 / 2];
+};
+
+struct __attribute__ ((packed)) block_q5_1
+{
+ half d;
+ half m;
+ uint32_t qh;
+ uint8_t qs[QK5_1 / 2];
+};
+
+struct __attribute__ ((packed)) block_q8_0
+{
+ half d;
+ int8_t qs[QK8_0];
+};
+
+
+__kernel void convert_fp16_to_fp32(__global half* x, __global float* y) {
+ const uint i = get_global_id(0);
+
+ y[i] = vload_half(0, &x[i]);
+}
+
+void dequantize_q4_0(__global const struct block_q4_0* x, const int ib, const int iqs, float* v0, float* v1) {
+ const float d = vload_half(0, &x[ib].d);
+
+ const uint8_t vui = x[ib].qs[iqs];
+
+ const int8_t vi0 = vui & 0xF;
+ const int8_t vi1 = vui >> 4;
+
+ *v0 = (vi0 - 8)*d;
+ *v1 = (vi1 - 8)*d;
+}
+void dequantize_q4_1(__global const struct block_q4_1* x, const int ib, const int iqs, float* v0, float* v1) {
+ const float d = vload_half(0, &x[ib].d);
+ const float m = vload_half(0, &x[ib].m);
+
+ const uint8_t vui = x[ib].qs[iqs];
+
+ const int8_t vi0 = vui & 0xF;
+ const int8_t vi1 = vui >> 4;
+
+ *v0 = vi0*d + m;
+ *v1 = vi1*d + m;
+}
+void dequantize_q5_0(__global const struct block_q5_0* x, const int ib, const int iqs, float* v0, float* v1) {
+ const float d = vload_half(0, &x[ib].d);
+
+ uint32_t qh = x[ib].qh;
+
+ const uint8_t xh_0 = ((qh >> (iqs + 0)) << 4) & 0x10;
+ const uint8_t xh_1 = ((qh >> (iqs + 12)) ) & 0x10;
+
+ const int32_t x0 = ((x[ib].qs[iqs] & 0xf) | xh_0) - 16;
+ const int32_t x1 = ((x[ib].qs[iqs] >> 4) | xh_1) - 16;
+
+ *v0 = x0*d;
+ *v1 = x1*d;
+}
+void dequantize_q5_1(__global const struct block_q5_1* x, const int ib, const int iqs, float* v0, float* v1) {
+ const float d = vload_half(0, &x[ib].d);
+ const float m = vload_half(0, &x[ib].m);
+
+ uint32_t qh = x[ib].qh;
+
+ const uint8_t xh_0 = ((qh >> (iqs + 0)) << 4) & 0x10;
+ const uint8_t xh_1 = ((qh >> (iqs + 12)) ) & 0x10;
+
+ const int32_t x0 = ((x[ib].qs[iqs] & 0xf) | xh_0);
+ const int32_t x1 = ((x[ib].qs[iqs] >> 4) | xh_1);
+
+ *v0 = x0*d + m;
+ *v1 = x1*d + m;
+}
+void dequantize_q8_0(__global const struct block_q8_0* x, const int ib, const int iqs, float* v0, float* v1) {
+ const float d = vload_half(0, &x[ib].d);
+
+ const int8_t vi0 = x[ib].qs[iqs + 0];
+ const int8_t vi1 = x[ib].qs[iqs + 1];
+
+ *v0 = vi0*d;
+ *v1 = vi1*d;
+}
+void convert_f16(__global half* x, const int ib, const int iqs, float* v0, float* v1){
+ *v0 = vload_half(0, &x[ib + 0]);
+ *v1 = vload_half(0, &x[ib + 1]);
+}
+);
+
+std::string dequant_template = MULTILINE_QUOTE(
+__kernel void KERNEL_NAME(__global X_TYPE* x, __global float* y) {
+ const int i = get_group_id(0)*get_local_size(0) + get_local_id(0)*2;
+
+ if (i >= get_global_size(0)) {
+ return;
+ }
+
+ const uint qk = QUANT_K;
+ const uint qr = QUANT_R;
+
+ const int ib = i/qk; // block index
+ const int iqs = (i%qk)/qr; // quant index
+ const int iybs = i - i%qk; // y block start index
+ const int y_offset = qr == 1 ? 1 : qk/2;
+
+ // dequantize
+ float v0, v1;
+ DEQUANT_FUNC(x, ib, iqs, &v0, &v1);
+ y[iybs + iqs + 0] = v0;
+ y[iybs + iqs + y_offset] = v1;
+}
+);
+
+std::string dequant_mul_mat_vec_template = MULTILINE_QUOTE(
+__kernel void KERNEL_NAME(__global X_TYPE* x, __local float* tmp, __global float* y, __global float* dst, const int ncols) {
+ const int block_size = get_local_size(0);
+ const int row = get_global_id(0) / block_size;
+ const int tid = get_local_id(0);
+
+ const uint qk = QUANT_K;
+ const uint qr = QUANT_R;
+
+ const int y_offset = qr == 1 ? 1 : qk/2;
+
+ tmp[tid] = 0;
+
+ for (int i = 0; i < ncols/block_size; i += 2) {
+ const int col = i*block_size + 2*tid;
+ const int ib = (row*ncols + col)/qk; // block index
+ const int iqs = (col%qk)/qr; // quant index
+ const int iybs = col - col%qk; // y block start index
+
+ // dequantize
+ float v0, v1;
+ DEQUANT_FUNC(x, ib, iqs, &v0, &v1);
+
+ // matrix multiplication
+ tmp[tid] += v0 * y[iybs + iqs + 0];
+ tmp[tid] += v1 * y[iybs + iqs + y_offset];
+ }
+
+ // sum up partial sums and write back result
+ barrier(CLK_LOCAL_MEM_FENCE);
+ for (int s=block_size/2; s>0; s>>=1) {
+ if (tid < s) {
+ tmp[tid] += tmp[tid + s];
+ }
+ barrier(CLK_LOCAL_MEM_FENCE);
+ }
+ if (tid == 0) {
+ dst[row] = tmp[0];
+ }
+}
+);
+
+#define CL_CHECK(err) \
+ do { \
+ cl_int err_ = (err); \
+ if (err_ != CL_SUCCESS) { \
+ fprintf(stderr, "ggml_opencl: %s error %d at %s:%d\n", \
+ #err, err_, __FILE__, __LINE__); \
+ exit(1); \
+ } \
+ } while (0)
+
+#define CLBLAST_CHECK(err) \
+ do { \
+ CLBlastStatusCode err_ = (err); \
+ if (err_ != CLBlastSuccess) { \
+ fprintf(stderr, "ggml_opencl: %s error %d at %s:%d\n", \
+ #err, err_, __FILE__, __LINE__); \
+ exit(1); \
+ } \
+ } while (0)
+
+std::array<std::string, 5> dequant_str_keys = {
+ "KERNEL_NAME", "X_TYPE", "QUANT_K", "QUANT_R", "DEQUANT_FUNC"
+};
+
+std::array<std::string, 30> dequant_str_values = {
+ "dequantize_row_q4_0", "struct block_q4_0", "QK4_0", "QR4_0", "dequantize_q4_0",
+ "dequantize_row_q4_1", "struct block_q4_1", "QK4_1", "QR4_1", "dequantize_q4_1",
+ "dequantize_row_q5_0", "struct block_q5_0", "QK5_0", "QR5_0", "dequantize_q5_0",
+ "dequantize_row_q5_1", "struct block_q5_1", "QK5_1", "QR5_1", "dequantize_q5_1",
+ "dequantize_row_q8_0", "struct block_q8_0", "QK8_0", "QR8_0", "dequantize_q8_0",
+ "convert_row_f16", "half", "1", "1", "convert_f16"
+};
+
+std::array<std::string, 30> dequant_mul_mat_vec_str_values = {
+ "dequantize_mul_mat_vec_q4_0", "struct block_q4_0", "QK4_0", "QR4_0", "dequantize_q4_0",
+ "dequantize_mul_mat_vec_q4_1", "struct block_q4_1", "QK4_1", "QR4_1", "dequantize_q4_1",
+ "dequantize_mul_mat_vec_q5_0", "struct block_q5_0", "QK5_0", "QR5_0", "dequantize_q5_0",
+ "dequantize_mul_mat_vec_q5_1", "struct block_q5_1", "QK5_1", "QR5_1", "dequantize_q5_1",
+ "dequantize_mul_mat_vec_q8_0", "struct block_q8_0", "QK8_0", "QR8_0", "dequantize_q8_0",
+ "convert_mul_mat_vec_f16", "half", "1", "1", "convert_f16"
+};
+
+std::string& replace(std::string& s, const std::string& from, const std::string& to) {
+ size_t pos = 0;
+ while ((pos = s.find(from, pos)) != std::string::npos) {
+ s.replace(pos, from.length(), to);
+ pos += to.length();
+ }
+ return s;
+}
+
+std::string generate_kernels() {
+ std::stringstream src;
+ src << program_source << '\n';
+ for (size_t i = 0; i < dequant_str_values.size(); i += dequant_str_keys.size()) {
+ std::string dequant_kernel = dequant_template;
+ std::string dmmv_kernel = dequant_mul_mat_vec_template;
+ for (size_t j = 0; j < dequant_str_keys.size(); j++) {
+ replace(dequant_kernel, dequant_str_keys[j], dequant_str_values[i + j]);
+ replace(dmmv_kernel, dequant_str_keys[j], dequant_mul_mat_vec_str_values[i + j]);
+ }
+ src << dequant_kernel << '\n';
+ src << dmmv_kernel << '\n';
+ }
+ return src.str();
+}
+
+static cl_platform_id platform;
+static cl_device_id device;
+static cl_context context;
+static cl_command_queue queue;
+static cl_program program;
+static cl_kernel convert_row_f16_cl;
+static cl_kernel dequantize_row_q4_0_cl, dequantize_row_q4_1_cl, dequantize_row_q5_0_cl, dequantize_row_q5_1_cl, dequantize_row_q8_0_cl;
+static cl_kernel dequantize_mul_mat_vec_q4_0_cl, dequantize_mul_mat_vec_q4_1_cl, dequantize_mul_mat_vec_q5_0_cl, dequantize_mul_mat_vec_q5_1_cl, dequantize_mul_mat_vec_q8_0_cl, convert_mul_mat_vec_f16_cl;
+static bool fp16_support;
+
+static cl_program build_program_from_source(cl_context ctx, cl_device_id dev, const char* program_buffer) {
+ cl_program p;
+ char *program_log;
+ size_t program_size;
+ size_t log_size;
+ int err;
+
+ program_size = strlen(program_buffer);
+
+ p = clCreateProgramWithSource(ctx, 1, (const char**)&program_buffer, &program_size, &err);
+ if(err < 0) {
+ fprintf(stderr, "OpenCL error creating program");
+ exit(1);
+ }
+
+ const char* compile_opts = "-cl-mad-enable -cl-unsafe-math-optimizations -cl-finite-math-only -cl-fast-relaxed-math "
+ "-DQK4_0=32 -DQR4_0=2 -DQK4_1=32 -DQR4_1=2 -DQK5_0=32 -DQR5_0=2 -DQK5_1=32 -DQR5_1=2 -DQK8_0=32 -DQR8_0=1";
+
+ err = clBuildProgram(p, 0, NULL, compile_opts, NULL, NULL);
+ if(err < 0) {
+
+ clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size);
+ program_log = (char*) malloc(log_size + 1);
+ program_log[log_size] = '\0';
+ clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, log_size + 1, program_log, NULL);
+ fprintf(stderr, "ggml_opencl: kernel compile error:\n\n%s\n", program_log);
+ free(program_log);
+ exit(1);
+ }
+
+ return p;
+}
+
+void ggml_cl_init(void) {
+ cl_int err;
+
+ struct cl_device;
+ struct cl_platform {
+ cl_platform_id id;
+ unsigned number;
+ char name[128];
+ char vendor[128];
+ struct cl_device * devices;
+ unsigned n_devices;
+ struct cl_device * default_device;
+ };
+
+ struct cl_device {
+ struct cl_platform * platform;
+ cl_device_id id;
+ unsigned number;
+ cl_device_type type;
+ char name[128];
+ };
+
+ enum { NPLAT = 16, NDEV = 16 };
+
+ struct cl_platform platforms[NPLAT];
+ unsigned n_platforms = 0;
+ struct cl_device devices[NDEV];
+ unsigned n_devices = 0;
+ struct cl_device * default_device = NULL;
+
+ platform = NULL;
+ device = NULL;
+
+ cl_platform_id platform_ids[NPLAT];
+ CL_CHECK(clGetPlatformIDs(NPLAT, platform_ids, &n_platforms));
+
+ for (unsigned i = 0; i < n_platforms; i++) {
+ struct cl_platform * p = &platforms[i];
+ p->number = i;
+ p->id = platform_ids[i];
+ CL_CHECK(clGetPlatformInfo(p->id, CL_PLATFORM_NAME, sizeof(p->name), &p->name, NULL));
+ CL_CHECK(clGetPlatformInfo(p->id, CL_PLATFORM_VENDOR, sizeof(p->vendor), &p->vendor, NULL));
+
+ cl_device_id device_ids[NDEV];
+ cl_int clGetDeviceIDsError = clGetDeviceIDs(p->id, CL_DEVICE_TYPE_ALL, NDEV, device_ids, &p->n_devices);
+ if (clGetDeviceIDsError == CL_DEVICE_NOT_FOUND) {
+ p->n_devices = 0;
+ } else {
+ CL_CHECK(clGetDeviceIDsError);
+ }
+ p->devices = p->n_devices > 0 ? &devices[n_devices] : NULL;
+ p->default_device = NULL;
+
+ for (unsigned j = 0; j < p->n_devices; j++) {
+ struct cl_device * d = &devices[n_devices];
+ d->number = n_devices++;
+ d->id = device_ids[j];
+ d->platform = p;
+ CL_CHECK(clGetDeviceInfo(d->id, CL_DEVICE_NAME, sizeof(d->name), &d->name, NULL));
+ CL_CHECK(clGetDeviceInfo(d->id, CL_DEVICE_TYPE, sizeof(d->type), &d->type, NULL));
+
+ if (p->default_device == NULL && d->type == CL_DEVICE_TYPE_GPU) {
+ p->default_device = d;
+ }
+ }
+
+ if (default_device == NULL && p->default_device != NULL) {
+ default_device = p->default_device;
+ }
+ }
+
+ if (n_devices == 0) {
+ fprintf(stderr, "ggml_opencl: could find any OpenCL devices.\n");
+ exit(1);
+ }
+
+ char * user_platform_string = getenv("GGML_OPENCL_PLATFORM");
+ char * user_device_string = getenv("GGML_OPENCL_DEVICE");
+ int user_platform_number = -1;
+ int user_device_number = -1;
+
+ unsigned n;
+ if (user_platform_string != NULL && sscanf(user_platform_string, " %u", &n) == 1 && n < n_platforms) {
+ user_platform_number = (int)n;
+ }
+ if (user_device_string != NULL && sscanf(user_device_string, " %u", &n) == 1 && n < n_devices) {
+ user_device_number = (int)n;
+ }
+ if (user_platform_number != -1 && user_device_number != -1) {
+ cl_platform* platform = &platforms[user_platform_number];
+ if ((unsigned)user_device_number >= platform->n_devices) {
+ fprintf(stderr, "ggml_opencl: invalid device number %d\n", user_device_number);
+ exit(1);
+ }
+ default_device = &platform->devices[user_device_number];
+ } else {
+
+ struct cl_device * selected_devices = devices;
+ unsigned n_selected_devices = n_devices;
+
+ if (user_platform_number == -1 && user_platform_string != NULL && user_platform_string[0] != 0) {
+ for (unsigned i = 0; i < n_platforms; i++) {
+ struct cl_platform * p = &platforms[i];
+ if (strstr(p->name, user_platform_string) != NULL ||
+ strstr(p->vendor, user_platform_string) != NULL) {
+ user_platform_number = (int)i;
+ break;
+ }
+ }
+ if (user_platform_number == -1) {
+ fprintf(stderr, "ggml_opencl: no platform matching '%s' was found.\n", user_platform_string);
+ exit(1);
+ }
+ }
+ if (user_platform_number != -1) {
+ struct cl_platform * p = &platforms[user_platform_number];
+ selected_devices = p->devices;
+ n_selected_devices = p->n_devices;
+ default_device = p->default_device;
+ if (n_selected_devices == 0) {
+ fprintf(stderr, "ggml_opencl: selected platform '%s' does not have any devices.\n", p->name);
+ exit(1);
+ }
+ }
+
+ if (user_device_number == -1 && user_device_string != NULL && user_device_string[0] != 0) {
+ for (unsigned i = 0; i < n_selected_devices; i++) {
+ struct cl_device * d = &selected_devices[i];
+ if (strstr(d->name, user_device_string) != NULL) {
+ user_device_number = d->number;
+ break;
+ }
+ }
+ if (user_device_number == -1) {
+ fprintf(stderr, "ggml_opencl: no device matching '%s' was found.\n", user_device_string);
+ exit(1);
+ }
+ }
+ if (user_device_number != -1) {
+ selected_devices = &devices[user_device_number];
+ n_selected_devices = 1;
+ default_device = &selected_devices[0];
+ }
+
+ GGML_ASSERT(n_selected_devices > 0);
+
+ if (default_device == NULL) {
+ default_device = &selected_devices[0];
+ }
+ }
+
+ fprintf(stderr, "ggml_opencl: selecting platform: '%s'\n", default_device->platform->name);
+ fprintf(stderr, "ggml_opencl: selecting device: '%s'\n", default_device->name);
+ if (default_device->type != CL_DEVICE_TYPE_GPU) {
+ fprintf(stderr, "ggml_opencl: warning, not a GPU: '%s'.\n", default_device->name);
+ }
+
+ platform = default_device->platform->id;
+ device = default_device->id;
+
+ size_t ext_str_size;
+ clGetDeviceInfo(device, CL_DEVICE_EXTENSIONS, 0, NULL, &ext_str_size);
+ char* ext_buffer = (char*) malloc(sizeof(char) * ext_str_size);
+ clGetDeviceInfo(device, CL_DEVICE_EXTENSIONS, ext_str_size, ext_buffer, NULL);
+ // Check if ext_buffer contains cl_khr_fp16
+ for (size_t i = 0; i < ext_str_size - 12; i++) {
+ if (memcmp(ext_buffer + i, "cl_khr_fp16", 11) == 0) {
+ fp16_support = true;
+ break;
+ }
+ }
+ free(ext_buffer);
+ fprintf(stderr, "ggml_opencl: device FP16 support: %s\n", fp16_support ? "true" : "false");
+
+ cl_context_properties properties[] = {
+ (intptr_t)CL_CONTEXT_PLATFORM, (intptr_t)platform, 0
+ };
+
+ CL_CHECK((context = clCreateContext(properties, 1, &device, NULL, NULL, &err), err));
+
+ CL_CHECK((queue = clCreateCommandQueue(context, device, CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE, &err),
+ (err != CL_INVALID_PROPERTY && err != CL_INVALID_VALUE ? err :
+ (queue = clCreateCommandQueue(context, device, 0, &err), err)
+ )));
+
+ const std::string kernel_src = generate_kernels();
+
+ program = build_program_from_source(context, device, kernel_src.c_str());
+
+ // FP16 to FP32 kernel
+ CL_CHECK((convert_row_f16_cl = clCreateKernel(program, "convert_row_f16", &err), err));
+
+ // Dequantize kernels
+ CL_CHECK((dequantize_row_q4_0_cl = clCreateKernel(program, "dequantize_row_q4_0", &err), err));
+ CL_CHECK((dequantize_row_q4_1_cl = clCreateKernel(program, "dequantize_row_q4_1", &err), err));
+ CL_CHECK((dequantize_row_q5_0_cl = clCreateKernel(program, "dequantize_row_q5_0", &err), err));
+ CL_CHECK((dequantize_row_q5_1_cl = clCreateKernel(program, "dequantize_row_q5_1", &err), err));
+ CL_CHECK((dequantize_row_q8_0_cl = clCreateKernel(program, "dequantize_row_q8_0", &err), err));
+
+ // dequant mul mat kernel
+ CL_CHECK((dequantize_mul_mat_vec_q4_0_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q4_0", &err), err));
+ CL_CHECK((dequantize_mul_mat_vec_q4_1_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q4_1", &err), err));
+ CL_CHECK((dequantize_mul_mat_vec_q5_0_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q5_0", &err), err));
+ CL_CHECK((dequantize_mul_mat_vec_q5_1_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q5_1", &err), err));
+ CL_CHECK((dequantize_mul_mat_vec_q8_0_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q8_0", &err), err));
+ CL_CHECK((convert_mul_mat_vec_f16_cl = clCreateKernel(program, "convert_mul_mat_vec_f16", &err), err));
+}
+
+static cl_kernel* ggml_get_to_fp32_cl(ggml_type type) {
+ switch (type) {
+ case GGML_TYPE_Q4_0:
+ return &dequantize_row_q4_0_cl;
+ case GGML_TYPE_Q4_1:
+ return &dequantize_row_q4_1_cl;
+ case GGML_TYPE_Q5_0:
+ return &dequantize_row_q5_0_cl;
+ case GGML_TYPE_Q5_1:
+ return &dequantize_row_q5_1_cl;
+ case GGML_TYPE_Q8_0:
+ return &dequantize_row_q8_0_cl;
+ case GGML_TYPE_F16:
+ return &convert_row_f16_cl;
+ default:
+ return nullptr;
+ }
+}
+
+static cl_kernel* ggml_get_dequantize_mul_mat_vec_cl(ggml_type type) {
+ switch (type) {
+ case GGML_TYPE_Q4_0:
+ return &dequantize_mul_mat_vec_q4_0_cl;
+ case GGML_TYPE_Q4_1:
+ return &dequantize_mul_mat_vec_q4_1_cl;
+ case GGML_TYPE_Q5_0:
+ return &dequantize_mul_mat_vec_q5_0_cl;
+ case GGML_TYPE_Q5_1:
+ return &dequantize_mul_mat_vec_q5_1_cl;
+ case GGML_TYPE_Q8_0:
+ return &dequantize_mul_mat_vec_q8_0_cl;
+ case GGML_TYPE_F16:
+ return &convert_mul_mat_vec_f16_cl;
+ default:
+ return nullptr;
+ }
+}
+
+// buffer pool for cl
+#define MAX_CL_BUFFERS 256
+
+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 cl_buffer {
+ cl_mem mem;
+ size_t size = 0;
+};
+
+static cl_buffer g_cl_buffer_pool[MAX_CL_BUFFERS];
+static std::atomic_flag g_cl_pool_lock = ATOMIC_FLAG_INIT;
+
+static cl_mem ggml_cl_pool_malloc(size_t size, size_t * actual_size, cl_mem_flags flags) {
+ scoped_spin_lock lock(g_cl_pool_lock);
+ cl_int err;
+
+ for (int i = 0; i < MAX_CL_BUFFERS; ++i) {
+ cl_buffer& b = g_cl_buffer_pool[i];
+ if (b.size > 0 && b.size >= size) {
+ cl_mem mem = b.mem;
+ *actual_size = b.size;
+ b.size = 0;
+ return mem;
+ }
+ }
+ cl_mem mem;
+ CL_CHECK((mem = clCreateBuffer(context, flags, size, NULL, &err), err));
+ *actual_size = size;
+ return mem;
+}
+
+static void ggml_cl_pool_free(cl_mem mem, size_t size) {
+ scoped_spin_lock lock(g_cl_pool_lock);
+
+ for (int i = 0; i < MAX_CL_BUFFERS; ++i) {
+ cl_buffer& b = g_cl_buffer_pool[i];
+ if (b.size == 0) {
+ b.mem = mem;
+ b.size = size;
+ return;
+ }
+ }
+ fprintf(stderr, "WARNING: cl buffer pool full, increase MAX_CL_BUFFERS\n");
+ clReleaseMemObject(mem);
+}
+
+static cl_int ggml_cl_h2d_tensor_2d(cl_command_queue queue, cl_mem dst, size_t offset, const struct ggml_tensor * src, uint64_t i3, uint64_t i2, cl_event* ev) {
+ cl_int err;
+ 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) {
+ err = clEnqueueWriteBuffer(queue, dst, CL_FALSE, offset, ne1*nb1, x, 0, NULL, ev);
+ return err;
+ }
+ if (nb0 == ts) {
+ const size_t buffer_origin[3] = { offset, 0, 0 };
+ const size_t host_origin[3] = { 0, 0, 0 };
+ const size_t region[3] = { ts*ne0/bs, ne1, 1 };
+ err = clEnqueueWriteBufferRect(queue, dst, CL_FALSE, buffer_origin, host_origin, region, ts*ne0/bs, 0, nb1, 0, x, 0, NULL, ev);
+ return err;
+ }
+ for (uint64_t i1 = 0; i1 < ne1; i1++) {
+ // pretend the row is a matrix with cols=1
+ const size_t buffer_origin[3] = { offset, i1, 0 };
+ const size_t host_origin[3] = { 0, 0, 0 };
+ const size_t region[3] = { ts/bs, ne0, 1 };
+ err = clEnqueueWriteBufferRect(queue, dst, CL_FALSE, buffer_origin, host_origin, region, 0, 0, nb0, 0, ((const char *)x) + i1*nb0, 0, NULL, ev);
+ if (err != CL_SUCCESS) {
+ break;
+ }
+ }
+ return err;
+}
+
+static void ggml_cl_mul_mat_f32(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
+ const int64_t ne00 = src0->ne[0];
+ const int64_t ne01 = src0->ne[1];
+ const int64_t ne02 = src0->ne[2];
+ const int64_t ne03 = src0->ne[3];
+
+ const int64_t ne10 = src1->ne[0];
+ const int64_t ne11 = src1->ne[1];
+
+ const int nb2 = dst->nb[2];
+ const int nb3 = dst->nb[3];
+
+ const float alpha = 1.0f;
+ const float beta = 0.0f;
+ const int x_ne = ne01 * ne00;
+ const int y_ne = ne11 * ne10;
+ const int d_ne = ne11 * ne01;
+
+ size_t x_size;
+ size_t y_size;
+ size_t d_size;
+ cl_mem d_X;
+ if (src0->backend == GGML_BACKEND_CL) {
+ d_X = *(cl_mem*) src0->data;
+ } else {
+ d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size, CL_MEM_READ_ONLY);
+ }
+ cl_mem d_Y = ggml_cl_pool_malloc(sizeof(float) * y_ne, &y_size, CL_MEM_READ_ONLY);
+ cl_mem d_D = ggml_cl_pool_malloc(sizeof(float) * d_ne, &d_size, CL_MEM_WRITE_ONLY);
+
+ for (int64_t i03 = 0; i03 < ne03; i03++) {
+ for (int64_t i02 = 0; i02 < ne02; i02++) {
+ // copy data to device
+ if (src0->backend != GGML_BACKEND_CL) {
+ CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, 0, src0, i03, i02, NULL));
+ }
+ CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, NULL));
+
+ CL_CHECK(clFinish(queue));
+
+ // compute
+ cl_event ev_sgemm;
+ clblast::StatusCode status = clblast::Gemm<cl_float>(clblast::Layout::kColMajor,
+ clblast::Transpose::kYes, clblast::Transpose::kNo,
+ ne01, ne11, ne10,
+ alpha,
+ d_X, 0, ne00,
+ d_Y, 0, ne10,
+ beta,
+ d_D, 0, ne01,
+ &queue, &ev_sgemm);
+
+ if (status != clblast::StatusCode::kSuccess) {
+ GGML_ASSERT(false);
+ }
+
+ // copy dst to host
+ float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
+ CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(float) * d_ne, d, 1, &ev_sgemm, NULL));
+ }
+ }
+
+ if (src0->backend != GGML_BACKEND_CL) {
+ ggml_cl_pool_free(d_X, x_size);
+ }
+ ggml_cl_pool_free(d_Y, y_size);
+ ggml_cl_pool_free(d_D, d_size);
+}
+
+static void ggml_cl_mul_mat_f16(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, void * wdata, size_t /* wsize */) {
+ GGML_ASSERT(fp16_support);
+
+ const int64_t ne00 = src0->ne[0];
+ const int64_t ne01 = src0->ne[1];
+ const int64_t ne02 = src0->ne[2];
+ const int64_t ne03 = src0->ne[3];
+
+ const int64_t ne10 = src1->ne[0];
+ const int64_t ne11 = src1->ne[1];
+
+ const int nb10 = src1->nb[0];
+ const int nb11 = src1->nb[1];
+ const int nb12 = src1->nb[2];
+ const int nb13 = src1->nb[3];
+
+ const int nb2 = dst->nb[2];
+ const int nb3 = dst->nb[3];
+
+ const ggml_fp16_t alpha = ggml_fp32_to_fp16(1.0f);
+ const ggml_fp16_t beta = ggml_fp32_to_fp16(0.0f);
+ const int x_ne = ne01 * ne00;
+ const int y_ne = ne11 * ne10;
+ const int d_ne = ne11 * ne01;
+
+ size_t x_size;
+ size_t y_size;
+ size_t d_size;
+ cl_mem d_X;
+ if (src0->backend == GGML_BACKEND_CL) {
+ d_X = *(cl_mem*) src0->data;
+ } else {
+ d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size, CL_MEM_READ_ONLY);
+ }
+ cl_mem d_Y = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * y_ne, &y_size, CL_MEM_READ_ONLY);
+ cl_mem d_D = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * d_ne, &d_size, CL_MEM_WRITE_ONLY);
+
+ bool src1_cont_rows = nb10 == sizeof(float);
+ bool src1_cont_cols = (size_t)nb11 == ne11*sizeof(float);
+
+ for (int64_t i03 = 0; i03 < ne03; i03++) {
+ for (int64_t i02 = 0; i02 < ne02; i02++) {
+ // copy src0 to device
+ if (src0->backend != GGML_BACKEND_CL) {
+ CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, 0, src0, i03, i02, NULL));
+ }
+
+ // convert src1 to fp16
+ // TODO: use multiple threads
+ ggml_fp16_t * const tmp = (ggml_fp16_t *) wdata + (ne11 * ne10) * (i03 * ne02 + i02);
+ char * src1i = (char *) src1->data + i03*nb13 + i02*nb12;
+ if (src1_cont_rows) {
+ if (src1_cont_cols) {
+ ggml_fp32_to_fp16_row((float *) src1i, tmp, ne10*ne11);
+ }
+ else {
+ for (int64_t i01 = 0; i01 < ne11; i01++) {
+ ggml_fp32_to_fp16_row((float *) (src1i + i01*nb11), tmp + i01*ne10, ne10);
+ }
+ }
+ }
+ else {
+ for (int64_t i01 = 0; i01 < ne11; i01++) {
+ for (int64_t i00 = 0; i00 < ne10; i00++) {
+ // very slow due to no inlining
+ tmp[i01*ne10 + i00] = ggml_fp32_to_fp16(*(float *) (src1i + i01*nb11 + i00*nb10));
+ }
+ }
+ }
+
+ // copy src1 to device
+ CL_CHECK(clEnqueueWriteBuffer(queue, d_Y, false, 0, sizeof(ggml_fp16_t) * y_ne, tmp, 0, NULL, NULL));
+
+ CL_CHECK(clFinish(queue));
+
+ // compute
+ cl_event ev_sgemm;
+ clblast::StatusCode status = clblast::Gemm<cl_half>(clblast::Layout::kColMajor,
+ clblast::Transpose::kYes, clblast::Transpose::kNo,
+ ne01, ne11, ne10,
+ alpha,
+ d_X, 0, ne00,
+ d_Y, 0, ne10,
+ beta,
+ d_D, 0, ne01,
+ &queue, &ev_sgemm);
+
+ if (status != clblast::StatusCode::kSuccess) {
+ GGML_ASSERT(false);
+ }
+
+ // copy dst to host, then convert to float
+ CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(ggml_fp16_t) * d_ne, tmp, 1, &ev_sgemm, NULL));
+
+ float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
+
+ ggml_fp16_to_fp32_row(tmp, d, d_ne);
+ }
+ }
+
+ if (src0->backend != GGML_BACKEND_CL) {
+ ggml_cl_pool_free(d_X, x_size);
+ }
+ ggml_cl_pool_free(d_Y, y_size);
+ ggml_cl_pool_free(d_D, d_size);
+}
+
+static void ggml_cl_mul_mat_q_f32(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
+ const int64_t ne00 = src0->ne[0];
+ const int64_t ne01 = src0->ne[1];
+ const int64_t ne02 = src0->ne[2];
+ const int64_t ne03 = src0->ne[3];
+
+ const int64_t ne10 = src1->ne[0];
+ const int64_t ne11 = src1->ne[1];
+
+ const int nb2 = dst->nb[2];
+ const int nb3 = dst->nb[3];
+ const ggml_type type = src0->type;
+ const bool mul_mat_vec = ne11 == 1;
+
+ const float alpha = 1.0f;
+ const float beta = 0.0f;
+ const int x_ne = ne01 * ne00;
+ const int y_ne = ne11 * ne10;
+ const int d_ne = ne11 * ne01;
+ const size_t q_sz = ggml_type_size(type) * x_ne / ggml_blck_size(type);
+
+ size_t x_size;
+ size_t y_size;
+ size_t d_size;
+ size_t q_size;
+ cl_mem d_X;
+ if (!mul_mat_vec) {
+ d_X = ggml_cl_pool_malloc(sizeof(float) * x_ne, &x_size, CL_MEM_READ_WRITE);
+ }
+ cl_mem d_Y = ggml_cl_pool_malloc(sizeof(float) * y_ne, &y_size, CL_MEM_READ_ONLY);
+ cl_mem d_D = ggml_cl_pool_malloc(sizeof(float) * d_ne, &d_size, CL_MEM_WRITE_ONLY);
+ cl_mem d_Q;
+ if (src0->backend == GGML_BACKEND_CPU) {
+ d_Q = ggml_cl_pool_malloc(q_sz, &q_size, CL_MEM_READ_ONLY);
+ }
+
+ cl_kernel* to_fp32_cl = ggml_get_to_fp32_cl(type);
+ cl_kernel* dmmv = ggml_get_dequantize_mul_mat_vec_cl(type);
+ GGML_ASSERT(to_fp32_cl != nullptr);
+
+ for (int64_t i03 = 0; i03 < ne03; i03++) {
+ for (int64_t i02 = 0; i02 < ne02; i02++) {
+ cl_event ev_sgemm;
+
+ // copy src0 to device if necessary
+ if (src0->backend == GGML_BACKEND_CPU) {
+ CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Q, 0, src0, i03, i02, NULL));
+ } else if (src0->backend == GGML_BACKEND_CL) {
+ d_Q = *(cl_mem*) src0->data;
+ } else {
+ GGML_ASSERT(false);
+ }
+ if (mul_mat_vec) { // specialized dequantize_mul_mat_vec kernel
+ // copy src1 to device
+ CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, NULL));
+
+ // compute
+ const size_t global = ne01 * CL_DMMV_BLOCK_SIZE;
+ const size_t local = CL_DMMV_BLOCK_SIZE;
+ const cl_int ncols = ne00;
+ CL_CHECK(clSetKernelArg(*dmmv, 0, sizeof(cl_mem), &d_Q));
+ CL_CHECK(clSetKernelArg(*dmmv, 1, sizeof(float) * local, NULL));
+ CL_CHECK(clSetKernelArg(*dmmv, 2, sizeof(cl_mem), &d_Y));
+ CL_CHECK(clSetKernelArg(*dmmv, 3, sizeof(cl_mem), &d_D));
+ CL_CHECK(clSetKernelArg(*dmmv, 4, sizeof(cl_int), &ncols));
+ CL_CHECK(clFinish(queue));
+ CL_CHECK(clEnqueueNDRangeKernel(queue, *dmmv, 1, NULL, &global, &local, 0, NULL, &ev_sgemm));
+ } else { // general dequantization kernel + CLBlast matrix matrix multiplication
+ // convert src0 to fp32 on device
+ const size_t global = x_ne;
+ CL_CHECK(clSetKernelArg(*to_fp32_cl, 0, sizeof(cl_mem), &d_Q));
+ CL_CHECK(clSetKernelArg(*to_fp32_cl, 1, sizeof(cl_mem), &d_X));
+ CL_CHECK(clFinish(queue));
+ CL_CHECK(clEnqueueNDRangeKernel(queue, *to_fp32_cl, 1, NULL, &global, NULL, 0, NULL, NULL));
+
+ // copy src1 to device
+ CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, NULL));
+
+ // wait for conversion
+ CL_CHECK(clFinish(queue));
+
+ // compute
+ clblast::StatusCode status = clblast::Gemm<cl_float>(clblast::Layout::kColMajor,
+ clblast::Transpose::kYes, clblast::Transpose::kNo,
+ ne01, ne11, ne10,
+ alpha,
+ d_X, 0, ne00,
+ d_Y, 0, ne10,
+ beta,
+ d_D, 0, ne01,
+ &queue, &ev_sgemm);
+
+ if (status != clblast::StatusCode::kSuccess) {
+ GGML_ASSERT(false);
+ }
+ }
+
+ // copy dst to host
+ float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
+ CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(float) * d_ne, d, 1, &ev_sgemm, NULL));
+ clReleaseEvent(ev_sgemm);
+ }
+ }
+
+ if (!mul_mat_vec) {
+ ggml_cl_pool_free(d_X, x_size);
+ }
+ ggml_cl_pool_free(d_Y, y_size);
+ ggml_cl_pool_free(d_D, d_size);
+ if (src0->backend == GGML_BACKEND_CPU) {
+ ggml_cl_pool_free(d_Q, q_size);
+ }
+}
+
+
+bool ggml_cl_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) {
+ const int64_t ne10 = src1->ne[0];
+
+ const int64_t ne0 = dst->ne[0];
+ const int64_t ne1 = dst->ne[1];
+
+ // TODO: find the optimal values for these
+ if ((src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16 || ggml_is_quantized(src0->type)) &&
+ src1->type == GGML_TYPE_F32 &&
+ dst->type == GGML_TYPE_F32 &&
+ ((ne0 >= 32 && ne1 >= 32 && ne10 >= 32) || src0->backend == GGML_BACKEND_CL)) {
+ return true;
+ }
+
+ return false;
+}
+
+bool ggml_cl_mul_mat_use_f16(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * /* dst */) {
+ // If device doesn't support FP16
+ if (!fp16_support) {
+ return false;
+ }
+
+ size_t src0_sz = ggml_nbytes(src0);
+ size_t src1_sz = ggml_nbytes(src1);
+
+ // mul_mat_q: src0 is converted to fp32 on device
+ size_t mul_mat_q_transfer = src0_sz + src1_sz;
+
+ // mul_mat_f16: src1 is converted to fp16 on cpu
+ size_t mul_mat_f16_transfer = src0_sz + sizeof(ggml_fp16_t) * ggml_nelements(src1);
+
+ // choose the smaller one to transfer to the device
+ // TODO: this is not always the best choice due to the overhead of converting to fp16
+ return mul_mat_f16_transfer < mul_mat_q_transfer;
+}
+
+void ggml_cl_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst, void * wdata, size_t wsize) {
+ GGML_ASSERT(ggml_cl_can_mul_mat(src0, src1, dst));
+
+ if (src0->type == GGML_TYPE_F32) {
+ ggml_cl_mul_mat_f32(src0, src1, dst);
+ }
+ else if (src0->type == GGML_TYPE_F16) {
+ if (ggml_cl_mul_mat_use_f16(src0, src1, dst)) {
+ ggml_cl_mul_mat_f16(src0, src1, dst, wdata, wsize);
+ }
+ else {
+ ggml_cl_mul_mat_q_f32(src0, src1, dst);
+ }
+ }
+ else if (ggml_is_quantized(src0->type)) {
+ ggml_cl_mul_mat_q_f32(src0, src1, dst);
+ }
+ else {
+ GGML_ASSERT(false);
+ }
+}
+
+size_t ggml_cl_mul_mat_get_wsize(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) {
+ if (ggml_cl_mul_mat_use_f16(src0, src1, dst)) {
+ return ggml_nelements(src1) * sizeof(ggml_fp16_t);
+ }
+ return 0;
+}
+
+void ggml_cl_transform_tensor(ggml_tensor * tensor) {
+ const int64_t ne0 = tensor->ne[0];
+ const int64_t ne1 = tensor->ne[1];
+ const int64_t ne2 = tensor->ne[2];
+ const int64_t ne3 = tensor->ne[3];
+
+ const ggml_type type = tensor->type;
+ const size_t q_sz = ggml_type_size(type) * ne0 * ne1 * ne2 * ne3 / ggml_blck_size(type);
+
+ size_t q_size;
+ cl_mem* dst = (cl_mem*) malloc(sizeof(cl_mem));
+ *dst = ggml_cl_pool_malloc(q_sz, &q_size, CL_MEM_READ_ONLY);
+
+ // copy tensor to device
+ for (int64_t i3 = 0; i3 < ne3; i3++) {
+ for (int64_t i2 = 0; i2 < ne2; i2++) {
+ int i = i3*ne2 + i2;
+ CL_CHECK(ggml_cl_h2d_tensor_2d(queue, *dst, i*ne0*ne1, tensor, i3, i2, NULL));
+ }
+ }
+
+ CL_CHECK(clFinish(queue));
+
+ tensor->data = dst;
+ tensor->backend = GGML_BACKEND_CL;
+}
diff --git a/ggml-opencl.h b/ggml-opencl.h
index 7bcc603..5a1a500 100644
--- a/ggml-opencl.h
+++ b/ggml-opencl.h
@@ -1,23 +1,21 @@
#pragma once
+#include "ggml.h"
+
#ifdef __cplusplus
extern "C" {
#endif
void ggml_cl_init(void);
-enum ggml_blas_order {
- GGML_BLAS_ORDER_ROW_MAJOR = 101,
- GGML_BLAS_ORDER_COLUMN_MAJOR = 102,
-};
+bool ggml_cl_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
+size_t ggml_cl_mul_mat_get_wsize(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst);
+void ggml_cl_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst, void * wdata, size_t wsize);
-enum ggml_blas_op {
- GGML_BLAS_OP_N = 111,
- GGML_BLAS_OP_T = 112,
- GGML_BLAS_OP_C = 113,
-};
+void * ggml_cl_host_malloc(size_t size);
+void ggml_cl_host_free(void * ptr);
-void ggml_cl_sgemm_wrapper(const enum ggml_blas_order order, const enum ggml_blas_op trans_a, const enum ggml_blas_op trans_b, const int m, const int n, const int k, const float alpha, const void *host_a, const int lda, const float *host_b, const int ldb, const float beta, float *host_c, const int ldc, const int btype);
+void ggml_cl_transform_tensor(struct ggml_tensor * tensor);
#ifdef __cplusplus
}
diff --git a/ggml.c b/ggml.c
index d36bb22..c0e7ec0 100644
--- a/ggml.c
+++ b/ggml.c
@@ -9431,7 +9431,7 @@ static void ggml_compute_forward_rms_norm_back(
// ggml_compute_forward_mul_mat
-#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
// helper function to determine if it is better to use BLAS or not
// for large matrices, BLAS is faster
static bool ggml_compute_forward_mul_mat_use_blas(
@@ -9472,7 +9472,7 @@ static void ggml_compute_forward_mul_mat_f32(
const int64_t ne02 = src0->ne[2];
const int64_t ne03 = src0->ne[3];
-#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
const int64_t ne10 = src1->ne[0];
#endif
const int64_t ne11 = src1->ne[1];
@@ -9536,9 +9536,16 @@ static void ggml_compute_forward_mul_mat_f32(
}
return;
}
+#elif defined(GGML_USE_CLBLAST)
+ if (ggml_cl_can_mul_mat(src0, src1, dst)) {
+ if (params->ith == 0 && params->type == GGML_TASK_COMPUTE) {
+ ggml_cl_mul_mat(src0, src1, dst, params->wdata, params->wsize);
+ }
+ return;
+ }
#endif
-#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
if (ggml_compute_forward_mul_mat_use_blas(src0, src1, dst)) {
if (params->ith != 0) {
return;
@@ -9558,21 +9565,11 @@ static void ggml_compute_forward_mul_mat_f32(
const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
-#if defined(GGML_USE_CLBLAST)
- // zT = y * xT
- ggml_cl_sgemm_wrapper(GGML_BLAS_ORDER_ROW_MAJOR, GGML_BLAS_OP_N, GGML_BLAS_OP_T,
- ne11, ne01, ne10,
- 1.0f, y, ne10,
- x, ne10,
- 0.0f, d, ne01,
- GGML_TYPE_F32);
-#else
cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasTrans,
ne11, ne01, ne10,
1.0f, y, ne10,
x, ne00,
0.0f, d, ne01);
-#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);
@@ -9711,9 +9708,16 @@ static void ggml_compute_forward_mul_mat_f16_f32(
}
return;
}
+#elif defined(GGML_USE_CLBLAST)
+ if (ggml_cl_can_mul_mat(src0, src1, dst)) {
+ if (params->ith == 0 && params->type == GGML_TASK_COMPUTE) {
+ ggml_cl_mul_mat(src0, src1, dst, params->wdata, params->wsize);
+ }
+ return;
+ }
#endif
-#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
if (ggml_compute_forward_mul_mat_use_blas(src0, src1, dst)) {
GGML_ASSERT(nb10 == sizeof(float));
@@ -9743,20 +9747,6 @@ static void ggml_compute_forward_mul_mat_f16_f32(
assert(id*sizeof(float) <= params->wsize);
}
-#if defined(GGML_USE_CLBLAST)
- const float * x = wdata;
- const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
-
- float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
-
- // zT = y * xT
- ggml_cl_sgemm_wrapper(GGML_BLAS_ORDER_ROW_MAJOR, GGML_BLAS_OP_N, GGML_BLAS_OP_T,
- ne11, ne01, ne10,
- 1.0f, y, ne10,
- x, ne10,
- 0.0f, d, ne01,
- GGML_TYPE_F32);
-#else
const float * x = wdata;
const float * y = (float *) ((char *) src1->data + i02*nb12 + i03*nb13);
@@ -9768,7 +9758,6 @@ static void ggml_compute_forward_mul_mat_f16_f32(
1.0f, y, ne10,
x, ne00,
0.0f, d, ne01);
-#endif
}
}
@@ -9931,9 +9920,16 @@ static void ggml_compute_forward_mul_mat_q_f32(
}
return;
}
+#elif defined(GGML_USE_CLBLAST)
+ if (ggml_cl_can_mul_mat(src0, src1, dst)) {
+ if (params->ith == 0 && params->type == GGML_TASK_COMPUTE) {
+ ggml_cl_mul_mat(src0, src1, dst, params->wdata, params->wsize);
+ }
+ return;
+ }
#endif
-#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
if (ggml_compute_forward_mul_mat_use_blas(src0, src1, dst)) {
if (params->ith != 0) {
return;
@@ -9956,9 +9952,6 @@ static void ggml_compute_forward_mul_mat_q_f32(
float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
-#if defined(GGML_USE_CLBLAST)
- const void* x = (char *) src0->data + i03*nb03 + i02*nb02;
-#else
{
size_t id = 0;
for (int64_t i01 = 0; i01 < ne01; ++i01) {
@@ -9970,23 +9963,12 @@ static void ggml_compute_forward_mul_mat_q_f32(
}
const float * x = wdata;
-#endif
-#if defined(GGML_USE_CLBLAST)
- // zT = y * xT
- ggml_cl_sgemm_wrapper(GGML_BLAS_ORDER_ROW_MAJOR, GGML_BLAS_OP_N, GGML_BLAS_OP_T,
- ne11, ne01, ne10,
- 1.0f, y, ne10,
- x, ne10,
- 0.0f, d, ne01,
- type);
-#else
cblas_sgemm(CblasRowMajor, CblasNoTrans, CblasTrans,
ne11, ne01, ne10,
1.0f, y, ne10,
x, ne00,
0.0f, d, ne01);
-#endif
}
}
@@ -14165,9 +14147,16 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
cur = ggml_cuda_mul_mat_get_wsize(node->src0, node->src1, node);
}
else
+#elif defined(GGML_USE_CLBLAST)
+ if (ggml_cl_can_mul_mat(node->src0, node->src1, node)) {
+ node->n_tasks = 1; // TODO: this actually is doing nothing
+ // the threads are still spinning
+ cur = ggml_cl_mul_mat_get_wsize(node->src0, node->src1, node);
+ }
+ else
#endif
if (node->src0->type == GGML_TYPE_F16 && node->src1->type == GGML_TYPE_F32) {
-#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
if (ggml_compute_forward_mul_mat_use_blas(node->src0, node->src1, node)) {
node->n_tasks = 1; // TODO: this actually is doing nothing
// the threads are still spinning
@@ -14181,13 +14170,13 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
#endif
} else if (node->src0->type == GGML_TYPE_F32 && node->src1->type == GGML_TYPE_F32) {
cur = 0;
-#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
if (ggml_compute_forward_mul_mat_use_blas(node->src0, node->src1, node)) {
node->n_tasks = 1;
}
#endif
} else if (ggml_is_quantized(node->src0->type) && node->src1->type == GGML_TYPE_F32) {
-#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS) || defined(GGML_USE_CLBLAST)
+#if defined(GGML_USE_ACCELERATE) || defined(GGML_USE_OPENBLAS)
if (ggml_compute_forward_mul_mat_use_blas(node->src0, node->src1, node)) {
node->n_tasks = 1;
cur = GGML_TYPE_SIZE[GGML_TYPE_F32]*(node->src0->ne[0]*node->src0->ne[1]);
diff --git a/ggml.h b/ggml.h
index 51a616c..c22d938 100644
--- a/ggml.h
+++ b/ggml.h
@@ -249,6 +249,7 @@ extern "C" {
enum ggml_backend {
GGML_BACKEND_CPU = 0,
GGML_BACKEND_CUDA = 1,
+ GGML_BACKEND_CL = 2,
};
// model file types
diff --git a/llama.cpp b/llama.cpp
index 4cbc8d6..5a19316 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -12,6 +12,8 @@
#include "ggml.h"
#ifdef GGML_USE_CUBLAS
#include "ggml-cuda.h"
+#elif defined(GGML_USE_CLBLAST)
+#include "ggml-opencl.h"
#endif
#include <array>
@@ -1092,7 +1094,7 @@ static void llama_model_load_internal(
fprintf(stderr, "%s: [cublas] offloading output layer to GPU\n", __func__);
}
fprintf(stderr, "%s: [cublas] total VRAM used: %zu MB\n", __func__, vram_total / 1024 / 1024);
-#else
+#elif !defined(GGML_USE_CLBLAST)
(void) n_gpu_layers;
#endif
}
@@ -1125,7 +1127,33 @@ static void llama_model_load_internal(
done_size += lt.size;
}
}
-#endif // GGML_USE_CUBLAS
+#elif defined(GGML_USE_CLBLAST)
+ {
+ const int n_gpu = std::min(n_gpu_layers, int(hparams.n_layer));
+
+ fprintf(stderr, "ggml_opencl: offloading %d layers to GPU\n", n_gpu);
+
+ size_t vram_total = 0;
+
+ for (int i = 0; i < n_gpu; ++i) {
+ const auto & layer = model.layers[i];
+
+ ggml_cl_transform_tensor(layer.wq); vram_total += ggml_nbytes(layer.wq);
+ ggml_cl_transform_tensor(layer.wk); vram_total += ggml_nbytes(layer.wk);
+ ggml_cl_transform_tensor(layer.wv); vram_total += ggml_nbytes(layer.wv);
+ ggml_cl_transform_tensor(layer.wo); vram_total += ggml_nbytes(layer.wo);
+ ggml_cl_transform_tensor(layer.w1); vram_total += ggml_nbytes(layer.w1);
+ ggml_cl_transform_tensor(layer.w2); vram_total += ggml_nbytes(layer.w2);
+ ggml_cl_transform_tensor(layer.w3); vram_total += ggml_nbytes(layer.w3);
+ }
+ if (n_gpu_layers > (int) hparams.n_layer) {
+ fprintf(stderr, "ggml_opencl: offloading output layer to GPU\n");
+ ggml_cl_transform_tensor(model.output); vram_total += ggml_nbytes(model.output);
+ }
+
+ fprintf(stderr, "ggml_opencl: total VRAM used: %zu MB\n", vram_total / 1024 / 1024);
+ }
+#endif
if (progress_callback) {
progress_callback(1.0f, progress_callback_user_data);
generated by cgit v1.2.3 (git 2.25.1) at 2024-10-18 14:24:43 +0000