OpenCL Token Generation Acceleration (#1459)

* Move back to C++ for OpenCL

* Refactor OpenCL code to work more like the CUDA code, add missing functions

* Deduplicate dequant kernels

* Add OpenCL compile options

* Use compile args for preprocessing constants

* Restore default platform + device selection by id behavior

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: Henri Vasserman <henv@hot.ee>

1 files changed, 1034 insertions, 0 deletions

diff --git a/ggml-opencl.cpp b/ggml-opencl.cpp
new file mode 100644
index 0000000..fb007dd
--- /dev/null
+++ b/ggml-opencl.cpp
@@ -0,0 +1,1034 @@
+#include "ggml-opencl.h"
+
+#include <array>
+#include <atomic>
+#include <sstream>
+
+#define CL_TARGET_OPENCL_VERSION 110
+#include <clblast.h>
+
+#include <stdlib.h>
+#include <stdio.h>
+#include <string.h>
+
+#include "ggml.h"
+
+#define CL_DMMV_BLOCK_SIZE 32;
+
+#define MULTILINE_QUOTE(...) #__VA_ARGS__
+static std::string program_source = MULTILINE_QUOTE(
+
+typedef char int8_t;
+typedef uchar uint8_t;
+typedef int int32_t;
+typedef uint uint32_t;
+
+struct __attribute__ ((packed)) block_q4_0
+{
+    half d;
+    uint8_t qs[QK4_0 / 2];
+};
+
+struct __attribute__ ((packed)) block_q4_1
+{
+    half d;
+    half m;
+    uint8_t qs[QK4_1 / 2];
+};
+
+struct __attribute__ ((packed)) block_q5_0
+{
+    half d;
+    uint32_t qh;
+    uint8_t qs[QK5_0 / 2];
+};
+
+struct __attribute__ ((packed)) block_q5_1
+{
+    half d;
+    half m;
+    uint32_t qh;
+    uint8_t qs[QK5_1 / 2];
+};
+
+struct __attribute__ ((packed)) block_q8_0
+{
+    half d;
+    int8_t qs[QK8_0];
+};
+
+
+__kernel void convert_fp16_to_fp32(__global half* x, __global float* y) {
+    const uint i = get_global_id(0);
+
+    y[i] = vload_half(0, &x[i]);
+}
+
+void dequantize_q4_0(__global const struct block_q4_0* x, const int ib, const int iqs, float* v0, float* v1) {
+    const float d = vload_half(0, &x[ib].d);
+
+    const uint8_t vui = x[ib].qs[iqs];
+
+    const int8_t vi0 = vui & 0xF;
+    const int8_t vi1 = vui >> 4;
+
+    *v0 = (vi0 - 8)*d;
+    *v1 = (vi1 - 8)*d;
+}
+void dequantize_q4_1(__global const struct block_q4_1* x, const int ib, const int iqs, float* v0, float* v1) {
+    const float d = vload_half(0, &x[ib].d);
+    const float m = vload_half(0, &x[ib].m);
+
+    const uint8_t vui = x[ib].qs[iqs];
+
+    const int8_t vi0 = vui & 0xF;
+    const int8_t vi1 = vui >> 4;
+
+    *v0 = vi0*d + m;
+    *v1 = vi1*d + m;
+}
+void dequantize_q5_0(__global const struct block_q5_0* x, const int ib, const int iqs, float* v0, float* v1) {
+    const float d = vload_half(0, &x[ib].d);
+
+    uint32_t qh = x[ib].qh;
+
+    const uint8_t xh_0 = ((qh >> (iqs +  0)) << 4) & 0x10;
+    const uint8_t xh_1 = ((qh >> (iqs + 12))     ) & 0x10;
+
+    const int32_t x0 = ((x[ib].qs[iqs] & 0xf) | xh_0) - 16;
+    const int32_t x1 = ((x[ib].qs[iqs] >>  4) | xh_1) - 16;
+
+    *v0 = x0*d;
+    *v1 = x1*d;
+}
+void dequantize_q5_1(__global const struct block_q5_1* x, const int ib, const int iqs, float* v0, float* v1) {
+    const float d = vload_half(0, &x[ib].d);
+    const float m = vload_half(0, &x[ib].m);
+
+    uint32_t qh = x[ib].qh;
+
+    const uint8_t xh_0 = ((qh >> (iqs +  0)) << 4) & 0x10;
+    const uint8_t xh_1 = ((qh >> (iqs + 12))     ) & 0x10;
+
+    const int32_t x0 = ((x[ib].qs[iqs] & 0xf) | xh_0);
+    const int32_t x1 = ((x[ib].qs[iqs] >>  4) | xh_1);
+
+    *v0 = x0*d + m;
+    *v1 = x1*d + m;
+}
+void dequantize_q8_0(__global const struct block_q8_0* x, const int ib, const int iqs, float* v0, float* v1) {
+    const float d = vload_half(0, &x[ib].d);
+
+    const int8_t vi0 = x[ib].qs[iqs + 0];
+    const int8_t vi1 = x[ib].qs[iqs + 1];
+
+    *v0 = vi0*d;
+    *v1 = vi1*d;
+}
+void convert_f16(__global half* x, const int ib, const int iqs, float* v0, float* v1){
+    *v0 = vload_half(0, &x[ib + 0]);
+    *v1 = vload_half(0, &x[ib + 1]);
+}
+);
+
+std::string dequant_template = MULTILINE_QUOTE(
+__kernel void KERNEL_NAME(__global X_TYPE* x, __global float* y) {
+    const int i = get_group_id(0)*get_local_size(0) + get_local_id(0)*2;
+
+    if (i >= get_global_size(0)) {
+        return;
+    }
+
+    const uint qk = QUANT_K;
+    const uint qr = QUANT_R;
+
+    const int ib = i/qk; // block index
+    const int iqs = (i%qk)/qr; // quant index
+    const int iybs = i - i%qk; // y block start index
+    const int y_offset = qr == 1 ? 1 : qk/2;
+
+    // dequantize
+    float v0, v1;
+    DEQUANT_FUNC(x, ib, iqs, &v0, &v1);
+    y[iybs + iqs + 0] = v0;
+    y[iybs + iqs + y_offset] = v1;
+}
+);
+
+std::string dequant_mul_mat_vec_template = MULTILINE_QUOTE(
+__kernel void KERNEL_NAME(__global X_TYPE* x, __local float* tmp, __global float* y, __global float* dst, const int ncols) {
+    const int block_size = get_local_size(0);
+    const int row = get_global_id(0) / block_size;
+    const int tid = get_local_id(0);
+
+    const uint qk = QUANT_K;
+    const uint qr = QUANT_R;
+
+    const int y_offset = qr == 1 ? 1 : qk/2;
+
+    tmp[tid] = 0;
+
+    for (int i = 0; i < ncols/block_size; i += 2) {
+        const int col = i*block_size + 2*tid;
+        const int ib = (row*ncols + col)/qk; // block index
+        const int iqs = (col%qk)/qr; // quant index
+        const int iybs = col - col%qk; // y block start index
+
+        // dequantize
+        float v0, v1;
+        DEQUANT_FUNC(x, ib, iqs, &v0, &v1);
+
+        // matrix multiplication
+        tmp[tid] += v0 * y[iybs + iqs + 0];
+        tmp[tid] += v1 * y[iybs + iqs + y_offset];
+    }
+
+    // sum up partial sums and write back result
+    barrier(CLK_LOCAL_MEM_FENCE);
+    for (int s=block_size/2; s>0; s>>=1) {
+        if (tid < s) {
+            tmp[tid] += tmp[tid + s];
+        }
+        barrier(CLK_LOCAL_MEM_FENCE);
+    }
+    if (tid == 0) {
+        dst[row] = tmp[0];
+    }
+}
+);
+
+#define CL_CHECK(err)                                               \
+    do {                                                            \
+        cl_int err_ = (err);                                        \
+        if (err_ != CL_SUCCESS) {                                   \
+            fprintf(stderr, "ggml_opencl: %s error %d at %s:%d\n",  \
+                #err, err_, __FILE__, __LINE__);                    \
+            exit(1);                                                \
+        }                                                           \
+    } while (0)
+
+#define CLBLAST_CHECK(err)                                          \
+    do {                                                            \
+        CLBlastStatusCode err_ = (err);                             \
+        if (err_ != CLBlastSuccess) {                               \
+            fprintf(stderr, "ggml_opencl: %s error %d at %s:%d\n",  \
+                #err, err_, __FILE__, __LINE__);                    \
+            exit(1);                                                \
+        }                                                           \
+    } while (0)
+
+std::array<std::string, 5> dequant_str_keys = {
+    "KERNEL_NAME", "X_TYPE", "QUANT_K", "QUANT_R", "DEQUANT_FUNC"
+};
+
+std::array<std::string, 30> dequant_str_values = {
+    "dequantize_row_q4_0", "struct block_q4_0", "QK4_0", "QR4_0", "dequantize_q4_0",
+    "dequantize_row_q4_1", "struct block_q4_1", "QK4_1", "QR4_1", "dequantize_q4_1",
+    "dequantize_row_q5_0", "struct block_q5_0", "QK5_0", "QR5_0", "dequantize_q5_0",
+    "dequantize_row_q5_1", "struct block_q5_1", "QK5_1", "QR5_1", "dequantize_q5_1",
+    "dequantize_row_q8_0", "struct block_q8_0", "QK8_0", "QR8_0", "dequantize_q8_0",
+    "convert_row_f16", "half", "1", "1", "convert_f16"
+};
+
+std::array<std::string, 30> dequant_mul_mat_vec_str_values = {
+    "dequantize_mul_mat_vec_q4_0", "struct block_q4_0", "QK4_0", "QR4_0", "dequantize_q4_0",
+    "dequantize_mul_mat_vec_q4_1", "struct block_q4_1", "QK4_1", "QR4_1", "dequantize_q4_1",
+    "dequantize_mul_mat_vec_q5_0", "struct block_q5_0", "QK5_0", "QR5_0", "dequantize_q5_0",
+    "dequantize_mul_mat_vec_q5_1", "struct block_q5_1", "QK5_1", "QR5_1", "dequantize_q5_1",
+    "dequantize_mul_mat_vec_q8_0", "struct block_q8_0", "QK8_0", "QR8_0", "dequantize_q8_0",
+    "convert_mul_mat_vec_f16", "half", "1", "1", "convert_f16"
+};
+
+std::string& replace(std::string& s, const std::string& from, const std::string& to) {
+    size_t pos = 0;
+    while ((pos = s.find(from, pos)) != std::string::npos) {
+         s.replace(pos, from.length(), to);
+         pos += to.length();
+    }
+    return s;
+}
+
+std::string generate_kernels() {
+    std::stringstream src;
+    src << program_source << '\n';
+    for (size_t i = 0; i < dequant_str_values.size(); i += dequant_str_keys.size()) {
+        std::string dequant_kernel = dequant_template;
+        std::string dmmv_kernel = dequant_mul_mat_vec_template;
+        for (size_t j = 0; j < dequant_str_keys.size(); j++) {
+            replace(dequant_kernel, dequant_str_keys[j], dequant_str_values[i + j]);
+            replace(dmmv_kernel, dequant_str_keys[j], dequant_mul_mat_vec_str_values[i + j]);
+        }
+        src << dequant_kernel << '\n';
+        src << dmmv_kernel << '\n';
+    }
+    return src.str();
+}
+
+static cl_platform_id platform;
+static cl_device_id device;
+static cl_context context;
+static cl_command_queue queue;
+static cl_program program;
+static cl_kernel convert_row_f16_cl;
+static cl_kernel dequantize_row_q4_0_cl, dequantize_row_q4_1_cl, dequantize_row_q5_0_cl, dequantize_row_q5_1_cl, dequantize_row_q8_0_cl;
+static cl_kernel dequantize_mul_mat_vec_q4_0_cl, dequantize_mul_mat_vec_q4_1_cl, dequantize_mul_mat_vec_q5_0_cl, dequantize_mul_mat_vec_q5_1_cl, dequantize_mul_mat_vec_q8_0_cl, convert_mul_mat_vec_f16_cl;
+static bool fp16_support;
+
+static cl_program build_program_from_source(cl_context ctx, cl_device_id dev, const char* program_buffer) {
+    cl_program p;
+    char *program_log;
+    size_t program_size;
+    size_t log_size;
+    int err;
+
+    program_size = strlen(program_buffer);
+
+    p = clCreateProgramWithSource(ctx, 1, (const char**)&program_buffer, &program_size, &err);
+    if(err < 0) {
+        fprintf(stderr, "OpenCL error creating program");
+        exit(1);
+    }
+
+    const char* compile_opts = "-cl-mad-enable -cl-unsafe-math-optimizations -cl-finite-math-only -cl-fast-relaxed-math "
+                               "-DQK4_0=32 -DQR4_0=2 -DQK4_1=32 -DQR4_1=2 -DQK5_0=32 -DQR5_0=2 -DQK5_1=32 -DQR5_1=2 -DQK8_0=32 -DQR8_0=1";
+
+    err = clBuildProgram(p, 0, NULL, compile_opts, NULL, NULL);
+    if(err < 0) {
+
+        clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, 0, NULL, &log_size);
+        program_log = (char*) malloc(log_size + 1);
+        program_log[log_size] = '\0';
+        clGetProgramBuildInfo(p, dev, CL_PROGRAM_BUILD_LOG, log_size + 1, program_log, NULL);
+        fprintf(stderr, "ggml_opencl: kernel compile error:\n\n%s\n", program_log);
+        free(program_log);
+        exit(1);
+    }
+
+    return p;
+}
+
+void ggml_cl_init(void) {
+    cl_int err;
+
+    struct cl_device;
+    struct cl_platform {
+        cl_platform_id id;
+        unsigned number;
+        char name[128];
+        char vendor[128];
+        struct cl_device * devices;
+        unsigned n_devices;
+        struct cl_device * default_device;
+    };
+
+    struct cl_device {
+        struct cl_platform * platform;
+        cl_device_id id;
+        unsigned number;
+        cl_device_type type;
+        char name[128];
+    };
+
+    enum { NPLAT = 16, NDEV = 16 };
+
+    struct cl_platform platforms[NPLAT];
+    unsigned n_platforms = 0;
+    struct cl_device devices[NDEV];
+    unsigned n_devices = 0;
+    struct cl_device * default_device = NULL;
+
+    platform = NULL;
+    device = NULL;
+
+    cl_platform_id platform_ids[NPLAT];
+    CL_CHECK(clGetPlatformIDs(NPLAT, platform_ids, &n_platforms));
+
+    for (unsigned i = 0; i < n_platforms; i++) {
+        struct cl_platform * p = &platforms[i];
+        p->number = i;
+        p->id = platform_ids[i];
+        CL_CHECK(clGetPlatformInfo(p->id, CL_PLATFORM_NAME, sizeof(p->name), &p->name, NULL));
+        CL_CHECK(clGetPlatformInfo(p->id, CL_PLATFORM_VENDOR, sizeof(p->vendor), &p->vendor, NULL));
+
+        cl_device_id device_ids[NDEV];
+        cl_int clGetDeviceIDsError = clGetDeviceIDs(p->id, CL_DEVICE_TYPE_ALL, NDEV, device_ids, &p->n_devices);
+        if (clGetDeviceIDsError == CL_DEVICE_NOT_FOUND) {
+            p->n_devices = 0;
+        } else {
+            CL_CHECK(clGetDeviceIDsError);
+        }
+        p->devices = p->n_devices > 0 ? &devices[n_devices] : NULL;
+        p->default_device = NULL;
+
+        for (unsigned j = 0; j < p->n_devices; j++) {
+            struct cl_device * d = &devices[n_devices];
+            d->number = n_devices++;
+            d->id = device_ids[j];
+            d->platform = p;
+            CL_CHECK(clGetDeviceInfo(d->id, CL_DEVICE_NAME, sizeof(d->name), &d->name, NULL));
+            CL_CHECK(clGetDeviceInfo(d->id, CL_DEVICE_TYPE, sizeof(d->type), &d->type, NULL));
+
+            if (p->default_device == NULL && d->type == CL_DEVICE_TYPE_GPU) {
+                p->default_device = d;
+            }
+        }
+
+        if (default_device == NULL && p->default_device != NULL) {
+            default_device = p->default_device;
+        }
+    }
+
+    if (n_devices == 0) {
+        fprintf(stderr, "ggml_opencl: could find any OpenCL devices.\n");
+        exit(1);
+    }
+
+    char * user_platform_string = getenv("GGML_OPENCL_PLATFORM");
+    char * user_device_string = getenv("GGML_OPENCL_DEVICE");
+    int user_platform_number = -1;
+    int user_device_number = -1;
+
+    unsigned n;
+    if (user_platform_string != NULL && sscanf(user_platform_string, " %u", &n) == 1 && n < n_platforms) {
+        user_platform_number = (int)n;
+    }
+    if (user_device_string != NULL && sscanf(user_device_string, " %u", &n) == 1 && n < n_devices) {
+        user_device_number = (int)n;
+    }
+    if (user_platform_number != -1 && user_device_number != -1) {
+        cl_platform* platform = &platforms[user_platform_number];
+        if ((unsigned)user_device_number >= platform->n_devices) {
+            fprintf(stderr, "ggml_opencl: invalid device number %d\n", user_device_number);
+            exit(1);
+        }
+        default_device = &platform->devices[user_device_number];
+    } else {
+
+        struct cl_device * selected_devices = devices;
+        unsigned n_selected_devices = n_devices;
+
+        if (user_platform_number == -1 && user_platform_string != NULL && user_platform_string[0] != 0) {
+            for (unsigned i = 0; i < n_platforms; i++) {
+                struct cl_platform * p = &platforms[i];
+                if (strstr(p->name, user_platform_string) != NULL ||
+                    strstr(p->vendor, user_platform_string) != NULL) {
+                    user_platform_number = (int)i;
+                    break;
+                }
+            }
+            if (user_platform_number == -1) {
+                fprintf(stderr, "ggml_opencl: no platform matching '%s' was found.\n", user_platform_string);
+                exit(1);
+            }
+        }
+        if (user_platform_number != -1) {
+            struct cl_platform * p = &platforms[user_platform_number];
+            selected_devices = p->devices;
+            n_selected_devices = p->n_devices;
+            default_device = p->default_device;
+            if (n_selected_devices == 0) {
+                fprintf(stderr, "ggml_opencl: selected platform '%s' does not have any devices.\n", p->name);
+                exit(1);
+            }
+        }
+
+        if (user_device_number == -1 && user_device_string != NULL && user_device_string[0] != 0) {
+            for (unsigned i = 0; i < n_selected_devices; i++) {
+                struct cl_device * d = &selected_devices[i];
+                if (strstr(d->name, user_device_string) != NULL) {
+                    user_device_number = d->number;
+                    break;
+                }
+            }
+            if (user_device_number == -1) {
+                fprintf(stderr, "ggml_opencl: no device matching '%s' was found.\n", user_device_string);
+                exit(1);
+            }
+        }
+        if (user_device_number != -1) {
+            selected_devices = &devices[user_device_number];
+            n_selected_devices = 1;
+            default_device = &selected_devices[0];
+        }
+
+        GGML_ASSERT(n_selected_devices > 0);
+
+        if (default_device == NULL) {
+            default_device = &selected_devices[0];
+        }
+    }
+
+    fprintf(stderr, "ggml_opencl: selecting platform: '%s'\n", default_device->platform->name);
+    fprintf(stderr, "ggml_opencl: selecting device: '%s'\n", default_device->name);
+    if (default_device->type != CL_DEVICE_TYPE_GPU) {
+        fprintf(stderr, "ggml_opencl: warning, not a GPU: '%s'.\n", default_device->name);
+    }
+
+    platform = default_device->platform->id;
+    device = default_device->id;
+
+    size_t ext_str_size;
+    clGetDeviceInfo(device, CL_DEVICE_EXTENSIONS, 0, NULL, &ext_str_size);
+    char* ext_buffer = (char*) malloc(sizeof(char) * ext_str_size);
+    clGetDeviceInfo(device, CL_DEVICE_EXTENSIONS, ext_str_size, ext_buffer, NULL);
+    // Check if ext_buffer contains cl_khr_fp16
+    for (size_t i = 0; i < ext_str_size - 12; i++) {
+        if (memcmp(ext_buffer + i, "cl_khr_fp16", 11) == 0) {
+            fp16_support = true;
+            break;
+        }
+    }
+    free(ext_buffer);
+    fprintf(stderr, "ggml_opencl: device FP16 support: %s\n", fp16_support ? "true" : "false");
+
+    cl_context_properties properties[] = {
+        (intptr_t)CL_CONTEXT_PLATFORM, (intptr_t)platform, 0
+    };
+
+    CL_CHECK((context = clCreateContext(properties, 1, &device, NULL, NULL, &err), err));
+
+    CL_CHECK((queue = clCreateCommandQueue(context, device, CL_QUEUE_OUT_OF_ORDER_EXEC_MODE_ENABLE, &err),
+        (err != CL_INVALID_PROPERTY && err != CL_INVALID_VALUE ? err :
+        (queue = clCreateCommandQueue(context, device, 0, &err), err)
+    )));
+
+    const std::string kernel_src = generate_kernels();
+
+    program = build_program_from_source(context, device, kernel_src.c_str());
+
+    // FP16 to FP32 kernel
+    CL_CHECK((convert_row_f16_cl = clCreateKernel(program, "convert_row_f16", &err), err));
+
+    // Dequantize kernels
+    CL_CHECK((dequantize_row_q4_0_cl = clCreateKernel(program, "dequantize_row_q4_0", &err), err));
+    CL_CHECK((dequantize_row_q4_1_cl = clCreateKernel(program, "dequantize_row_q4_1", &err), err));
+    CL_CHECK((dequantize_row_q5_0_cl = clCreateKernel(program, "dequantize_row_q5_0", &err), err));
+    CL_CHECK((dequantize_row_q5_1_cl = clCreateKernel(program, "dequantize_row_q5_1", &err), err));
+    CL_CHECK((dequantize_row_q8_0_cl = clCreateKernel(program, "dequantize_row_q8_0", &err), err));
+
+    // dequant mul mat kernel
+    CL_CHECK((dequantize_mul_mat_vec_q4_0_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q4_0", &err), err));
+    CL_CHECK((dequantize_mul_mat_vec_q4_1_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q4_1", &err), err));
+    CL_CHECK((dequantize_mul_mat_vec_q5_0_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q5_0", &err), err));
+    CL_CHECK((dequantize_mul_mat_vec_q5_1_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q5_1", &err), err));
+    CL_CHECK((dequantize_mul_mat_vec_q8_0_cl = clCreateKernel(program, "dequantize_mul_mat_vec_q8_0", &err), err));
+    CL_CHECK((convert_mul_mat_vec_f16_cl = clCreateKernel(program, "convert_mul_mat_vec_f16", &err), err));
+}
+
+static cl_kernel* ggml_get_to_fp32_cl(ggml_type type) {
+    switch (type) {
+        case GGML_TYPE_Q4_0:
+            return &dequantize_row_q4_0_cl;
+        case GGML_TYPE_Q4_1:
+            return &dequantize_row_q4_1_cl;
+        case GGML_TYPE_Q5_0:
+            return &dequantize_row_q5_0_cl;
+        case GGML_TYPE_Q5_1:
+            return &dequantize_row_q5_1_cl;
+        case GGML_TYPE_Q8_0:
+            return &dequantize_row_q8_0_cl;
+        case GGML_TYPE_F16:
+            return &convert_row_f16_cl;
+        default:
+            return nullptr;
+    }
+}
+
+static cl_kernel* ggml_get_dequantize_mul_mat_vec_cl(ggml_type type) {
+    switch (type) {
+        case GGML_TYPE_Q4_0:
+            return &dequantize_mul_mat_vec_q4_0_cl;
+        case GGML_TYPE_Q4_1:
+            return &dequantize_mul_mat_vec_q4_1_cl;
+        case GGML_TYPE_Q5_0:
+            return &dequantize_mul_mat_vec_q5_0_cl;
+        case GGML_TYPE_Q5_1:
+            return &dequantize_mul_mat_vec_q5_1_cl;
+        case GGML_TYPE_Q8_0:
+            return &dequantize_mul_mat_vec_q8_0_cl;
+        case GGML_TYPE_F16:
+            return &convert_mul_mat_vec_f16_cl;
+        default:
+            return nullptr;
+    }
+}
+
+// buffer pool for cl
+#define MAX_CL_BUFFERS 256
+
+struct scoped_spin_lock {
+    std::atomic_flag& lock;
+    scoped_spin_lock(std::atomic_flag& lock) : lock(lock) {
+        while (lock.test_and_set(std::memory_order_acquire)) {
+            ; // spin
+        }
+    }
+    ~scoped_spin_lock() {
+        lock.clear(std::memory_order_release);
+    }
+    scoped_spin_lock(const scoped_spin_lock&) = delete;
+    scoped_spin_lock& operator=(const scoped_spin_lock&) = delete;
+};
+
+struct cl_buffer {
+    cl_mem mem;
+    size_t size = 0;
+};
+
+static cl_buffer g_cl_buffer_pool[MAX_CL_BUFFERS];
+static std::atomic_flag g_cl_pool_lock = ATOMIC_FLAG_INIT;
+
+static cl_mem ggml_cl_pool_malloc(size_t size, size_t * actual_size, cl_mem_flags flags) {
+    scoped_spin_lock lock(g_cl_pool_lock);
+    cl_int err;
+
+    for (int i = 0; i < MAX_CL_BUFFERS; ++i) {
+        cl_buffer& b = g_cl_buffer_pool[i];
+        if (b.size > 0 && b.size >= size) {
+            cl_mem mem = b.mem;
+            *actual_size = b.size;
+            b.size = 0;
+            return mem;
+        }
+    }
+    cl_mem mem;
+    CL_CHECK((mem = clCreateBuffer(context, flags, size, NULL, &err), err));
+    *actual_size = size;
+    return mem;
+}
+
+static void ggml_cl_pool_free(cl_mem mem, size_t size) {
+    scoped_spin_lock lock(g_cl_pool_lock);
+
+    for (int i = 0; i < MAX_CL_BUFFERS; ++i) {
+        cl_buffer& b = g_cl_buffer_pool[i];
+        if (b.size == 0) {
+            b.mem = mem;
+            b.size = size;
+            return;
+        }
+    }
+    fprintf(stderr, "WARNING: cl buffer pool full, increase MAX_CL_BUFFERS\n");
+    clReleaseMemObject(mem);
+}
+
+static cl_int ggml_cl_h2d_tensor_2d(cl_command_queue queue, cl_mem dst, size_t offset, const struct ggml_tensor * src, uint64_t i3, uint64_t i2, cl_event* ev) {
+    cl_int err;
+    const uint64_t ne0 = src->ne[0];
+    const uint64_t ne1 = src->ne[1];
+    const uint64_t nb0 = src->nb[0];
+    const uint64_t nb1 = src->nb[1];
+    const uint64_t nb2 = src->nb[2];
+    const uint64_t nb3 = src->nb[3];
+    const enum ggml_type type = src->type;
+    const size_t ts = ggml_type_size(type);
+    const size_t bs = ggml_blck_size(type);
+
+    const void * x = (const void *) ((const char *) src->data + i2*nb2 + i3*nb3);
+    if (nb0 == ts && nb1 == ts*ne0/bs) {
+        err = clEnqueueWriteBuffer(queue, dst, CL_FALSE, offset, ne1*nb1, x, 0, NULL, ev);
+        return err;
+    }
+    if (nb0 == ts) {
+        const size_t buffer_origin[3] = { offset, 0, 0 };
+        const size_t host_origin[3] = { 0, 0, 0 };
+        const size_t region[3] = { ts*ne0/bs, ne1, 1 };
+        err = clEnqueueWriteBufferRect(queue, dst, CL_FALSE, buffer_origin, host_origin, region, ts*ne0/bs, 0, nb1, 0, x, 0, NULL, ev);
+        return err;
+    }
+    for (uint64_t i1 = 0; i1 < ne1; i1++) {
+        // pretend the row is a matrix with cols=1
+        const size_t buffer_origin[3] = { offset, i1, 0 };
+        const size_t host_origin[3] = { 0, 0, 0 };
+        const size_t region[3] = { ts/bs, ne0, 1 };
+        err = clEnqueueWriteBufferRect(queue, dst, CL_FALSE, buffer_origin, host_origin, region, 0, 0, nb0, 0, ((const char *)x) + i1*nb0, 0, NULL, ev);
+        if (err != CL_SUCCESS) {
+            break;
+        }
+    }
+    return err;
+}
+
+static void ggml_cl_mul_mat_f32(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
+    const int64_t ne00 = src0->ne[0];
+    const int64_t ne01 = src0->ne[1];
+    const int64_t ne02 = src0->ne[2];
+    const int64_t ne03 = src0->ne[3];
+
+    const int64_t ne10 = src1->ne[0];
+    const int64_t ne11 = src1->ne[1];
+
+    const int nb2  = dst->nb[2];
+    const int nb3  = dst->nb[3];
+
+    const float alpha = 1.0f;
+    const float beta = 0.0f;
+    const int x_ne = ne01 * ne00;
+    const int y_ne = ne11 * ne10;
+    const int d_ne = ne11 * ne01;
+
+    size_t x_size;
+    size_t y_size;
+    size_t d_size;
+    cl_mem d_X;
+    if (src0->backend == GGML_BACKEND_CL) {
+        d_X = *(cl_mem*) src0->data;
+    } else {
+        d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size, CL_MEM_READ_ONLY);
+    }
+    cl_mem d_Y = ggml_cl_pool_malloc(sizeof(float) * y_ne, &y_size, CL_MEM_READ_ONLY);
+    cl_mem d_D = ggml_cl_pool_malloc(sizeof(float) * d_ne, &d_size, CL_MEM_WRITE_ONLY);
+
+    for (int64_t i03 = 0; i03 < ne03; i03++) {
+        for (int64_t i02 = 0; i02 < ne02; i02++) {
+            // copy data to device
+            if (src0->backend != GGML_BACKEND_CL) {
+                CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, 0, src0, i03, i02, NULL));
+            }
+            CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, NULL));
+
+            CL_CHECK(clFinish(queue));
+
+            // compute
+            cl_event ev_sgemm;
+            clblast::StatusCode status = clblast::Gemm<cl_float>(clblast::Layout::kColMajor,
+                                                       clblast::Transpose::kYes, clblast::Transpose::kNo,
+                                                       ne01, ne11, ne10,
+                                                       alpha,
+                                                       d_X, 0, ne00,
+                                                       d_Y, 0, ne10,
+                                                       beta,
+                                                       d_D, 0, ne01,
+                                                       &queue, &ev_sgemm);
+
+            if (status != clblast::StatusCode::kSuccess) {
+                GGML_ASSERT(false);
+            }
+
+            // copy dst to host
+            float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
+            CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(float) * d_ne, d, 1, &ev_sgemm, NULL));
+        }
+    }
+
+    if (src0->backend != GGML_BACKEND_CL) {
+        ggml_cl_pool_free(d_X, x_size);
+    }
+    ggml_cl_pool_free(d_Y, y_size);
+    ggml_cl_pool_free(d_D, d_size);
+}
+
+static void ggml_cl_mul_mat_f16(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, void * wdata, size_t /* wsize */) {
+    GGML_ASSERT(fp16_support);
+
+    const int64_t ne00 = src0->ne[0];
+    const int64_t ne01 = src0->ne[1];
+    const int64_t ne02 = src0->ne[2];
+    const int64_t ne03 = src0->ne[3];
+
+    const int64_t ne10 = src1->ne[0];
+    const int64_t ne11 = src1->ne[1];
+
+    const int nb10 = src1->nb[0];
+    const int nb11 = src1->nb[1];
+    const int nb12 = src1->nb[2];
+    const int nb13 = src1->nb[3];
+
+    const int nb2  = dst->nb[2];
+    const int nb3  = dst->nb[3];
+
+    const ggml_fp16_t alpha = ggml_fp32_to_fp16(1.0f);
+    const ggml_fp16_t beta = ggml_fp32_to_fp16(0.0f);
+    const int x_ne = ne01 * ne00;
+    const int y_ne = ne11 * ne10;
+    const int d_ne = ne11 * ne01;
+
+    size_t x_size;
+    size_t y_size;
+    size_t d_size;
+    cl_mem d_X;
+    if (src0->backend == GGML_BACKEND_CL) {
+        d_X = *(cl_mem*) src0->data;
+    } else {
+        d_X = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * x_ne, &x_size, CL_MEM_READ_ONLY);
+    }
+    cl_mem d_Y = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * y_ne, &y_size, CL_MEM_READ_ONLY);
+    cl_mem d_D = ggml_cl_pool_malloc(sizeof(ggml_fp16_t) * d_ne, &d_size, CL_MEM_WRITE_ONLY);
+
+    bool src1_cont_rows = nb10 == sizeof(float);
+    bool src1_cont_cols = (size_t)nb11 == ne11*sizeof(float);
+
+    for (int64_t i03 = 0; i03 < ne03; i03++) {
+        for (int64_t i02 = 0; i02 < ne02; i02++) {
+            // copy src0 to device
+            if (src0->backend != GGML_BACKEND_CL) {
+                CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_X, 0, src0, i03, i02, NULL));
+            }
+
+            // convert src1 to fp16
+            // TODO: use multiple threads
+            ggml_fp16_t * const tmp = (ggml_fp16_t *) wdata + (ne11 * ne10) * (i03 * ne02 + i02);
+            char * src1i = (char *) src1->data + i03*nb13 + i02*nb12;
+            if (src1_cont_rows) {
+                if (src1_cont_cols) {
+                    ggml_fp32_to_fp16_row((float *) src1i, tmp, ne10*ne11);
+                }
+                else {
+                    for (int64_t i01 = 0; i01 < ne11; i01++) {
+                        ggml_fp32_to_fp16_row((float *) (src1i + i01*nb11), tmp + i01*ne10, ne10);
+                    }
+                }
+            }
+            else {
+                for (int64_t i01 = 0; i01 < ne11; i01++) {
+                    for (int64_t i00 = 0; i00 < ne10; i00++) {
+                        // very slow due to no inlining
+                        tmp[i01*ne10 + i00] = ggml_fp32_to_fp16(*(float *) (src1i + i01*nb11 + i00*nb10));
+                    }
+                }
+            }
+
+            // copy src1 to device
+            CL_CHECK(clEnqueueWriteBuffer(queue, d_Y, false, 0, sizeof(ggml_fp16_t) * y_ne, tmp, 0, NULL, NULL));
+
+            CL_CHECK(clFinish(queue));
+
+            // compute
+            cl_event ev_sgemm;
+            clblast::StatusCode status = clblast::Gemm<cl_half>(clblast::Layout::kColMajor,
+                                                       clblast::Transpose::kYes, clblast::Transpose::kNo,
+                                                       ne01, ne11, ne10,
+                                                       alpha,
+                                                       d_X, 0, ne00,
+                                                       d_Y, 0, ne10,
+                                                       beta,
+                                                       d_D, 0, ne01,
+                                                       &queue, &ev_sgemm);
+
+            if (status != clblast::StatusCode::kSuccess) {
+                GGML_ASSERT(false);
+            }
+
+            // copy dst to host, then convert to float
+            CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(ggml_fp16_t) * d_ne, tmp, 1, &ev_sgemm, NULL));
+
+            float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
+
+            ggml_fp16_to_fp32_row(tmp, d, d_ne);
+        }
+    }
+
+    if (src0->backend != GGML_BACKEND_CL) {
+        ggml_cl_pool_free(d_X, x_size);
+    }
+    ggml_cl_pool_free(d_Y, y_size);
+    ggml_cl_pool_free(d_D, d_size);
+}
+
+static void ggml_cl_mul_mat_q_f32(const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
+    const int64_t ne00 = src0->ne[0];
+    const int64_t ne01 = src0->ne[1];
+    const int64_t ne02 = src0->ne[2];
+    const int64_t ne03 = src0->ne[3];
+
+    const int64_t ne10 = src1->ne[0];
+    const int64_t ne11 = src1->ne[1];
+
+    const int nb2  = dst->nb[2];
+    const int nb3  = dst->nb[3];
+    const ggml_type type = src0->type;
+    const bool mul_mat_vec = ne11 == 1;
+
+    const float alpha = 1.0f;
+    const float beta = 0.0f;
+    const int x_ne = ne01 * ne00;
+    const int y_ne = ne11 * ne10;
+    const int d_ne = ne11 * ne01;
+    const size_t q_sz = ggml_type_size(type) * x_ne / ggml_blck_size(type);
+
+    size_t x_size;
+    size_t y_size;
+    size_t d_size;
+    size_t q_size;
+    cl_mem d_X;
+    if (!mul_mat_vec) {
+        d_X = ggml_cl_pool_malloc(sizeof(float) * x_ne, &x_size, CL_MEM_READ_WRITE);
+    }
+    cl_mem d_Y = ggml_cl_pool_malloc(sizeof(float) * y_ne, &y_size, CL_MEM_READ_ONLY);
+    cl_mem d_D = ggml_cl_pool_malloc(sizeof(float) * d_ne, &d_size, CL_MEM_WRITE_ONLY);
+    cl_mem d_Q;
+    if (src0->backend == GGML_BACKEND_CPU) {
+        d_Q = ggml_cl_pool_malloc(q_sz, &q_size, CL_MEM_READ_ONLY);
+    }
+
+    cl_kernel* to_fp32_cl = ggml_get_to_fp32_cl(type);
+    cl_kernel* dmmv = ggml_get_dequantize_mul_mat_vec_cl(type);
+    GGML_ASSERT(to_fp32_cl != nullptr);
+
+    for (int64_t i03 = 0; i03 < ne03; i03++) {
+        for (int64_t i02 = 0; i02 < ne02; i02++) {
+            cl_event ev_sgemm;
+
+            // copy src0 to device if necessary
+            if (src0->backend == GGML_BACKEND_CPU) {
+                CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Q, 0, src0, i03, i02, NULL));
+            } else if (src0->backend == GGML_BACKEND_CL) {
+                d_Q = *(cl_mem*) src0->data;
+            } else {
+                GGML_ASSERT(false);
+            }
+            if (mul_mat_vec) { // specialized dequantize_mul_mat_vec kernel
+                // copy src1 to device
+                CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, NULL));
+
+                // compute
+                const size_t global = ne01 * CL_DMMV_BLOCK_SIZE;
+                const size_t local = CL_DMMV_BLOCK_SIZE;
+                const cl_int ncols = ne00;
+                CL_CHECK(clSetKernelArg(*dmmv, 0, sizeof(cl_mem), &d_Q));
+                CL_CHECK(clSetKernelArg(*dmmv, 1, sizeof(float) * local, NULL));
+                CL_CHECK(clSetKernelArg(*dmmv, 2, sizeof(cl_mem), &d_Y));
+                CL_CHECK(clSetKernelArg(*dmmv, 3, sizeof(cl_mem), &d_D));
+                CL_CHECK(clSetKernelArg(*dmmv, 4, sizeof(cl_int), &ncols));
+                CL_CHECK(clFinish(queue));
+                CL_CHECK(clEnqueueNDRangeKernel(queue, *dmmv, 1, NULL, &global, &local, 0, NULL, &ev_sgemm));
+            } else { // general dequantization kernel + CLBlast matrix matrix multiplication
+                // convert src0 to fp32 on device
+                const size_t global = x_ne;
+                CL_CHECK(clSetKernelArg(*to_fp32_cl, 0, sizeof(cl_mem), &d_Q));
+                CL_CHECK(clSetKernelArg(*to_fp32_cl, 1, sizeof(cl_mem), &d_X));
+                CL_CHECK(clFinish(queue));
+                CL_CHECK(clEnqueueNDRangeKernel(queue, *to_fp32_cl, 1, NULL, &global, NULL, 0, NULL, NULL));
+
+                // copy src1 to device
+                CL_CHECK(ggml_cl_h2d_tensor_2d(queue, d_Y, 0, src1, i03, i02, NULL));
+
+                // wait for conversion
+                CL_CHECK(clFinish(queue));
+
+                // compute
+                clblast::StatusCode status = clblast::Gemm<cl_float>(clblast::Layout::kColMajor,
+                                                           clblast::Transpose::kYes, clblast::Transpose::kNo,
+                                                           ne01, ne11, ne10,
+                                                           alpha,
+                                                           d_X, 0, ne00,
+                                                           d_Y, 0, ne10,
+                                                           beta,
+                                                           d_D, 0, ne01,
+                                                           &queue, &ev_sgemm);
+
+                if (status != clblast::StatusCode::kSuccess) {
+                    GGML_ASSERT(false);
+                }
+            }
+
+            // copy dst to host
+            float * d = (float *) ((char *) dst->data + i02*nb2 + i03*nb3);
+            CL_CHECK(clEnqueueReadBuffer(queue, d_D, true, 0, sizeof(float) * d_ne, d, 1, &ev_sgemm, NULL));
+            clReleaseEvent(ev_sgemm);
+        }
+    }
+
+    if (!mul_mat_vec) {
+        ggml_cl_pool_free(d_X, x_size);
+    }
+    ggml_cl_pool_free(d_Y, y_size);
+    ggml_cl_pool_free(d_D, d_size);
+    if (src0->backend == GGML_BACKEND_CPU) {
+        ggml_cl_pool_free(d_Q, q_size);
+    }
+}
+
+
+bool ggml_cl_can_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) {
+    const int64_t ne10 = src1->ne[0];
+
+    const int64_t ne0 = dst->ne[0];
+    const int64_t ne1 = dst->ne[1];
+
+    // TODO: find the optimal values for these
+    if ((src0->type == GGML_TYPE_F32 || src0->type == GGML_TYPE_F16 || ggml_is_quantized(src0->type)) &&
+        src1->type == GGML_TYPE_F32 &&
+        dst->type == GGML_TYPE_F32 &&
+        ((ne0 >= 32 && ne1 >= 32 && ne10 >= 32) || src0->backend == GGML_BACKEND_CL)) {
+        return true;
+    }
+
+    return false;
+}
+
+bool ggml_cl_mul_mat_use_f16(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * /* dst */) {
+    // If device doesn't support FP16
+    if (!fp16_support) {
+        return false;
+    }
+
+    size_t src0_sz = ggml_nbytes(src0);
+    size_t src1_sz = ggml_nbytes(src1);
+
+    // mul_mat_q: src0 is converted to fp32 on device
+    size_t mul_mat_q_transfer = src0_sz + src1_sz;
+
+    // mul_mat_f16: src1 is converted to fp16 on cpu
+    size_t mul_mat_f16_transfer = src0_sz + sizeof(ggml_fp16_t) * ggml_nelements(src1);
+
+    // choose the smaller one to transfer to the device
+    // TODO: this is not always the best choice due to the overhead of converting to fp16
+    return mul_mat_f16_transfer < mul_mat_q_transfer;
+}
+
+void ggml_cl_mul_mat(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst, void * wdata, size_t wsize) {
+    GGML_ASSERT(ggml_cl_can_mul_mat(src0, src1, dst));
+
+    if (src0->type == GGML_TYPE_F32) {
+        ggml_cl_mul_mat_f32(src0, src1, dst);
+    }
+    else if (src0->type == GGML_TYPE_F16) {
+        if (ggml_cl_mul_mat_use_f16(src0, src1, dst)) {
+            ggml_cl_mul_mat_f16(src0, src1, dst, wdata, wsize);
+        }
+        else {
+            ggml_cl_mul_mat_q_f32(src0, src1, dst);
+        }
+    }
+    else if (ggml_is_quantized(src0->type)) {
+        ggml_cl_mul_mat_q_f32(src0, src1, dst);
+    }
+    else {
+        GGML_ASSERT(false);
+    }
+}
+
+size_t ggml_cl_mul_mat_get_wsize(const struct ggml_tensor * src0, const struct ggml_tensor * src1, struct ggml_tensor * dst) {
+    if (ggml_cl_mul_mat_use_f16(src0, src1, dst)) {
+        return ggml_nelements(src1) * sizeof(ggml_fp16_t);
+    }
+    return 0;
+}
+
+void ggml_cl_transform_tensor(ggml_tensor * tensor) {
+    const int64_t ne0 = tensor->ne[0];
+    const int64_t ne1 = tensor->ne[1];
+    const int64_t ne2 = tensor->ne[2];
+    const int64_t ne3 = tensor->ne[3];
+
+    const ggml_type type = tensor->type;
+    const size_t q_sz = ggml_type_size(type) * ne0 * ne1 * ne2 * ne3 / ggml_blck_size(type);
+
+    size_t q_size;
+    cl_mem* dst = (cl_mem*) malloc(sizeof(cl_mem));
+    *dst = ggml_cl_pool_malloc(q_sz, &q_size, CL_MEM_READ_ONLY);
+
+    // copy tensor to device
+    for (int64_t i3 = 0; i3 < ne3; i3++) {
+        for (int64_t i2 = 0; i2 < ne2; i2++) {
+            int i = i3*ne2 + i2;
+            CL_CHECK(ggml_cl_h2d_tensor_2d(queue, *dst, i*ne0*ne1, tensor, i3, i2, NULL));
+        }
+    }
+
+    CL_CHECK(clFinish(queue));
+
+    tensor->data = dst;
+    tensor->backend = GGML_BACKEND_CL;
+}