#include "ggml-opencl.h" #include #include #include #define CL_TARGET_OPENCL_VERSION 110 #include #include #include #include #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 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::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_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)); // 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(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(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(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; }