+++ /dev/null
-#include "ggml-opencl.h"
-
-#define CL_TARGET_OPENCL_VERSION 110
-#include <clblast_c.h>
-
-#include <stdlib.h>
-#include <stdio.h>
-#include <string.h>
-
-#include "ggml.h"
-
-#define MULTILINE_QUOTE(...) #__VA_ARGS__
-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);
-}
--- /dev/null
+#include "ggml-opencl.h"
+
+#include <array>
+#include <atomic>
+#include <sstream>
+#include <vector>
+#include <limits>
+
+#define CL_TARGET_OPENCL_VERSION 110
+#include <clblast.h>
+
+#include <stdlib.h>
+#include <stdio.h>
+#include <string.h>
+
+#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<std::string, 5> dequant_str_keys = {
+ "KERNEL_NAME", "X_TYPE", "QUANT_K", "QUANT_R", "DEQUANT_FUNC"
+};
+
+std::array<std::string, 30> dequant_str_values = {
+ "dequantize_row_q4_0", "struct block_q4_0", "QK4_0", "QR4_0", "dequantize_q4_0",
+ "dequantize_row_q4_1", "struct block_q4_1", "QK4_1", "QR4_1", "dequantize_q4_1",
+ "dequantize_row_q5_0", "struct block_q5_0", "QK5_0", "QR5_0", "dequantize_q5_0",
+ "dequantize_row_q5_1", "struct block_q5_1", "QK5_1", "QR5_1", "dequantize_q5_1",
+ "dequantize_row_q8_0", "struct block_q8_0", "QK8_0", "QR8_0", "dequantize_q8_0",
+ "convert_row_f16", "half", "1", "1", "convert_f16"
+};
+
+std::array<std::string, 30> dequant_mul_mat_vec_str_values = {
+ "dequantize_mul_mat_vec_q4_0", "struct block_q4_0", "QK4_0", "QR4_0", "dequantize_q4_0",
+ "dequantize_mul_mat_vec_q4_1", "struct block_q4_1", "QK4_1", "QR4_1", "dequantize_q4_1",
+ "dequantize_mul_mat_vec_q5_0", "struct block_q5_0", "QK5_0", "QR5_0", "dequantize_q5_0",
+ "dequantize_mul_mat_vec_q5_1", "struct block_q5_1", "QK5_1", "QR5_1", "dequantize_q5_1",
+ "dequantize_mul_mat_vec_q8_0", "struct block_q8_0", "QK8_0", "QR8_0", "dequantize_q8_0",
+ "convert_mul_mat_vec_f16", "half", "1", "1", "convert_f16"
+};
+
+std::array<std::string, 2> mul_str_keys = {
+ "KERNEL_NAME", "TYPE"
+};
+std::array<std::string, 2> mul_str_values = {
+ "mul_f32", "float"
+};
+
+std::array<std::string, 3> dmmv_k_str_keys = {
+ "KERNEL_NAME", "X_TYPE", "DOT_KERNEL"
+};
+
+std::array<std::string, 15> 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<size_t>::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<cl_float>(clblast::Layout::kColMajor,
+ clblast::Transpose::kYes, clblast::Transpose::kNo,
+ ne01, ne11, ne10,
+ alpha,
+ d_X, 0, ne00,
+ d_Y, 0, ne10,
+ beta,
+ d_D, 0, ne01,
+ &queue, &ev_sgemm);
+
+ if (status != clblast::StatusCode::kSuccess) {
+ GGML_ASSERT(false);
+ }
+
+ // copy dst to host
+ float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
+ CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(float) * d_ne, d, 1, &ev_sgemm, NULL));
+ }
+ }
+
+ if (src0->backend != GGML_BACKEND_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<cl_half>(clblast::Layout::kColMajor,
+ clblast::Transpose::kYes, clblast::Transpose::kNo,
+ ne01, ne11, ne10,
+ alpha,
+ d_X, 0, ne00,
+ d_Y, 0, ne10,
+ beta,
+ d_D, 0, ne01,
+ &queue, &ev_sgemm);
+
+ if (status != clblast::StatusCode::kSuccess) {
+ GGML_ASSERT(false);
+ }
+
+ // copy dst to host, then convert to float
+ CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(ggml_fp16_t) * d_ne, tmp, 1, &ev_sgemm, NULL));
+
+ float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
+
+ ggml_fp16_to_fp32_row(tmp, d, d_ne);
+ }
+ }
+
+ if (src0->backend != GGML_BACKEND_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<cl_event> 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<cl_float>(clblast::Layout::kColMajor,
+ clblast::Transpose::kYes, clblast::Transpose::kNo,
+ ne01, ne11, ne10,
+ alpha,
+ d_X, 0, ne00,
+ d_Y, 0, ne10,
+ beta,
+ d_D, 0, ne01,
+ &queue, 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);
+}
overview / pkg / ggml / sources / whisper.cpp / commitdiff