diff --git a/CMakeLists.txt b/CMakeLists.txt index 60eb027..db5d347 100644 --- a/CMakeLists.txt +++ b/CMakeLists.txt @@ -182,7 +182,7 @@ if (WHISPER_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 95fae0d..73e1c5f 100644 --- a/Makefile +++ b/Makefile @@ -175,8 +175,8 @@ ifdef WHISPER_CLBLAST CFLAGS += -DGGML_USE_CLBLAST LDFLAGS += -lclblast -lOpenCL WHISPER_OBJ += ggml-opencl.o - -ggml-opencl.o: ggml-opencl.c ggml-opencl.h + +ggml-opencl.o: ggml-opencl.cpp ggml-opencl.h $(CC) $(CFLAGS) -c $< -o $@ endif diff --git a/extra/sync-ggml.sh b/extra/sync-ggml.sh index db5c1cf..e242ea7 100755 --- a/extra/sync-ggml.sh +++ b/extra/sync-ggml.sh @@ -4,7 +4,7 @@ cp -rpv ../ggml/src/ggml.c ./ggml.c cp -rpv ../ggml/src/ggml-cuda.h ./ggml-cuda.h cp -rpv ../ggml/src/ggml-cuda.cu ./ggml-cuda.cu cp -rpv ../ggml/src/ggml-opencl.h ./ggml-opencl.h -cp -rpv ../ggml/src/ggml-opencl.c ./ggml-opencl.c +cp -rpv ../ggml/src/ggml-opencl.cpp ./ggml-opencl.cpp cp -rpv ../ggml/include/ggml/ggml.h ./ggml.h cp -rpv ../ggml/examples/common.h ./examples/common.h cp -rpv ../ggml/examples/common.cpp ./examples/common.cpp diff --git a/ggml-opencl.c b/ggml-opencl.c deleted file mode 100644 index 31ab13b..0000000 --- a/ggml-opencl.c +++ /dev/null @@ -1,361 +0,0 @@ -#include "ggml-opencl.h" - -#define CL_TARGET_OPENCL_VERSION 110 -#include - -#include -#include -#include - -#include "ggml.h" - -#define MULTILINE_QUOTE(...) #__VA_ARGS__ -const char * clblast_dequant = MULTILINE_QUOTE( - -typedef uchar uint8_t; -typedef int int32_t; -typedef uint uint32_t; - -constant uint QK4_0 = 32; -struct block_q4_0 -{ - float d; - uint8_t qs[QK4_0 / 2]; -}; - -constant uint QK4_1 = 32; -struct block_q4_1 -{ - float d; - float m; - uint8_t qs[QK4_1 / 2]; -}; - -constant uint QK5_0 = 32; -struct __attribute__ ((packed)) block_q5_0 -{ - half d; - uint32_t qh; - uint8_t qs[QK5_0 / 2]; -}; - -constant uint QK5_1 = 32; -struct block_q5_1 -{ - half d; - half m; - uint32_t qh; - uint8_t qs[QK5_1 / 2]; -}; - -constant uint QK8_0 = 32; -struct block_q8_0 -{ - float d; - uint8_t qs[QK8_0]; -}; - - -__kernel void dequantize_row_q4_0(__global struct block_q4_0* x, __global float* y) { - constant uint qk = QK4_0; - - const uint i = get_global_id(0) / qk; - const uint j = get_local_id(0); - - const float d = x[i].d; - - const int x0 = (x[i].qs[j] & 0xf) - 8; - const int x1 = (x[i].qs[j] >> 4) - 8; - - y[i*qk + j + 0 ] = x0*d; - y[i*qk + j + qk/2] = x1*d; -} - -__kernel void dequantize_row_q4_1(__global struct block_q4_1* x, __global float* y) { - constant uint qk = QK4_1; - - const uint i = get_global_id(0) / qk; - const uint j = get_local_id(0); - - const float d = x[i].d; - const float m = x[i].m; - - const int x0 = (x[i].qs[j] & 0xf); - const int x1 = (x[i].qs[j] >> 4); - - y[i*qk + j + 0 ] = x0*d + m; - y[i*qk + j + qk/2] = x1*d + m; -} - -__kernel void dequantize_row_q5_0(__global struct block_q5_0* x, __global float* y) { - constant uint qk = QK5_0; - - const uint i = get_global_id(0) / qk; - 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*qk + j + 0 ] = x0*d; - y[i*qk + j + qk/2] = x1*d; -} - -__kernel void dequantize_row_q5_1(__global struct block_q5_1* x, __global float* y) { - constant uint qk = QK5_1; - - const uint i = get_global_id(0) / qk; - 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*qk + j + 0 ] = x0*d + m; - y[i*qk + j + qk/2] = x1*d + m; -} - -__kernel void dequantize_row_q8_0(__global struct block_q8_0* x, __global float* y) { - constant uint qk = QK8_0; - const uint i = get_global_id(0) / qk; - const uint j = get_local_id(0); - - const float d = x[i].d; - y[i*qk + j] = x[i].qs[j]*d; -} - -); - -#define CL_CHECK(err, name) \ - do { \ - cl_int err_ = (err); \ - if (err_ != CL_SUCCESS) { \ - fprintf(stderr, "OpenCL %s error %d at %s:%d\n", name, 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; - char * GGML_CLBLAST_PLATFORM = getenv("GGML_CLBLAST_PLATFORM"); - char * GGML_CLBLAST_DEVICE = getenv("GGML_CLBLAST_DEVICE"); - int plat_num = (GGML_CLBLAST_PLATFORM == NULL ? 0 : atoi(GGML_CLBLAST_PLATFORM)); - int dev_num = (GGML_CLBLAST_DEVICE == NULL ? 0 : atoi(GGML_CLBLAST_DEVICE)); - printf("\nInitializing CLBlast (First Run)..."); - printf("\nAttempting to use: Platform=%d, Device=%d (If invalid, program will crash)\n",plat_num,dev_num); - cl_uint num_platforms; - clGetPlatformIDs(0, NULL, &num_platforms); - cl_platform_id* platforms = (cl_platform_id*)malloc(num_platforms*sizeof(cl_platform_id)); - clGetPlatformIDs(num_platforms, platforms, NULL); - platform = platforms[plat_num]; - char platform_buffer[1024]; - clGetPlatformInfo(platform, CL_PLATFORM_NAME, sizeof(platform_buffer), &platform_buffer, NULL); - cl_uint num_devices; - clGetDeviceIDs(platform, CL_DEVICE_TYPE_ALL, 0, NULL, &num_devices); - cl_device_id* devices = (cl_device_id*)malloc(num_devices*sizeof(cl_device_id)); - clGetDeviceIDs(platform, CL_DEVICE_TYPE_ALL, num_devices, devices, NULL); - device = devices[dev_num]; - char device_buffer[1024]; - clGetDeviceInfo(device, CL_DEVICE_NAME, sizeof(device_buffer), &device_buffer, NULL); - printf("Using Platform: %s Device: %s\n", platform_buffer, device_buffer); - context = clCreateContext(NULL, 1, &device, NULL, NULL, &err); - CL_CHECK(err, "clCreateContext"); - queue = clCreateCommandQueue(context, device, CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE, &err); - CL_CHECK(err, "clCreateCommandQueue"); - - free(platforms); - free(devices); - - program = build_program_from_source(context, device, clblast_dequant); - - // Prepare dequantize kernels - kernel_q4_0 = clCreateKernel(program, "dequantize_row_q4_0", &err); - CL_CHECK(err, "clCreateKernel"); - kernel_q4_1 = clCreateKernel(program, "dequantize_row_q4_1", &err); - CL_CHECK(err, "clCreateKernel"); - kernel_q5_0 = clCreateKernel(program, "dequantize_row_q5_0", &err); - CL_CHECK(err, "clCreateKernel"); - kernel_q5_1 = clCreateKernel(program, "dequantize_row_q5_1", &err); - CL_CHECK(err, "clCreateKernel"); - kernel_q8_0 = clCreateKernel(program, "dequantize_row_q8_0", &err); - CL_CHECK(err, "clCreateKernel"); -} - -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; - *buf = clCreateBuffer(context, flags, req_size, NULL, &err); - *cur_size = req_size; - CL_CHECK(err, "clCreateBuffer"); -} - -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_int err = 0; - - 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(float) + local) / 32; - break; - case GGML_TYPE_Q4_1: - dequant = true; - kernel = kernel_q4_1; - local = 16; - size_qb = global * (sizeof(float) * 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(float) + 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) { - err = clSetKernelArg(kernel, 0, sizeof(cl_mem), &cl_buffer_qb); - err |= clSetKernelArg(kernel, 1, sizeof(cl_mem), &cl_buffer_b); - CL_CHECK(err, "clSetKernelArg"); - err = clEnqueueWriteBuffer(queue, cl_buffer_qb, CL_FALSE, 0, size_qb, host_b, 0, NULL, &ev_qb); - CL_CHECK(err, "clEnqueueWriteBuffer qb"); - } else { - err = clEnqueueWriteBuffer(queue, cl_buffer_b, CL_FALSE, 0, size_b, host_b, 0, NULL, &ev_b); - CL_CHECK(err, "clEnqueueWriteBuffer b"); - } - - err = clEnqueueWriteBuffer(queue, cl_buffer_a, CL_FALSE, 0, size_a, host_a, 0, NULL, &ev_a); - CL_CHECK(err, "clEnqueueWriteBuffer a"); - if (dequant) { - err = clEnqueueNDRangeKernel(queue, kernel, 1, NULL, &global, &local, 1, &ev_qb, &ev_b); - CL_CHECK(err, "clEnqueueNDRangeKernel"); - clReleaseEvent(ev_qb); - } - clWaitForEvents(1, &ev_a); - clWaitForEvents(1, &ev_b); - clReleaseEvent(ev_a); - clReleaseEvent(ev_b); - - cl_event ev_sgemm; - CLBlastStatusCode status = 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); - - if (status != CLBlastSuccess) { - fprintf(stderr, "Error: CLBlast SGEMM %d\n", status); - abort(); - } - - cl_event ev_c; - clEnqueueReadBuffer(queue, cl_buffer_c, CL_TRUE, 0, size_c, host_c, 1, &ev_sgemm, &ev_c); - - // Wait for completion - clWaitForEvents(1, &ev_c); - clReleaseEvent(ev_sgemm); - clReleaseEvent(ev_c); -} diff --git a/ggml-opencl.cpp b/ggml-opencl.cpp new file mode 100644 index 0000000..95f4cec --- /dev/null +++ b/ggml-opencl.cpp @@ -0,0 +1,1684 @@ +#include "ggml-opencl.h" + +#include +#include +#include +#include +#include + +#define CL_TARGET_OPENCL_VERSION 110 +#include + +#include +#include +#include + +#include "ggml.h" + +#if defined(_MSC_VER) +#pragma warning(disable: 4244 4267) // possible loss of data +#endif + +#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]; +}; + +struct __attribute__((packed)) block_q2_K +{ + uint8_t scales[16]; + uint8_t qs[64]; + half d; + half dmin; +}; + +struct __attribute__((packed)) block_q3_K +{ + uint8_t hmask[32]; + uint8_t qs[64]; + uint8_t scales[12]; + half d; +}; + +struct __attribute__((packed)) block_q4_K +{ + half d; + half dmin; + uint8_t scales[12]; + uint8_t qs[128]; +}; + +struct __attribute__((packed)) block_q5_K +{ + half d; + half dmin; + uint8_t scales[12]; + uint8_t qh[32]; + uint8_t qs[128]; +}; + +struct __attribute__((packed)) block_q6_K +{ + uint8_t ql[128]; + uint8_t qh[64]; + int8_t scales[16]; + half d; +}; + +__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]); +} + +inline void get_scale_min_k4(int j, const __global uint8_t *q, uint8_t *d, uint8_t *m) +{ + if (j < 4) + { + *d = q[j] & 63; + *m = q[j + 4] & 63; + } + else + { + *d = (q[j + 4] & 0xF) | ((q[j - 4] >> 6) << 4); + *m = (q[j + 4] >> 4) | ((q[j - 0] >> 6) << 4); + } +} + +__kernel void dequantize_block_q2_K(__global const struct block_q2_K *x, __global float *yy) +{ + const int i = get_group_id(0); + const int tid = get_local_id(0); + const int n = tid / 32; + const int l = tid - 32 * n; + const int is = 8 * n + l / 16; + + const uint8_t q = x[i].qs[32 * n + l]; + __global float *y = yy + i * 256 + 128 * n; + + const float dall = vload_half(0, &x[i].d); + const float dmin = vload_half(0, &x[i].dmin); + + y[l + 0] = dall * (x[i].scales[is + 0] & 0xF) * ((q >> 0) & 3) - dmin * (x[i].scales[is + 0] >> 4); + 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); +} + +__kernel void dequantize_block_q3_K(__global const struct block_q3_K *x, __global float *yy) +{ + int r = get_local_id(0) / 4; + int i = get_group_id(0); + int tid = r / 2; + int is0 = r % 2; + int l0 = 16 * is0 + 4 * (get_local_id(0) % 4); + int n = tid / 4; + int j = tid - 4 * n; + + uint8_t m = 1 << (4 * n + j); + int is = 8 * n + 2 * j + is0; + int shift = 2 * j; + + int8_t us = is < 4 ? (x[i].scales[is - 0] & 0xF) | (((x[i].scales[is + 8] >> 0) & 3) << 4) + : is < 8 ? (x[i].scales[is - 0] & 0xF) | (((x[i].scales[is + 4] >> 2) & 3) << 4) + : is < 12 ? (x[i].scales[is - 8] >> 4) | (((x[i].scales[is + 0] >> 4) & 3) << 4) + : (x[i].scales[is - 8] >> 4) | (((x[i].scales[is - 4] >> 6) & 3) << 4); + float d_all = vload_half(0, &x[i].d); + float dl = d_all * (us - 32); + + __global float *y = yy + i * 256 + 128 * n + 32 * j; + const __global uint8_t *q = x[i].qs + 32 * n; + const __global 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)); +} + +__kernel void dequantize_block_q4_K(__global const struct block_q4_K *x, __global float *yy) +{ + const int i = get_group_id(0); + const int tid = get_local_id(0); + const int il = tid / 8; + const int ir = tid % 8; + const int is = 2 * il; + const int n = 4; + + __global float *y = yy + i * 256 + 64 * il + n * ir; + + const float dall = vload_half(0, &x[i].d); + const float dmin = vload_half(0, &x[i].dmin); + + __global const uint8_t *q = x[i].qs + 32 * il + n * ir; + + uint8_t sc, m; + get_scale_min_k4(is + 0, x[i].scales, &sc, &m); + float d1 = dall * sc; + float m1 = dmin * m; + get_scale_min_k4(is + 1, x[i].scales, &sc, &m); + float d2 = dall * sc; + float m2 = dmin * m; + for (int l = 0; l < n; ++l) + { + y[l + 0] = d1 * (q[l] & 0xF) - m1; + y[l + 32] = d2 * (q[l] >> 4) - m2; + } +} + +__kernel void dequantize_block_q5_K(__global const struct block_q5_K *x, __global float *yy) +{ + const int i = get_group_id(0); + const int tid = get_local_id(0); + const int il = tid / 16; + const int ir = tid % 16; + const int is = 2 * il; + + __global float *y = yy + i * 256 + 64 * il + 2 * ir; + + const float dall = vload_half(0, &x[i].d); + const float dmin = vload_half(0, &x[i].dmin); + + __global const uint8_t *ql = x[i].qs + 32 * il + 2 * ir; + __global const uint8_t *qh = x[i].qh + 2 * ir; + + uint8_t sc, m; + get_scale_min_k4(is + 0, x[i].scales, &sc, &m); + const float d1 = dall * sc; + const float m1 = dmin * m; + get_scale_min_k4(is + 1, x[i].scales, &sc, &m); + const float d2 = dall * sc; + const float m2 = dmin * m; + + uint8_t hm = 1 << (2 * il); + y[0] = d1 * ((ql[0] & 0xF) + (qh[0] & hm ? 16 : 0)) - m1; + y[1] = d1 * ((ql[1] & 0xF) + (qh[1] & hm ? 16 : 0)) - m1; + 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; +} + +__kernel void dequantize_block_q6_K(__global const struct block_q6_K *x, __global float *yy) +{ + const int i = get_group_id(0); + const int tid = get_local_id(0); + const int ip = tid / 32; + const int il = tid - 32 * ip; + const int is = 8 * ip + il / 16; + + __global float *y = yy + i * 256 + 128 * ip + il; + + const float d = vload_half(0, &x[i].d); + + __global const uint8_t *ql = x[i].ql + 64 * ip + il; + const uint8_t qh = x[i].qh[32 * ip + il]; + __global const int8_t *sc = x[i].scales + is; + + y[0] = d * sc[0] * ((int8_t)((ql[0] & 0xF) | (((qh >> 0) & 3) << 4)) - 32); + 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); +} + + +void vec_dot_q2_K(__global const struct block_q2_K* x, const int ib, const int iqs, const __global float *yy, float *result) { + + int n = iqs / 128; + int r = iqs - 128 * n; + int l = r / 8; + + __global const float *y = yy + 128 * n + l; + __global const uint8_t *q = x[ib].qs + 32 * n + l; + __global const uint8_t *s = x[ib].scales + 8 * n; + + const float dall = vload_half(0, &x[ib].d); + const float dmin = vload_half(0, &x[ib].dmin); + + float sum = y[ 0] * (dall * ((s[0] & 0xF) * ((q[ 0] >> 0) & 3)) - dmin * (s[0] >> 4)) + + y[ 32] * (dall * ((s[2] & 0xF) * ((q[ 0] >> 2) & 3)) - dmin * (s[2] >> 4)) + + y[ 64] * (dall * ((s[4] & 0xF) * ((q[ 0] >> 4) & 3)) - dmin * (s[4] >> 4)) + + y[ 96] * (dall * ((s[6] & 0xF) * ((q[ 0] >> 6) & 3)) - dmin * (s[6] >> 4)) + + y[ 16] * (dall * ((s[1] & 0xF) * ((q[16] >> 0) & 3)) - dmin * (s[1] >> 4)) + + y[ 48] * (dall * ((s[3] & 0xF) * ((q[16] >> 2) & 3)) - dmin * (s[3] >> 4)) + + y[ 80] * (dall * ((s[5] & 0xF) * ((q[16] >> 4) & 3)) - dmin * (s[5] >> 4)) + + y[112] * (dall * ((s[7] & 0xF) * ((q[16] >> 6) & 3)) - dmin * (s[7] >> 4)); + + *result = sum; +} + +void vec_dot_q3_K(__global const struct block_q3_K* x, const int ib, const int iqs, const __global float *yy, float *result) { + + const uint32_t kmask1 = 0x03030303; + const uint32_t kmask2 = 0x0f0f0f0f; + + uint32_t aux[3]; + uint32_t utmp[4]; + + int n = iqs/128; + int r = iqs - 128*n; + int l = r/8; + + __global const float * y = yy + 128*n + l; + __global const uint8_t * q = x[ib].qs + 32*n + l; + __global const uint8_t * hm = x[ib].hmask + l; + const int8_t * s = (const int8_t *)utmp + 8*n; + + aux[0] = x[ib].scales[0] | x[ib].scales[1] << 8 | x[ib].scales[2] << 16 | x[ib].scales[3] << 24; + aux[1] = x[ib].scales[4] | x[ib].scales[5] << 8 | x[ib].scales[6] << 16 | x[ib].scales[7] << 24; + aux[2] = x[ib].scales[8] | x[ib].scales[9] << 8 | x[ib].scales[10] << 16 | x[ib].scales[11] << 24; + + utmp[3] = ((aux[1] >> 4) & kmask2) | (((aux[2] >> 6) & kmask1) << 4); + utmp[2] = ((aux[0] >> 4) & kmask2) | (((aux[2] >> 4) & kmask1) << 4); + utmp[1] = (aux[1] & kmask2) | (((aux[2] >> 2) & kmask1) << 4); + utmp[0] = (aux[0] & kmask2) | (((aux[2] >> 0) & kmask1) << 4); + + const float dall = vload_half(0, &x[ib].d); + const uint8_t m = 1 << (4*n); + + float sum = y[ 0] * (s[0] - 32) * (((q[ 0] >> 0) & 3) - (hm[ 0] & (m << 0) ? 0 : 4)) + + y[ 32] * (s[2] - 32) * (((q[ 0] >> 2) & 3) - (hm[ 0] & (m << 1) ? 0 : 4)) + + y[ 64] * (s[4] - 32) * (((q[ 0] >> 4) & 3) - (hm[ 0] & (m << 2) ? 0 : 4)) + + y[ 96] * (s[6] - 32) * (((q[ 0] >> 6) & 3) - (hm[ 0] & (m << 3) ? 0 : 4)) + + y[ 16] * (s[1] - 32) * (((q[16] >> 0) & 3) - (hm[16] & (m << 0) ? 0 : 4)) + + y[ 48] * (s[3] - 32) * (((q[16] >> 2) & 3) - (hm[16] & (m << 1) ? 0 : 4)) + + y[ 80] * (s[5] - 32) * (((q[16] >> 4) & 3) - (hm[16] & (m << 2) ? 0 : 4)) + + y[112] * (s[7] - 32) * (((q[16] >> 6) & 3) - (hm[16] & (m << 3) ? 0 : 4)); + + *result = sum * dall; + +} + +void vec_dot_q4_K(__global const struct block_q4_K* x, const int ib, const int iqs, const __global float *yy, float *result) { + + const int j = iqs / 64; // j is in 0...3 + const int ir = (iqs - 64*j)/2; // ir is in 0...28 in steps of 4 + const int is = 2*j; // is is in 0...6 in steps of 2 + + __global const float * y = yy + 64*j + ir; + __global const uint8_t * q = x[ib].qs + 32*j + ir; + + const float dall = vload_half(0, &x[ib].d); + const float dmin = vload_half(0, &x[ib].dmin); + + uint8_t sc, m; + get_scale_min_k4(is + 0, x[ib].scales, &sc, &m); + const float d1 = dall * sc; + const float m1 = dmin * m; + get_scale_min_k4(is + 1, x[ib].scales, &sc, &m); + const float d2 = dall * sc; + const float m2 = dmin * m; + + float sum = 0; + for (int k = 0; k < 4; ++k) { + sum += y[k + 0] * (d1 * (q[k] & 0xF) - m1); + sum += y[k + 32] * (d2 * (q[k] >> 4) - m2); + } + + *result = sum; +} + +void vec_dot_q5_K(__global const struct block_q5_K* x, const int ib, const int iqs, const __global float *yy, float *result) { + + const int j = iqs / 64; + const int ir = (iqs - 64*j)/2; + const int is = 2*j; + + __global const float * y = yy + 64*j + ir; + __global const uint8_t * ql = x[ib].qs + 32*j + ir; + __global const uint8_t * qh = x[ib].qh + ir; + + const float dall = vload_half(0, &x[ib].d); + const float dmin = vload_half(0, &x[ib].dmin); + + uint8_t sc, m; + get_scale_min_k4(is + 0, x[ib].scales, &sc, &m); + const float d1 = dall * sc; + const float m1 = dmin * m; + get_scale_min_k4(is + 1, x[ib].scales, &sc, &m); + const float d2 = dall * sc; + const float m2 = dmin * m; + + uint8_t hm = 1 << is; + float sum = 0; + for (int k = 0; k < 4; ++k) { + sum += y[k + 0] * (d1 * ((ql[k] & 0xF) + (qh[k] & hm ? 16 : 0)) - m1); + } + hm <<= 1; + for (int k = 0; k < 4; ++k) { + sum += y[k + 32] * (d2 * ((ql[k] >> 4) + (qh[k] & hm ? 16 : 0)) - m2); + } + *result = sum; + +} + +void vec_dot_q6_K(__global const struct block_q6_K* x, const int ib, const int iqs, const __global float *yy, float *result) { + + + const int ip = iqs / 128; // 0 or 1 + const int il = (iqs - 128*ip)/8; // 0...15 + const int is = 8*ip; + + __global const float * y = yy + 128*ip + il; + + const float d = vload_half(0, &x[ib].d); + + __global const uint8_t * ql = x[ib].ql + 64*ip + il; + __global const uint8_t * qh = x[ib].qh + 32*ip + il; + __global const int8_t * sc = x[ib].scales + is; + + *result = y[ 0] * d * sc[0] * ((int8_t)((ql[ 0] & 0xF) | (((qh[ 0] >> 0) & 3) << 4)) - 32) + + y[ 32] * d * sc[2] * ((int8_t)((ql[32] & 0xF) | (((qh[ 0] >> 2) & 3) << 4)) - 32) + + y[ 64] * d * sc[4] * ((int8_t)((ql[ 0] >> 4) | (((qh[ 0] >> 4) & 3) << 4)) - 32) + + y[ 96] * d * sc[6] * ((int8_t)((ql[32] >> 4) | (((qh[ 0] >> 6) & 3) << 4)) - 32) + + y[ 16] * d * sc[1] * ((int8_t)((ql[16] & 0xF) | (((qh[16] >> 0) & 3) << 4)) - 32) + + y[ 48] * d * sc[3] * ((int8_t)((ql[48] & 0xF) | (((qh[16] >> 2) & 3) << 4)) - 32) + + y[ 80] * d * sc[5] * ((int8_t)((ql[16] >> 4) | (((qh[16] >> 4) & 3) << 4)) - 32) + + y[112] * d * sc[7] * ((int8_t)((ql[48] >> 4) | (((qh[16] >> 6) & 3) << 4)) - 32); + +} + +); + + +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_group_id(0); + 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]; + } +} +); + +std::string dequant_mul_mat_vec_k_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_group_id(0); + const int tid = get_local_id(0); + + const int iter_stride = 256; + const int vals_per_iter = iter_stride / block_size; + const int num_blocks_per_row = ncols / 256; + const int ib0 = row*num_blocks_per_row; + + tmp[tid] = 0; + + for (int i = 0; i < ncols; i += iter_stride) { + const int col = i + vals_per_iter*tid; + const int ib = ib0 + col/256; // x block index + const int iqs = col%256; // x quant index + const int iybs = col - col%256; // y block start index + + // dequantize + float v; + DOT_KERNEL(x, ib, iqs, y + iybs, &v); + tmp[tid] += v; + } + + // 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]; + } +} +); + +std::string mul_template = MULTILINE_QUOTE( +__kernel void KERNEL_NAME(__global TYPE* x, const int x_offset, __global TYPE* y, const int y_offset, __global TYPE* dst, const int dst_offset, const int ky) { + const int i = get_group_id(0)*get_local_size(0) + get_local_id(0); + + if (i >= get_global_size(0)) { + return; + } + + dst[dst_offset + i] = x[x_offset + i] * y[y_offset + i%ky]; +} +); + +#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 dequant_str_keys = { + "KERNEL_NAME", "X_TYPE", "QUANT_K", "QUANT_R", "DEQUANT_FUNC" +}; + +std::array 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 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::array mul_str_keys = { + "KERNEL_NAME", "TYPE" +}; +std::array mul_str_values = { + "mul_f32", "float" +}; + +std::array dmmv_k_str_keys = { + "KERNEL_NAME", "X_TYPE", "DOT_KERNEL" +}; + +std::array dmmv_k_str_values = { + "dequantize_mul_mat_vec_q2_K", "struct block_q2_K", "vec_dot_q2_K", + "dequantize_mul_mat_vec_q3_K", "struct block_q3_K", "vec_dot_q3_K", + "dequantize_mul_mat_vec_q4_K", "struct block_q4_K", "vec_dot_q4_K", + "dequantize_mul_mat_vec_q5_K", "struct block_q5_K", "vec_dot_q5_K", + "dequantize_mul_mat_vec_q6_K", "struct block_q6_K", "vec_dot_q6_K", +}; + +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'; + } + for (size_t i = 0; i < mul_str_values.size(); i += mul_str_keys.size()) { + std::string mul_kernel = mul_template; + for (size_t j = 0; j < mul_str_keys.size(); j++) { + replace(mul_kernel, mul_str_keys[j], mul_str_values[i + j]); + } + src << mul_kernel << '\n'; + } + for (size_t i = 0; i < dmmv_k_str_values.size(); i += dmmv_k_str_keys.size()) { + std::string dmmv_k_kernel = dequant_mul_mat_vec_k_template; + for (size_t j = 0; j < dmmv_k_str_keys.size(); j++) { + replace(dmmv_k_kernel, dmmv_k_str_keys[j], dmmv_k_str_values[i + j]); + } + src << dmmv_k_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 cl_kernel dequantize_block_q2_k_cl, dequantize_block_q3_k_cl, dequantize_block_q4_k_cl, dequantize_block_q5_k_cl, dequantize_block_q6_k_cl; +static cl_kernel dequantize_mul_mat_vec_q2_K_cl, dequantize_mul_mat_vec_q3_K_cl, dequantize_mul_mat_vec_q4_K_cl, dequantize_mul_mat_vec_q5_K_cl, dequantize_mul_mat_vec_q6_K_cl; +static cl_kernel mul_f32_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 *)alloca(ext_str_size + 1); + clGetDeviceInfo(device, CL_DEVICE_EXTENSIONS, ext_str_size, ext_buffer, NULL); + ext_buffer[ext_str_size] = '\0'; // ensure it is null terminated + // Check if ext_buffer contains cl_khr_fp16 + fp16_support = strstr(ext_buffer, "cl_khr_fp16") != NULL; + 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_QUEUE_PROPERTIES && 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)); + CL_CHECK((dequantize_row_q8_0_cl = clCreateKernel(program, "dequantize_row_q8_0", &err), err)); + CL_CHECK((dequantize_block_q2_k_cl = clCreateKernel(program, "dequantize_block_q2_K", &err), err)); + CL_CHECK((dequantize_block_q3_k_cl = clCreateKernel(program, "dequantize_block_q3_K", &err), err)); + CL_CHECK((dequantize_block_q4_k_cl = clCreateKernel(program, "dequantize_block_q4_K", &err), err)); + CL_CHECK((dequantize_block_q5_k_cl = clCreateKernel(program, "dequantize_block_q5_K", &err), err)); + CL_CHECK((dequantize_block_q6_k_cl = clCreateKernel(program, "dequantize_block_q6_K", &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)); + CL_CHECK((dequantize_mul_mat_vec_q2_K_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q2_K", &err), err)); + CL_CHECK((dequantize_mul_mat_vec_q3_K_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q3_K", &err), err)); + CL_CHECK((dequantize_mul_mat_vec_q4_K_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q4_K", &err), err)); + CL_CHECK((dequantize_mul_mat_vec_q5_K_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q5_K", &err), err)); + CL_CHECK((dequantize_mul_mat_vec_q6_K_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q6_K", &err), err)); + + // mul kernel + CL_CHECK((mul_f32_cl = clCreateKernel(program, "mul_f32", &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_Q2_K: + return &dequantize_block_q2_k_cl; + case GGML_TYPE_Q3_K: + return &dequantize_block_q3_k_cl; + case GGML_TYPE_Q4_K: + return &dequantize_block_q4_k_cl; + case GGML_TYPE_Q5_K: + return &dequantize_block_q5_k_cl; + case GGML_TYPE_Q6_K: + return &dequantize_block_q6_k_cl; + case GGML_TYPE_F16: + return &convert_row_f16_cl; + default: + return nullptr; + } +} + +static size_t ggml_cl_global_denom(ggml_type type) { + switch (type) { + case GGML_TYPE_Q4_0: + case GGML_TYPE_Q4_1: + case GGML_TYPE_Q5_0: + case GGML_TYPE_Q5_1: + case GGML_TYPE_Q8_0: + return 1; + case GGML_TYPE_Q2_K: + case GGML_TYPE_Q3_K: + return 4; + case GGML_TYPE_Q4_K: + return 8; + case GGML_TYPE_Q5_K: + case GGML_TYPE_Q6_K: + return 4; + case GGML_TYPE_F16: + default: + return 1; + } +} + +static size_t ggml_cl_local_size(ggml_type type) { + switch (type) { + case GGML_TYPE_Q4_0: + case GGML_TYPE_Q4_1: + case GGML_TYPE_Q5_0: + case GGML_TYPE_Q5_1: + case GGML_TYPE_Q8_0: + return 0; + case GGML_TYPE_Q2_K: + case GGML_TYPE_Q3_K: + return 64; + case GGML_TYPE_Q4_K: + return 32; + case GGML_TYPE_Q5_K: + case GGML_TYPE_Q6_K: + return 64; + case GGML_TYPE_F16: + default: + return 0; + } +} + +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; + case GGML_TYPE_Q2_K: + return &dequantize_mul_mat_vec_q2_K_cl; + case GGML_TYPE_Q3_K: + return &dequantize_mul_mat_vec_q3_K_cl; + case GGML_TYPE_Q4_K: + return &dequantize_mul_mat_vec_q4_K_cl; + case GGML_TYPE_Q5_K: + return &dequantize_mul_mat_vec_q5_K_cl; + case GGML_TYPE_Q6_K: + return &dequantize_mul_mat_vec_q6_K_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) { + scoped_spin_lock lock(g_cl_pool_lock); + cl_int err; + + int best_i = -1; + size_t best_size = std::numeric_limits::max(); //smallest unused buffer that fits our needs + int worst_i = -1; + size_t worst_size = 0; //largest unused buffer seen so far + for (int i = 0; i < MAX_CL_BUFFERS; ++i) { + cl_buffer &b = g_cl_buffer_pool[i]; + if (b.size > 0 && b.size >= size && b.size < best_size) + { + best_i = i; + best_size = b.size; + } + if (b.size > 0 && b.size > worst_size) + { + worst_i = i; + worst_size = b.size; + } + } + if(best_i!=-1) //found the smallest buffer that fits our needs + { + cl_buffer& b = g_cl_buffer_pool[best_i]; + cl_mem mem = b.mem; + *actual_size = b.size; + b.size = 0; + return mem; + } + if(worst_i!=-1) //no buffer that fits our needs, resize largest one to save memory + { + cl_buffer& b = g_cl_buffer_pool[worst_i]; + cl_mem mem = b.mem; + b.size = 0; + clReleaseMemObject(mem); + } + cl_mem mem; + CL_CHECK((mem = clCreateBuffer(context, CL_MEM_READ_WRITE, 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); +} + +void ggml_cl_free_data(const struct ggml_tensor* tensor) { + if (tensor->backend != GGML_BACKEND_GPU) { + return; + } + + cl_mem mem = (cl_mem)tensor->data; + 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_f32(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) { + GGML_ASSERT(src1->backend == GGML_BACKEND_GPU); + 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[2]; + const int64_t ne0 = ne00 * ne01 * ne02 * ne03; + const int64_t ne10 = src1->ne[0]; + const int64_t ne11 = src1->ne[1]; + const int64_t ne12 = src1->ne[2]; + const int64_t ne13 = src1->ne[3]; + const int64_t nb10 = src1->nb[0]; + const int nb2 = dst->nb[2]; + const int nb3 = dst->nb[3]; + size_t x_size; + size_t d_size; + + cl_mem d_X = ggml_cl_pool_malloc(ne0 * sizeof(float), &x_size); // src0 + cl_mem d_Y = (cl_mem) src1->data; // src1 is already on device, broadcasted. + cl_mem d_D = ggml_cl_pool_malloc(ne0 * sizeof(float), &d_size); // dst + + + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + const int i0 = i03*ne02 + i02; + + cl_event ev; + + // copy src0 to device + CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, i0, src0, i03, i02, &ev)); + + if (nb10 == sizeof(float)) { + // Contiguous, avoid overhead from queueing many kernel runs + const int64_t i13 = i03%ne13; + const int64_t i12 = i02%ne12; + const int i1 = i13*ne12*ne11 + i12*ne11; + + cl_int x_offset = 0; + cl_int y_offset = i1*ne10; + cl_int d_offset = 0; + + size_t global = ne00 * ne01; + cl_int ky = ne10; + CL_CHECK(clSetKernelArg(mul_f32_cl, 0, sizeof(cl_mem), &d_X)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 1, sizeof(cl_int), &x_offset)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 2, sizeof(cl_mem), &d_Y)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 3, sizeof(cl_int), &y_offset)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 4, sizeof(cl_mem), &d_D)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 5, sizeof(cl_int), &d_offset)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 6, sizeof(cl_int), &ky)); + CL_CHECK(clEnqueueNDRangeKernel(queue, mul_f32_cl, 1, NULL, &global, NULL, 1, &ev, NULL)); + } else { + for (int64_t i01 = 0; i01 < ne01; i01++) { + const int64_t i13 = i03%ne13; + const int64_t i12 = i02%ne12; + const int64_t i11 = i01%ne11; + const int i1 = i13*ne12*ne11 + i12*ne11 + i11; + + cl_int x_offset = i01*ne00; + cl_int y_offset = i1*ne10; + cl_int d_offset = i01*ne00; + + // compute + size_t global = ne00; + cl_int ky = ne10; + CL_CHECK(clSetKernelArg(mul_f32_cl, 0, sizeof(cl_mem), &d_X)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 1, sizeof(cl_int), &x_offset)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 2, sizeof(cl_mem), &d_Y)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 3, sizeof(cl_int), &y_offset)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 4, sizeof(cl_mem), &d_D)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 5, sizeof(cl_int), &d_offset)); + CL_CHECK(clSetKernelArg(mul_f32_cl, 6, sizeof(cl_int), &ky)); + CL_CHECK(clEnqueueNDRangeKernel(queue, mul_f32_cl, 1, NULL, &global, NULL, 1, &ev, NULL)); + } + } + + CL_CHECK(clReleaseEvent(ev)); + CL_CHECK(clFinish(queue)); + + // copy dst to host + float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3); + CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(float) * ne00*ne01, d, 0, NULL, NULL)); + } + } + ggml_cl_pool_free(d_X, x_size); + ggml_cl_pool_free(d_D, d_size); +} + +void ggml_cl_mul(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) { + GGML_ASSERT(src0->type == GGML_TYPE_F32 && src1->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32); + ggml_cl_mul_f32(src0, src1, dst); +} + +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_GPU) { // NOLINT + d_X = (cl_mem) src0->data; + } else { + d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size); + } + cl_mem d_Y = ggml_cl_pool_malloc(sizeof(float) * y_ne, &y_size); + cl_mem d_D = ggml_cl_pool_malloc(sizeof(float) * d_ne, &d_size); + + 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_GPU) { + 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(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_GPU) { + 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_GPU) { // NOLINT + d_X = (cl_mem) src0->data; + } else { + d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size); + } + cl_mem d_Y = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * y_ne, &y_size); + cl_mem d_D = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * d_ne, &d_size); + + 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_GPU) { + 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(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_GPU) { + 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 d_Y = ggml_cl_pool_malloc(sizeof(float) * y_ne, &y_size); + cl_mem d_D = ggml_cl_pool_malloc(sizeof(float) * d_ne, &d_size); + cl_mem d_Q; + if (src0->backend == GGML_BACKEND_CPU) { + d_Q = ggml_cl_pool_malloc(q_sz, &q_size); + } + + 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); + + const size_t global_denom = ggml_cl_global_denom(type); + const size_t local = ggml_cl_local_size(type); + + size_t ev_idx = 0; + std::vector events; + + for (int64_t i03 = 0; i03 < ne03; i03++) { + for (int64_t i02 = 0; i02 < ne02; i02++) { + // copy src0 to device if necessary + if (src0->backend == GGML_BACKEND_CPU) { + events.emplace_back(); + CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Q, 0, src0, i03, i02, events.data() + ev_idx++)); + } else if (src0->backend == GGML_BACKEND_GPU) { + d_Q = (cl_mem) src0->data; + } else { + GGML_ASSERT(false); + } + if (mul_mat_vec) { // specialized dequantize_mul_mat_vec kernel + // copy src1 to device + events.emplace_back(); + CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, events.data() + ev_idx++)); + + // compute + const size_t global = ne01 * CL_DMMV_BLOCK_SIZE; + const size_t local = CL_DMMV_BLOCK_SIZE; + const cl_int ncols = ne00; + events.emplace_back(); + 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(clEnqueueNDRangeKernel(queue, *dmmv, 1, NULL, &global, &local, events.size() - 1, events.data(), events.data() + ev_idx++)); + } else { // general dequantization kernel + CLBlast matrix matrix multiplication + // convert src0 to fp32 on device + const size_t global = x_ne / global_denom; + 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(clEnqueueNDRangeKernel(queue, *to_fp32_cl, 1, NULL, &global, local > 0 ? &local : NULL, events.size(), !events.empty() ? events.data() : NULL, NULL)); + + // copy src1 to device + CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, NULL)); + + events.emplace_back(); + + // wait for conversion + CL_CHECK(clFinish(queue)); + + // compute + clblast::StatusCode status = clblast::Gemm(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, events.data() + ev_idx++); + + 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, &events[events.size() - 1], NULL)); + for (auto *event : events) { + clReleaseEvent(event); + } + + ev_idx = 0; + events.clear(); + } + } + + 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_GPU)) { + 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(void * data, 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 = ggml_cl_pool_malloc(q_sz, &q_size); + + tensor->data = data; + // 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; + GGML_ASSERT(tensor->backend == GGML_BACKEND_GPU); +}