opencl: add q4_K gemm and gemv kernels for Adreno (#20919)
* opencl: add q4_K gemm and gemv kernels for Adreno * opencl: fix whitespace * opencl: add workarounds for compiler bugs on older devices * opencl: handle fp16 denorm on X Elite * opencl: fix kernel build error * opencl: fix whitespace * opencl: make q4_K cvt kernels signature consistent --------- Co-authored-by: Li He <lih@qti.qualcomm.com>
This commit is contained in:
shaofeiqi
GitHub
parent
84ae8434d0
commit
08f21453ae
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@ -114,6 +114,8 @@ set(GGML_OPENCL_KERNELS
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gemv_noshuffle_q4_1_f32
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gemm_noshuffle_q4_1_f32
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gemv_noshuffle_general_q8_0_f32
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gemv_noshuffle_q4_k_f32
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gemm_noshuffle_q4_k_f32
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gemv_noshuffle_q6_k_f32
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gemm_noshuffle_q6_k_f32
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mul
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@ -538,6 +538,8 @@ struct ggml_backend_opencl_context {
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cl_kernel kernel_restore_block_q4_0_noshuffle;
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cl_kernel kernel_convert_block_q4_1_noshuffle;
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cl_kernel kernel_restore_block_q4_1_noshuffle;
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cl_kernel kernel_convert_block_q4_K_noshuffle;
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cl_kernel kernel_restore_block_q4_K_noshuffle;
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cl_kernel kernel_convert_block_q4_K, kernel_restore_block_q4_K;
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cl_kernel kernel_convert_block_q6_K, kernel_restore_block_q6_K;
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cl_kernel kernel_mul_mat_q4_0_f32_1d_8x_flat, kernel_mul_mat_q4_0_f32_1d_16x_flat;
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@ -720,6 +722,8 @@ struct ggml_backend_opencl_context {
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cl_kernel kernel_gemm_noshuffle_q4_1_f32;
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cl_kernel kernel_mul_mm_q8_0_f32_8x4;
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cl_kernel CL_mul_mat_vec_q8_0_f32;
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cl_kernel kernel_gemv_noshuffle_q4_k_f32;
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cl_kernel kernel_gemm_noshuffle_q4_k_f32;
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cl_kernel kernel_gemv_noshuffle_q6_K_f32;
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cl_kernel kernel_gemm_noshuffle_q6_K_f32;
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#endif // GGML_OPENCL_USE_ADRENO_KERNELS
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@ -932,6 +936,8 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve
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CL_CHECK((backend_ctx->kernel_restore_block_q8_0_trans = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_q8_0_trans", &err), err));
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CL_CHECK((backend_ctx->kernel_convert_block_q4_K = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_q4_K", &err), err));
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CL_CHECK((backend_ctx->kernel_restore_block_q4_K = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_q4_K", &err), err));
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CL_CHECK((backend_ctx->kernel_convert_block_q4_K_noshuffle = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_q4_K_noshuffle", &err), err));
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CL_CHECK((backend_ctx->kernel_restore_block_q4_K_noshuffle = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_q4_K_noshuffle", &err), err));
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CL_CHECK((backend_ctx->kernel_convert_block_q6_K = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_q6_K", &err), err));
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CL_CHECK((backend_ctx->kernel_restore_block_q6_K = clCreateKernel(backend_ctx->program_cvt, "kernel_restore_block_q6_K", &err), err));
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CL_CHECK((backend_ctx->kernel_convert_block_q6_K_noshuffle = clCreateKernel(backend_ctx->program_cvt, "kernel_convert_block_q6_K_noshuffle", &err), err));
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@ -2619,6 +2625,45 @@ static void load_cl_kernels(ggml_backend_opencl_context *backend_ctx, ggml_cl_ve
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GGML_LOG_CONT(".");
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}
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// gemm_noshuffle_q4_k_f32
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{
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#ifdef GGML_OPENCL_EMBED_KERNELS
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const std::string kernel_src {
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#include "gemm_noshuffle_q4_k_f32.cl.h"
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};
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#else
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const std::string kernel_src = read_file("gemm_noshuffle_q4_k_f32.cl");
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#endif
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cl_program prog = build_program_from_source(backend_ctx->context, backend_ctx->device, kernel_src.c_str(), compile_opts);
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CL_CHECK((backend_ctx->kernel_gemm_noshuffle_q4_k_f32 = clCreateKernel(prog, "kernel_gemm_noshuffle_q4_k_f32", &err), err));
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CL_CHECK(clReleaseProgram(prog));
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GGML_LOG_CONT(".");
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}
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// gemv_noshuffle_q4_k_f32
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{
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std::string CL_gemv_compile_opts = std::string("-cl-std=") + opencl_c_std +
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" -cl-mad-enable ";
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if (backend_ctx->has_vector_subgroup_broadcast) {
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CL_gemv_compile_opts += " -DVECTOR_SUB_GROUP_BROADCAST ";
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}
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#ifdef GGML_OPENCL_EMBED_KERNELS
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const std::string kernel_src {
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#include "gemv_noshuffle_q4_k_f32.cl.h"
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};
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#else
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const std::string kernel_src = read_file("gemv_noshuffle_q4_k_f32.cl");
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#endif
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cl_program prog = build_program_from_source(
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backend_ctx->context, backend_ctx->device, kernel_src.c_str(), CL_gemv_compile_opts);
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CL_CHECK((backend_ctx->kernel_gemv_noshuffle_q4_k_f32 = clCreateKernel(prog, "kernel_gemv_noshuffle_q4_k_f32", &err), err));
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CL_CHECK(clReleaseProgram(prog));
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GGML_LOG_CONT(".");
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}
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std::string CL_moe_compile_opts = std::string("-cl-std=") + opencl_c_std +
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" -cl-mad-enable "
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" -cl-fast-relaxed-math";
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@ -5060,12 +5105,25 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer,
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CL_BUFFER_CREATE_TYPE_REGION, ®ion, &err);
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CL_CHECK(err);
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#ifdef GGML_OPENCL_USE_ADRENO_KERNELS
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cl_kernel kernel = backend_ctx->kernel_convert_block_q4_K;
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if (use_adreno_kernels(backend_ctx, tensor)) {
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kernel = backend_ctx->kernel_convert_block_q4_K_noshuffle;
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}
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#else
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cl_kernel kernel = backend_ctx->kernel_convert_block_q4_K;
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#endif
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cl_uchar mask_0F = 0x0F;
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cl_uchar mask_F0 = 0xF0;
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CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &data_device));
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CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->q));
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CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra->s));
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CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_mem), &extra->d));
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CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &extra->dm));
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CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_uchar), &mask_0F));
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CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_uchar), &mask_F0));
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size_t global_work_size[] = {(size_t)ggml_nelements(tensor)/ggml_blck_size(tensor->type), 1, 1};
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size_t local_work_size[] = {64, 1, 1};
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@ -5076,6 +5134,20 @@ static void ggml_backend_opencl_buffer_set_tensor(ggml_backend_buffer_t buffer,
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CL_CHECK(clReleaseMemObject(data_device));
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tensor->extra = extra;
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#ifdef GGML_OPENCL_USE_ADRENO_KERNELS
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if (use_adreno_kernels(backend_ctx, tensor)) {
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int M = tensor->ne[1];
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int K = tensor->ne[0];
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GGML_ASSERT(K % 32 == 0);
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// Transpose q, d, dm as ushort
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transpose_2d_as_16b(backend_ctx, extra->q, extra->q, size_q, K/4, M);
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transpose_2d_as_16b(backend_ctx, extra->d, extra->d, size_d, K/256, M);
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transpose_2d_as_16b(backend_ctx, extra->dm, extra->dm, size_dm, K/256, M);
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}
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#endif // GGML_OPENCL_USE_ADRENO_KERNELS
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return;
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}
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if (tensor->type == GGML_TYPE_Q6_K) {
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@ -5516,12 +5588,60 @@ static void ggml_backend_opencl_buffer_get_tensor(ggml_backend_buffer_t buffer,
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ggml_nbytes(tensor), NULL, &err);
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CL_CHECK(err);
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cl_uchar mask_0F = 0x0F;
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cl_uchar mask_F0 = 0xF0;
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#ifdef GGML_OPENCL_USE_ADRENO_KERNELS
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if (use_adreno_kernels(backend_ctx, tensor)) {
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int M = tensor->ne[1];
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int K = tensor->ne[0];
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size_t size_q = ggml_nelements(tensor)/ggml_blck_size(tensor->type)*ggml_blck_size(tensor->type)/2;
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size_t size_d = ggml_nelements(tensor)/ggml_blck_size(tensor->type)*sizeof(ggml_fp16_t);
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size_t size_dm = ggml_nelements(tensor)/ggml_blck_size(tensor->type)*sizeof(ggml_fp16_t);
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static ggml_cl_buffer buf_trans_q;
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static ggml_cl_buffer buf_trans_d;
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static ggml_cl_buffer buf_trans_dm;
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buf_trans_q.allocate(backend_ctx->context, size_q);
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buf_trans_d.allocate(backend_ctx->context, size_d);
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buf_trans_dm.allocate(backend_ctx->context, size_dm);
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// Transpose q, d, dm back
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transpose_2d_as_16b(backend_ctx, extra->q, buf_trans_q.buffer, size_q, M, K/4);
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transpose_2d_as_16b(backend_ctx, extra->d, buf_trans_d.buffer, size_d, M, K/256);
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transpose_2d_as_16b(backend_ctx, extra->dm, buf_trans_dm.buffer, size_dm, M, K/256);
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cl_kernel kernel = backend_ctx->kernel_restore_block_q4_K_noshuffle;
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CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &buf_trans_q.buffer));
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CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->s));
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CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &buf_trans_d.buffer));
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CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_mem), &buf_trans_dm.buffer));
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CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &data_device));
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CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_uchar), &mask_0F));
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CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_uchar), &mask_F0));
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size_t global_work_size[] = {(size_t)ggml_nelements(tensor)/ggml_blck_size(tensor->type), 1, 1};
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size_t local_work_size[] = {1, 1, 1};
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CL_CHECK(clEnqueueNDRangeKernel(queue, kernel, 3, NULL,
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global_work_size, local_work_size, 0, NULL, NULL));
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CL_CHECK(clEnqueueReadBuffer(queue, data_device, CL_TRUE, offset,
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size, data, 0, NULL, NULL));
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CL_CHECK(clReleaseMemObject(data_device));
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return;
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}
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#endif // GGML_OPENCL_USE_ADRENO_KERNELS
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cl_kernel kernel = backend_ctx->kernel_restore_block_q4_K;
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CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extra->q));
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CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra->s));
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CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra->d));
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CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_mem), &extra->dm));
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CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &data_device));
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CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_uchar), &mask_0F));
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CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_uchar), &mask_F0));
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size_t global_work_size[] = {(size_t)ggml_nelements(tensor)/ggml_blck_size(tensor->type), 1, 1};
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size_t local_work_size[] = {1, 1, 1};
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@ -9688,6 +9808,192 @@ static void ggml_cl_mul_mat_q8_0_f32_adreno(ggml_backend_t backend, const ggml_t
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#endif
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}
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static void ggml_cl_mul_mat_q4_k_f32_adreno(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
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#ifdef GGML_OPENCL_USE_ADRENO_KERNELS
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GGML_ASSERT(src0);
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GGML_ASSERT(src0->extra);
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GGML_ASSERT(src1);
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GGML_ASSERT(src1->extra);
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GGML_ASSERT(dst);
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GGML_ASSERT(dst->extra);
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ggml_backend_opencl_context *backend_ctx = (ggml_backend_opencl_context *)backend->context;
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ggml_tensor_extra_cl * extra1 = (ggml_tensor_extra_cl *)src1->extra;
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ggml_tensor_extra_cl * extrad = (ggml_tensor_extra_cl *)dst->extra;
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ggml_tensor_extra_cl_q4_K * extra0_q4_k = (ggml_tensor_extra_cl_q4_K *)src0->extra;
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cl_ulong offset1 = extra1->offset + src1->view_offs;
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cl_ulong offsetd = extrad->offset + dst->view_offs;
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const int ne00 = src0->ne[0];
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const int ne01 = src0->ne[1];
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const int ne1 = dst->ne[1];
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GGML_ASSERT(ne00 % ggml_blck_size(src0->type) == 0);
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cl_context context = backend_ctx->context;
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cl_kernel kernel;
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cl_int err;
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cl_image_format img_fmt;
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cl_image_desc img_desc;
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cl_buffer_region region;
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int M = ne01;
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int N = ne1;
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int K = ne00;
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cl_uchar mask_d6 = 0x3F;
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cl_uchar mask_d4 = 0x0F;
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cl_uchar mask_hi2 = 0xC0;
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if (ne1 == 1) {
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cl_mem q_img = nullptr;
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cl_mem b_sub_buf = nullptr;
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cl_mem b_img = nullptr;
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// image for q
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img_fmt = { CL_R, CL_UNSIGNED_INT32};
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memset(&img_desc, 0, sizeof(img_desc));
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img_desc.image_type = CL_MEM_OBJECT_IMAGE1D_BUFFER;
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img_desc.image_width = M * K / 2 / 4;
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img_desc.buffer = extra0_q4_k->q;
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CL_CHECK((q_img = clCreateImage(context, CL_MEM_READ_ONLY, &img_fmt, &img_desc, NULL, &err), err));
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// subbuffer for activations
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region.origin = offset1;
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region.size = K * N * sizeof(float);
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CL_CHECK((b_sub_buf = clCreateSubBuffer(extra1->data_device, 0, CL_BUFFER_CREATE_TYPE_REGION, ®ion, &err), err));
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// image for activations
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img_fmt = {CL_RGBA, CL_FLOAT};
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memset(&img_desc, 0, sizeof(img_desc));
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img_desc.image_type = CL_MEM_OBJECT_IMAGE1D_BUFFER;
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img_desc.image_width = K * N / 4;
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img_desc.buffer = b_sub_buf;
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CL_CHECK((b_img = clCreateImage(context, CL_MEM_READ_ONLY, &img_fmt, &img_desc, NULL, &err), err));
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kernel = backend_ctx->kernel_gemv_noshuffle_q4_k_f32;
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CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &q_img));
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CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra0_q4_k->d));
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CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra0_q4_k->dm));
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CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_mem), &extra0_q4_k->s));
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CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &b_img));
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CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_mem), &extrad->data_device));
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CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_ulong), &offsetd));
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CL_CHECK(clSetKernelArg(kernel, 7, sizeof(cl_int), &ne00));
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CL_CHECK(clSetKernelArg(kernel, 8, sizeof(cl_int), &ne01));
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CL_CHECK(clSetKernelArg(kernel, 9, sizeof(cl_uchar), &mask_d6));
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CL_CHECK(clSetKernelArg(kernel, 10, sizeof(cl_uchar), &mask_d4));
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CL_CHECK(clSetKernelArg(kernel, 11, sizeof(cl_uchar), &mask_hi2));
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size_t local_work_size[3] = {64, 4, 1};
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size_t global_work_size[3] = {(size_t)CEIL_DIV(ne01/2, 64)*64, 4, 1};
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backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
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CL_CHECK(clReleaseMemObject(q_img));
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CL_CHECK(clReleaseMemObject(b_sub_buf));
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CL_CHECK(clReleaseMemObject(b_img));
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} else {
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cl_mem b_sub_buf = nullptr;
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cl_mem b_sub_buf_trans = nullptr;
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cl_mem b_img = nullptr;
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cl_mem b_img_trans = nullptr;
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// subbuffer for activations
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region.origin = offset1;
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region.size = K * N * sizeof(float);
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CL_CHECK((b_sub_buf = clCreateSubBuffer(extra1->data_device, 0, CL_BUFFER_CREATE_TYPE_REGION, ®ion, &err), err));
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// image for activations
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img_fmt = {CL_RGBA, CL_FLOAT};
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memset(&img_desc, 0, sizeof(img_desc));
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img_desc.image_type = CL_MEM_OBJECT_IMAGE1D_BUFFER;
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img_desc.image_width = K * N / 4;
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img_desc.buffer = b_sub_buf;
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CL_CHECK((b_img = clCreateImage(context, CL_MEM_READ_ONLY, &img_fmt, &img_desc, NULL, &err), err));
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// pad N to multiple of 8
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int extra_elements = N % 8;
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int padding = 0;
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if (extra_elements > 0){
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padding = 8 - extra_elements;
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}
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// subbuffer for transposed activations
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region.origin = 0;
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region.size = K * (N + padding) * sizeof(float)/2;
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backend_ctx->prealloc_act_trans.allocate(context, region.size);
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CL_CHECK((b_sub_buf_trans = clCreateSubBuffer(backend_ctx->prealloc_act_trans.buffer, 0, CL_BUFFER_CREATE_TYPE_REGION, ®ion, &err), err));
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// image for transposed activations
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img_fmt = {CL_RGBA, CL_HALF_FLOAT};
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memset(&img_desc, 0, sizeof(img_desc));
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img_desc.image_type = CL_MEM_OBJECT_IMAGE1D_BUFFER;
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img_desc.image_width = K * (N + padding) / 4;
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img_desc.buffer = b_sub_buf_trans;
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CL_CHECK((b_img_trans = clCreateImage(context, 0, &img_fmt, &img_desc, NULL, &err), err));
|
||||
|
||||
// transpose activations
|
||||
int height_B = N/4;
|
||||
if (height_B == 0) {
|
||||
height_B = 1;
|
||||
}
|
||||
int width_B = K/4;
|
||||
int padded_height_B = (N + padding)/4;
|
||||
|
||||
kernel = backend_ctx->kernel_transpose_32_16;
|
||||
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &b_img));
|
||||
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &b_img_trans));
|
||||
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(int), &height_B));
|
||||
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(int), &width_B));
|
||||
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(int), &padded_height_B));
|
||||
|
||||
size_t local_work_size_t[2] = { 1, 16 };
|
||||
size_t global_work_size_t[2] = { (size_t)width_B, (size_t)padded_height_B };
|
||||
backend_ctx->enqueue_ndrange_kernel(kernel, 2, global_work_size_t, local_work_size_t, dst);
|
||||
|
||||
// gemm
|
||||
kernel = backend_ctx->kernel_gemm_noshuffle_q4_k_f32;
|
||||
int padded_N = N + padding;
|
||||
|
||||
CL_CHECK(clSetKernelArg(kernel, 0, sizeof(cl_mem), &extra0_q4_k->q));
|
||||
CL_CHECK(clSetKernelArg(kernel, 1, sizeof(cl_mem), &extra0_q4_k->s));
|
||||
CL_CHECK(clSetKernelArg(kernel, 2, sizeof(cl_mem), &extra0_q4_k->d));
|
||||
CL_CHECK(clSetKernelArg(kernel, 3, sizeof(cl_mem), &extra0_q4_k->dm));
|
||||
CL_CHECK(clSetKernelArg(kernel, 4, sizeof(cl_mem), &b_img_trans));
|
||||
CL_CHECK(clSetKernelArg(kernel, 5, sizeof(cl_mem), &extrad->data_device));
|
||||
CL_CHECK(clSetKernelArg(kernel, 6, sizeof(cl_ulong), &offsetd));
|
||||
CL_CHECK(clSetKernelArg(kernel, 7, sizeof(cl_int), &ne01));
|
||||
CL_CHECK(clSetKernelArg(kernel, 8, sizeof(cl_int), &padded_N));
|
||||
CL_CHECK(clSetKernelArg(kernel, 9, sizeof(cl_int), &ne00));
|
||||
CL_CHECK(clSetKernelArg(kernel, 10, sizeof(cl_int), &ne1));
|
||||
CL_CHECK(clSetKernelArg(kernel, 11, sizeof(cl_uchar), &mask_d6));
|
||||
CL_CHECK(clSetKernelArg(kernel, 12, sizeof(cl_uchar), &mask_d4));
|
||||
CL_CHECK(clSetKernelArg(kernel, 13, sizeof(cl_uchar), &mask_hi2));
|
||||
|
||||
size_t global_work_size[3] = {(size_t)CEIL_DIV(ne1, 8), (size_t)CEIL_DIV(ne01, 4), 1};
|
||||
size_t local_work_size[3] = {1, 128, 1};
|
||||
|
||||
backend_ctx->enqueue_ndrange_kernel(kernel, 3, global_work_size, local_work_size, dst);
|
||||
CL_CHECK(clReleaseMemObject(b_sub_buf));
|
||||
CL_CHECK(clReleaseMemObject(b_sub_buf_trans));
|
||||
CL_CHECK(clReleaseMemObject(b_img));
|
||||
CL_CHECK(clReleaseMemObject(b_img_trans));
|
||||
}
|
||||
#else
|
||||
GGML_UNUSED(backend);
|
||||
GGML_UNUSED(src0);
|
||||
GGML_UNUSED(src1);
|
||||
GGML_UNUSED(dst);
|
||||
#endif
|
||||
}
|
||||
|
||||
static void ggml_cl_mul_mat_q6_K_f32_adreno(ggml_backend_t backend, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
|
||||
#ifdef GGML_OPENCL_USE_ADRENO_KERNELS
|
||||
GGML_ASSERT(src0);
|
||||
|
|
@ -10014,6 +10320,12 @@ static void ggml_cl_mul_mat(ggml_backend_t backend, const ggml_tensor * src0, co
|
|||
return;
|
||||
}
|
||||
|
||||
// q4_k x fp32
|
||||
if (src0t == GGML_TYPE_Q4_K && src1t == GGML_TYPE_F32) {
|
||||
ggml_cl_mul_mat_q4_k_f32_adreno(backend, src0, src1, dst);
|
||||
return;
|
||||
}
|
||||
|
||||
// q6_K x fp32
|
||||
if (src0t == GGML_TYPE_Q6_K && src1t == GGML_TYPE_F32) {
|
||||
ggml_cl_mul_mat_q6_K_f32_adreno(backend, src0, src1, dst);
|
||||
|
|
|
|||
|
|
@ -424,13 +424,17 @@ kernel void kernel_restore_block_q8_0_trans(
|
|||
// Convert the block_q4_K format to 4 separate arrays (AOS -> SOA).
|
||||
// This kernel does not deshuffle the bits.
|
||||
// Each thread processes a super block.
|
||||
// Mask args are just to keep the signature consistent with the no-shuffle
|
||||
// version and they are not used in this kernel.
|
||||
//------------------------------------------------------------------------------
|
||||
kernel void kernel_convert_block_q4_K(
|
||||
global struct block_q4_K * src0,
|
||||
global uchar * dst_q,
|
||||
global uchar * dst_s,
|
||||
global half * dst_d,
|
||||
global half * dst_dm
|
||||
global half * dst_dm,
|
||||
uchar mask_0F,
|
||||
uchar mask_F0
|
||||
) {
|
||||
global struct block_q4_K * b = (global struct block_q4_K *) src0 + get_global_id(0);
|
||||
global uchar * q = (global uchar *) dst_q + QK_K/2*get_global_id(0);
|
||||
|
|
@ -451,12 +455,15 @@ kernel void kernel_convert_block_q4_K(
|
|||
|
||||
// Restore block_q4_K from flattened arrays.
|
||||
// Each thread processes a super block.
|
||||
// Mask args are just to keep the signature consistent with the no-shuffle ones.
|
||||
kernel void kernel_restore_block_q4_K(
|
||||
global uchar * src_q,
|
||||
global uchar * src_s,
|
||||
global half * src_d,
|
||||
global half * src_dm,
|
||||
global struct block_q4_K * dst
|
||||
global struct block_q4_K * dst,
|
||||
uchar mask_0F,
|
||||
uchar mask_F0
|
||||
) {
|
||||
global struct block_q4_K * b = (global struct block_q4_K *) dst + get_global_id(0);
|
||||
global uchar * q = (global uchar *) src_q + QK_K/2*get_global_id(0);
|
||||
|
|
@ -475,6 +482,70 @@ kernel void kernel_restore_block_q4_K(
|
|||
}
|
||||
}
|
||||
|
||||
kernel void kernel_convert_block_q4_K_noshuffle(
|
||||
global struct block_q4_K * src0,
|
||||
global uchar * dst_q,
|
||||
global uchar * dst_s,
|
||||
global half * dst_d,
|
||||
global half * dst_dm,
|
||||
uchar mask_0F,
|
||||
uchar mask_F0
|
||||
) {
|
||||
global struct block_q4_K * b = (global struct block_q4_K *) src0 + get_global_id(0);
|
||||
global uchar * q = (global uchar *) dst_q + QK_K/2 * get_global_id(0);
|
||||
global uchar * s = (global uchar *) dst_s + K_SCALE_SIZE * get_global_id(0);
|
||||
global half * d = (global half *) dst_d + get_global_id(0);
|
||||
global half * dm = (global half *) dst_dm + get_global_id(0);
|
||||
|
||||
*d = b->d;
|
||||
*dm = b->dm;
|
||||
|
||||
for (int i = 0; i < QK_K / 64; ++i) {
|
||||
for (int j = 0; j < 16; ++j) {
|
||||
uchar x0 = b->q[i*32 + 2*j];
|
||||
uchar x1 = b->q[i*32 + 2*j + 1];
|
||||
q[i*32 + j] = convert_uchar(x0 & mask_0F) | convert_uchar((x1 & mask_0F) << 4);
|
||||
q[i*32 + j + 16] = convert_uchar((x0 & mask_F0) >> 4) | convert_uchar(x1 & mask_F0);
|
||||
}
|
||||
}
|
||||
|
||||
for (int i = 0; i < K_SCALE_SIZE; ++i) {
|
||||
s[i] = b->s[i];
|
||||
}
|
||||
}
|
||||
|
||||
kernel void kernel_restore_block_q4_K_noshuffle(
|
||||
global uchar * src_q,
|
||||
global uchar * src_s,
|
||||
global half * src_d,
|
||||
global half * src_dm,
|
||||
global struct block_q4_K * dst,
|
||||
uchar mask_0F,
|
||||
uchar mask_F0
|
||||
) {
|
||||
global struct block_q4_K * b = (global struct block_q4_K *) dst + get_global_id(0);
|
||||
global uchar * q = (global uchar *) src_q + QK_K/2 * get_global_id(0);
|
||||
global uchar * s = (global uchar *) src_s + K_SCALE_SIZE * get_global_id(0);
|
||||
global half * d = (global half *) src_d + get_global_id(0);
|
||||
global half * dm = (global half *) src_dm + get_global_id(0);
|
||||
|
||||
b->d = *d;
|
||||
b->dm = *dm;
|
||||
|
||||
for (int i = 0; i < QK_K / 64; ++i) {
|
||||
for (int j = 0; j < 16; ++j) {
|
||||
uchar lo = q[i*32 + j];
|
||||
uchar hi = q[i*32 + j + 16];
|
||||
b->q[i*32 + 2*j] = convert_uchar((lo & mask_0F) | ((hi & mask_0F) << 4));
|
||||
b->q[i*32 + 2*j + 1] = convert_uchar(((lo & mask_F0) >> 4) | (hi & mask_F0));
|
||||
}
|
||||
}
|
||||
|
||||
for (int i = 0; i < K_SCALE_SIZE; ++i) {
|
||||
b->s[i] = s[i];
|
||||
}
|
||||
}
|
||||
|
||||
//------------------------------------------------------------------------------
|
||||
// kernel_convert_block_q6_K
|
||||
// Convert the block_q6_K format to 3 separate arrays (AOS -> SOA).
|
||||
|
|
|
|||
|
|
@ -0,0 +1,172 @@
|
|||
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
|
||||
|
||||
#ifdef cl_qcom_reqd_sub_group_size
|
||||
#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
|
||||
#define ADRENO_GPU 1
|
||||
#define REQD_SUBGROUP_SIZE_128 __attribute__((qcom_reqd_sub_group_size("full")))
|
||||
#endif
|
||||
#define QK_K 256
|
||||
#define K_SCALE_SIZE 12
|
||||
|
||||
inline void get_scale_min_k4(
|
||||
int j,
|
||||
global const uchar * q,
|
||||
uchar * d,
|
||||
uchar * m,
|
||||
uchar mask_d6,
|
||||
uchar mask_d4,
|
||||
uchar mask_hi2
|
||||
) {
|
||||
if (j < 4) {
|
||||
*d = q[j] & mask_d6;
|
||||
*m = q[j+4] & mask_d6;
|
||||
} else {
|
||||
*d = (q[j+4] & mask_d4) | ((q[j-4] & mask_hi2) >> 2);
|
||||
*m = ((q[j+4] >> 4) & mask_d4) | ((q[j] & mask_hi2) >> 2);
|
||||
}
|
||||
}
|
||||
|
||||
#ifdef ADRENO_GPU
|
||||
REQD_SUBGROUP_SIZE_128
|
||||
#endif
|
||||
kernel void kernel_gemm_noshuffle_q4_k_f32(
|
||||
global const ushort * src0_q,
|
||||
global const uchar * src0_s,
|
||||
global const half * src0_d,
|
||||
global const half * src0_dm,
|
||||
read_only image1d_buffer_t src1,
|
||||
global float * dst,
|
||||
ulong offsetd,
|
||||
int m,
|
||||
int n,
|
||||
int k,
|
||||
int n_no_padding,
|
||||
uchar mask_d6,
|
||||
uchar mask_d4,
|
||||
uchar mask_hi2
|
||||
) {
|
||||
dst = (global float *)((global char *)dst + offsetd);
|
||||
int n_4 = n >> 2;
|
||||
int gy = get_global_id(0);
|
||||
int gx = get_global_id(1);
|
||||
int gx_2 = gx << 2;
|
||||
|
||||
half8 c0 = 0, c1 = 0, c2 = 0, c3 = 0;
|
||||
half8 B;
|
||||
half4 dequantized_weights;
|
||||
|
||||
int num_blocks_K = k / QK_K;
|
||||
|
||||
global const ushort * weight_ptr = src0_q + gx_2;
|
||||
global const half * d_ptr = src0_d + gx_2;
|
||||
global const half * dm_ptr = src0_dm + gx_2;
|
||||
|
||||
for (int i = 0; i < k; i += 32) {
|
||||
int sb_idx = i / QK_K;
|
||||
int sub_idx = (i / 32) % 8;
|
||||
|
||||
half4 d = vload4(0, d_ptr + sb_idx * m);
|
||||
half4 dm = vload4(0, dm_ptr + sb_idx * m);
|
||||
|
||||
global const uchar * sc0 = src0_s + (gx_2+0) * num_blocks_K * K_SCALE_SIZE + sb_idx * K_SCALE_SIZE;
|
||||
global const uchar * sc1 = src0_s + (gx_2+1) * num_blocks_K * K_SCALE_SIZE + sb_idx * K_SCALE_SIZE;
|
||||
global const uchar * sc2 = src0_s + (gx_2+2) * num_blocks_K * K_SCALE_SIZE + sb_idx * K_SCALE_SIZE;
|
||||
global const uchar * sc3 = src0_s + (gx_2+3) * num_blocks_K * K_SCALE_SIZE + sb_idx * K_SCALE_SIZE;
|
||||
|
||||
uchar sv0, mn0, sv1, mn1, sv2, mn2, sv3, mn3;
|
||||
get_scale_min_k4(sub_idx, sc0, &sv0, &mn0, mask_d6, mask_d4, mask_hi2);
|
||||
get_scale_min_k4(sub_idx, sc1, &sv1, &mn1, mask_d6, mask_d4, mask_hi2);
|
||||
get_scale_min_k4(sub_idx, sc2, &sv2, &mn2, mask_d6, mask_d4, mask_hi2);
|
||||
get_scale_min_k4(sub_idx, sc3, &sv3, &mn3, mask_d6, mask_d4, mask_hi2);
|
||||
|
||||
half4 scale = convert_half4(convert_float4(d) * convert_float4((uchar4)(sv0, sv1, sv2, sv3)));
|
||||
half4 mval = convert_half4(convert_float4(dm) * convert_float4((uchar4)(mn0, mn1, mn2, mn3)));
|
||||
|
||||
for (int l = 0; l < 32; l += 4) {
|
||||
int ki = i + l;
|
||||
ushort4 bits4 = vload4(0, weight_ptr + (ki/4) * m);
|
||||
|
||||
// j=0
|
||||
B.s0123 = read_imageh(src1, gy*2 + (ki+0) * n_4);
|
||||
B.s4567 = read_imageh(src1, gy*2+1 + (ki+0) * n_4);
|
||||
dequantized_weights.s0 = (bits4.s0 & 0x000F) * scale.s0 - mval.s0;
|
||||
dequantized_weights.s1 = (bits4.s1 & 0x000F) * scale.s1 - mval.s1;
|
||||
dequantized_weights.s2 = (bits4.s2 & 0x000F) * scale.s2 - mval.s2;
|
||||
dequantized_weights.s3 = (bits4.s3 & 0x000F) * scale.s3 - mval.s3;
|
||||
c0 += B * dequantized_weights.s0;
|
||||
c1 += B * dequantized_weights.s1;
|
||||
c2 += B * dequantized_weights.s2;
|
||||
c3 += B * dequantized_weights.s3;
|
||||
|
||||
// j=1
|
||||
B.s0123 = read_imageh(src1, gy*2 + (ki+1) * n_4);
|
||||
B.s4567 = read_imageh(src1, gy*2+1 + (ki+1) * n_4);
|
||||
dequantized_weights.s0 = ((bits4.s0 & 0x00F0) >> 4) * scale.s0 - mval.s0;
|
||||
dequantized_weights.s1 = ((bits4.s1 & 0x00F0) >> 4) * scale.s1 - mval.s1;
|
||||
dequantized_weights.s2 = ((bits4.s2 & 0x00F0) >> 4) * scale.s2 - mval.s2;
|
||||
dequantized_weights.s3 = ((bits4.s3 & 0x00F0) >> 4) * scale.s3 - mval.s3;
|
||||
c0 += B * dequantized_weights.s0;
|
||||
c1 += B * dequantized_weights.s1;
|
||||
c2 += B * dequantized_weights.s2;
|
||||
c3 += B * dequantized_weights.s3;
|
||||
|
||||
// j=2
|
||||
B.s0123 = read_imageh(src1, gy*2 + (ki+2) * n_4);
|
||||
B.s4567 = read_imageh(src1, gy*2+1 + (ki+2) * n_4);
|
||||
dequantized_weights.s0 = ((bits4.s0 & 0x0F00) >> 8) * scale.s0 - mval.s0;
|
||||
dequantized_weights.s1 = ((bits4.s1 & 0x0F00) >> 8) * scale.s1 - mval.s1;
|
||||
dequantized_weights.s2 = ((bits4.s2 & 0x0F00) >> 8) * scale.s2 - mval.s2;
|
||||
dequantized_weights.s3 = ((bits4.s3 & 0x0F00) >> 8) * scale.s3 - mval.s3;
|
||||
c0 += B * dequantized_weights.s0;
|
||||
c1 += B * dequantized_weights.s1;
|
||||
c2 += B * dequantized_weights.s2;
|
||||
c3 += B * dequantized_weights.s3;
|
||||
|
||||
// j=3
|
||||
B.s0123 = read_imageh(src1, gy*2 + (ki+3) * n_4);
|
||||
B.s4567 = read_imageh(src1, gy*2+1 + (ki+3) * n_4);
|
||||
dequantized_weights.s0 = ((bits4.s0 & 0xF000) >> 12) * scale.s0 - mval.s0;
|
||||
dequantized_weights.s1 = ((bits4.s1 & 0xF000) >> 12) * scale.s1 - mval.s1;
|
||||
dequantized_weights.s2 = ((bits4.s2 & 0xF000) >> 12) * scale.s2 - mval.s2;
|
||||
dequantized_weights.s3 = ((bits4.s3 & 0xF000) >> 12) * scale.s3 - mval.s3;
|
||||
c0 += B * dequantized_weights.s0;
|
||||
c1 += B * dequantized_weights.s1;
|
||||
c2 += B * dequantized_weights.s2;
|
||||
c3 += B * dequantized_weights.s3;
|
||||
}
|
||||
}
|
||||
|
||||
int idx = (gy<<3)*m + (gx<<2);
|
||||
|
||||
if (idx+3 < m*n_no_padding) {
|
||||
vstore4((float4)(c0.s0, c1.s0, c2.s0, c3.s0), 0, dst + idx);
|
||||
idx += m;
|
||||
}
|
||||
if (idx+3 < m*n_no_padding) {
|
||||
vstore4((float4)(c0.s1, c1.s1, c2.s1, c3.s1), 0, dst + idx);
|
||||
idx += m;
|
||||
}
|
||||
if (idx+3 < m*n_no_padding) {
|
||||
vstore4((float4)(c0.s2, c1.s2, c2.s2, c3.s2), 0, dst + idx);
|
||||
idx += m;
|
||||
}
|
||||
if (idx+3 < m*n_no_padding) {
|
||||
vstore4((float4)(c0.s3, c1.s3, c2.s3, c3.s3), 0, dst + idx);
|
||||
idx += m;
|
||||
}
|
||||
if (idx+3 < m*n_no_padding) {
|
||||
vstore4((float4)(c0.s4, c1.s4, c2.s4, c3.s4), 0, dst + idx);
|
||||
idx += m;
|
||||
}
|
||||
if (idx+3 < m*n_no_padding) {
|
||||
vstore4((float4)(c0.s5, c1.s5, c2.s5, c3.s5), 0, dst + idx);
|
||||
idx += m;
|
||||
}
|
||||
if (idx+3 < m*n_no_padding) {
|
||||
vstore4((float4)(c0.s6, c1.s6, c2.s6, c3.s6), 0, dst + idx);
|
||||
idx += m;
|
||||
}
|
||||
if (idx+3 < m*n_no_padding) {
|
||||
vstore4((float4)(c0.s7, c1.s7, c2.s7, c3.s7), 0, dst + idx);
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,318 @@
|
|||
#pragma OPENCL EXTENSION cl_khr_fp16 : enable
|
||||
#pragma OPENCL EXTENSION cl_khr_subgroups : enable
|
||||
|
||||
#ifdef cl_qcom_reqd_sub_group_size
|
||||
#pragma OPENCL EXTENSION cl_qcom_reqd_sub_group_size : enable
|
||||
#define ADRENO_GPU 1
|
||||
#define REQD_SUBGROUP_SIZE_64 __attribute__((qcom_reqd_sub_group_size("half")))
|
||||
#endif
|
||||
|
||||
#define QK_K 256
|
||||
#define NSUBGROUPS 4
|
||||
#define SUBGROUP_SIZE 64
|
||||
|
||||
inline void get_scale_min_k4(
|
||||
int j,
|
||||
global const uchar * q,
|
||||
uchar * d,
|
||||
uchar * m,
|
||||
uchar mask_d6,
|
||||
uchar mask_d4,
|
||||
uchar mask_hi2
|
||||
) {
|
||||
if (j < 4) {
|
||||
*d = q[j] & mask_d6;
|
||||
*m = q[j+4] & mask_d6;
|
||||
} else {
|
||||
*d = (q[j+4] & mask_d4) | ((q[j-4] & mask_hi2) >> 2);
|
||||
*m = ((q[j+4] >> 4) & mask_d4) | ((q[j] & mask_hi2) >> 2);
|
||||
}
|
||||
}
|
||||
|
||||
#define dequantizeBlockAccum_ns_sgbroadcast_1_hi(total_sums, bits4, scale, minv, y) \
|
||||
float shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s0, 0); \
|
||||
total_sums.s0 += ((bits4.s0 & 0x000F) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += ((bits4.s1 & 0x000F) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s1, 0); \
|
||||
total_sums.s0 += (((bits4.s0 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s1 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s2, 0); \
|
||||
total_sums.s0 += (((bits4.s0 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s1 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s3, 0); \
|
||||
total_sums.s0 += (((bits4.s0 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s1 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s4, 0); \
|
||||
total_sums.s0 += ((bits4.s2 & 0x000F) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += ((bits4.s3 & 0x000F) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s5, 0); \
|
||||
total_sums.s0 += (((bits4.s2 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s3 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s6, 0); \
|
||||
total_sums.s0 += (((bits4.s2 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s3 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s7, 0); \
|
||||
total_sums.s0 += (((bits4.s2 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s3 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s0, 1); \
|
||||
total_sums.s0 += ((bits4.s4 & 0x000F) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += ((bits4.s5 & 0x000F) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s1, 1); \
|
||||
total_sums.s0 += (((bits4.s4 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s5 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s2, 1); \
|
||||
total_sums.s0 += (((bits4.s4 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s5 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s3, 1); \
|
||||
total_sums.s0 += (((bits4.s4 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s5 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s4, 1); \
|
||||
total_sums.s0 += ((bits4.s6 & 0x000F) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += ((bits4.s7 & 0x000F) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s5, 1); \
|
||||
total_sums.s0 += (((bits4.s6 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s7 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s6, 1); \
|
||||
total_sums.s0 += (((bits4.s6 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s7 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s7, 1); \
|
||||
total_sums.s0 += (((bits4.s6 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s7 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y; \
|
||||
|
||||
|
||||
#define dequantizeBlockAccum_ns_sgbroadcast_1_lo(total_sums, bits4, scale, minv, y) \
|
||||
shared_y = sub_group_broadcast(y.s0, 2); \
|
||||
total_sums.s0 += ((bits4.s0 & 0x000F) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += ((bits4.s1 & 0x000F) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s1, 2); \
|
||||
total_sums.s0 += (((bits4.s0 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s1 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s2, 2); \
|
||||
total_sums.s0 += (((bits4.s0 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s1 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s3, 2); \
|
||||
total_sums.s0 += (((bits4.s0 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s1 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s4, 2); \
|
||||
total_sums.s0 += ((bits4.s2 & 0x000F) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += ((bits4.s3 & 0x000F) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s5, 2); \
|
||||
total_sums.s0 += (((bits4.s2 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s3 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s6, 2); \
|
||||
total_sums.s0 += (((bits4.s2 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s3 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s7, 2); \
|
||||
total_sums.s0 += (((bits4.s2 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s3 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s0, 3); \
|
||||
total_sums.s0 += ((bits4.s4 & 0x000F) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += ((bits4.s5 & 0x000F) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s1, 3); \
|
||||
total_sums.s0 += (((bits4.s4 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s5 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s2, 3); \
|
||||
total_sums.s0 += (((bits4.s4 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s5 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s3, 3); \
|
||||
total_sums.s0 += (((bits4.s4 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s5 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s4, 3); \
|
||||
total_sums.s0 += ((bits4.s6 & 0x000F) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += ((bits4.s7 & 0x000F) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s5, 3); \
|
||||
total_sums.s0 += (((bits4.s6 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s7 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s6, 3); \
|
||||
total_sums.s0 += (((bits4.s6 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s7 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y; \
|
||||
shared_y = sub_group_broadcast(y.s7, 3); \
|
||||
total_sums.s0 += (((bits4.s6 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y; \
|
||||
total_sums.s1 += (((bits4.s7 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y; \
|
||||
|
||||
|
||||
#define dequantizeBlockAccum_ns_sgbroadcast_8_hi(total_sums, bits4, scale, minv, y) \
|
||||
float8 shared_y; \
|
||||
shared_y = sub_group_broadcast(y, 0); \
|
||||
total_sums.s0 += ((bits4.s0 & 0x000F) * scale.s0 - minv.s0) * shared_y.s0; \
|
||||
total_sums.s0 += (((bits4.s0 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y.s1; \
|
||||
total_sums.s0 += (((bits4.s0 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y.s2; \
|
||||
total_sums.s0 += (((bits4.s0 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y.s3; \
|
||||
total_sums.s0 += ((bits4.s2 & 0x000F) * scale.s0 - minv.s0) * shared_y.s4; \
|
||||
total_sums.s0 += (((bits4.s2 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y.s5; \
|
||||
total_sums.s0 += (((bits4.s2 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y.s6; \
|
||||
total_sums.s0 += (((bits4.s2 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y.s7; \
|
||||
total_sums.s1 += ((bits4.s1 & 0x000F) * scale.s1 - minv.s1) * shared_y.s0; \
|
||||
total_sums.s1 += (((bits4.s1 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y.s1; \
|
||||
total_sums.s1 += (((bits4.s1 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y.s2; \
|
||||
total_sums.s1 += (((bits4.s1 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y.s3; \
|
||||
total_sums.s1 += ((bits4.s3 & 0x000F) * scale.s1 - minv.s1) * shared_y.s4; \
|
||||
total_sums.s1 += (((bits4.s3 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y.s5; \
|
||||
total_sums.s1 += (((bits4.s3 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y.s6; \
|
||||
total_sums.s1 += (((bits4.s3 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y.s7; \
|
||||
shared_y = sub_group_broadcast(y, 1); \
|
||||
total_sums.s0 += ((bits4.s4 & 0x000F) * scale.s0 - minv.s0) * shared_y.s0; \
|
||||
total_sums.s0 += (((bits4.s4 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y.s1; \
|
||||
total_sums.s0 += (((bits4.s4 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y.s2; \
|
||||
total_sums.s0 += (((bits4.s4 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y.s3; \
|
||||
total_sums.s0 += ((bits4.s6 & 0x000F) * scale.s0 - minv.s0) * shared_y.s4; \
|
||||
total_sums.s0 += (((bits4.s6 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y.s5; \
|
||||
total_sums.s0 += (((bits4.s6 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y.s6; \
|
||||
total_sums.s0 += (((bits4.s6 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y.s7; \
|
||||
total_sums.s1 += ((bits4.s5 & 0x000F) * scale.s1 - minv.s1) * shared_y.s0; \
|
||||
total_sums.s1 += (((bits4.s5 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y.s1; \
|
||||
total_sums.s1 += (((bits4.s5 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y.s2; \
|
||||
total_sums.s1 += (((bits4.s5 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y.s3; \
|
||||
total_sums.s1 += ((bits4.s7 & 0x000F) * scale.s1 - minv.s1) * shared_y.s4; \
|
||||
total_sums.s1 += (((bits4.s7 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y.s5; \
|
||||
total_sums.s1 += (((bits4.s7 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y.s6; \
|
||||
total_sums.s1 += (((bits4.s7 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y.s7; \
|
||||
|
||||
|
||||
#define dequantizeBlockAccum_ns_sgbroadcast_8_lo(total_sums, bits4, scale, minv, y) \
|
||||
shared_y = sub_group_broadcast(y, 2); \
|
||||
total_sums.s0 += ((bits4.s0 & 0x000F) * scale.s0 - minv.s0) * shared_y.s0; \
|
||||
total_sums.s0 += (((bits4.s0 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y.s1; \
|
||||
total_sums.s0 += (((bits4.s0 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y.s2; \
|
||||
total_sums.s0 += (((bits4.s0 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y.s3; \
|
||||
total_sums.s0 += ((bits4.s2 & 0x000F) * scale.s0 - minv.s0) * shared_y.s4; \
|
||||
total_sums.s0 += (((bits4.s2 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y.s5; \
|
||||
total_sums.s0 += (((bits4.s2 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y.s6; \
|
||||
total_sums.s0 += (((bits4.s2 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y.s7; \
|
||||
total_sums.s1 += ((bits4.s1 & 0x000F) * scale.s1 - minv.s1) * shared_y.s0; \
|
||||
total_sums.s1 += (((bits4.s1 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y.s1; \
|
||||
total_sums.s1 += (((bits4.s1 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y.s2; \
|
||||
total_sums.s1 += (((bits4.s1 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y.s3; \
|
||||
total_sums.s1 += ((bits4.s3 & 0x000F) * scale.s1 - minv.s1) * shared_y.s4; \
|
||||
total_sums.s1 += (((bits4.s3 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y.s5; \
|
||||
total_sums.s1 += (((bits4.s3 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y.s6; \
|
||||
total_sums.s1 += (((bits4.s3 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y.s7; \
|
||||
shared_y = sub_group_broadcast(y, 3); \
|
||||
total_sums.s0 += ((bits4.s4 & 0x000F) * scale.s0 - minv.s0) * shared_y.s0; \
|
||||
total_sums.s0 += (((bits4.s4 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y.s1; \
|
||||
total_sums.s0 += (((bits4.s4 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y.s2; \
|
||||
total_sums.s0 += (((bits4.s4 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y.s3; \
|
||||
total_sums.s0 += ((bits4.s6 & 0x000F) * scale.s0 - minv.s0) * shared_y.s4; \
|
||||
total_sums.s0 += (((bits4.s6 & 0x00F0) >> 4) * scale.s0 - minv.s0) * shared_y.s5; \
|
||||
total_sums.s0 += (((bits4.s6 & 0x0F00) >> 8) * scale.s0 - minv.s0) * shared_y.s6; \
|
||||
total_sums.s0 += (((bits4.s6 & 0xF000) >> 12) * scale.s0 - minv.s0) * shared_y.s7; \
|
||||
total_sums.s1 += ((bits4.s5 & 0x000F) * scale.s1 - minv.s1) * shared_y.s0; \
|
||||
total_sums.s1 += (((bits4.s5 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y.s1; \
|
||||
total_sums.s1 += (((bits4.s5 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y.s2; \
|
||||
total_sums.s1 += (((bits4.s5 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y.s3; \
|
||||
total_sums.s1 += ((bits4.s7 & 0x000F) * scale.s1 - minv.s1) * shared_y.s4; \
|
||||
total_sums.s1 += (((bits4.s7 & 0x00F0) >> 4) * scale.s1 - minv.s1) * shared_y.s5; \
|
||||
total_sums.s1 += (((bits4.s7 & 0x0F00) >> 8) * scale.s1 - minv.s1) * shared_y.s6; \
|
||||
total_sums.s1 += (((bits4.s7 & 0xF000) >> 12) * scale.s1 - minv.s1) * shared_y.s7; \
|
||||
|
||||
#ifdef ADRENO_GPU
|
||||
REQD_SUBGROUP_SIZE_64
|
||||
#endif
|
||||
kernel void kernel_gemv_noshuffle_q4_k_f32(
|
||||
read_only image1d_buffer_t src0_q,
|
||||
global half2 * src0_d,
|
||||
global half2 * src0_m,
|
||||
global uchar * src0_s,
|
||||
read_only image1d_buffer_t src1,
|
||||
global float * dst,
|
||||
ulong offsetd,
|
||||
int ne00,
|
||||
int ne01,
|
||||
uchar mask_d6,
|
||||
uchar mask_d4,
|
||||
uchar mask_hi2)
|
||||
{
|
||||
uint groupId = get_local_id(1);
|
||||
uint gid = get_global_id(0);
|
||||
ushort slid = get_sub_group_local_id();
|
||||
|
||||
uint K = ne00;
|
||||
uint M = ne01;
|
||||
|
||||
uint LINE_STRIDE_A = M / 2;
|
||||
uint BLOCK_STRIDE_A = NSUBGROUPS * M;
|
||||
uint scales_per_row = (K / QK_K) * 12;
|
||||
|
||||
private uint4 regA;
|
||||
private half2 regS;
|
||||
private half2 regM;
|
||||
private float8 regB;
|
||||
|
||||
private float2 totalSum = (float2)(0.0f);
|
||||
|
||||
for (uint k = groupId; k < (K / 32); k += NSUBGROUPS) {
|
||||
uint sb = k / 8;
|
||||
uint j = k % 8;
|
||||
|
||||
half2 d = src0_d[gid + sb * LINE_STRIDE_A];
|
||||
half2 dm = src0_m[gid + sb * LINE_STRIDE_A];
|
||||
|
||||
global const uchar * sc0 = src0_s + 2 * gid * scales_per_row + sb * 12;
|
||||
global const uchar * sc1 = src0_s + (2 * gid + 1) * scales_per_row + sb * 12;
|
||||
|
||||
uchar sv0, mn0, sv1, mn1;
|
||||
get_scale_min_k4(j, sc0, &sv0, &mn0, mask_d6, mask_d4, mask_hi2);
|
||||
get_scale_min_k4(j, sc1, &sv1, &mn1, mask_d6, mask_d4, mask_hi2);
|
||||
|
||||
regS = convert_half2(convert_float2(d) * convert_float2((uchar2)(sv0, sv1)));
|
||||
regM = convert_half2(convert_float2(dm) * convert_float2((uchar2)(mn0, mn1)));
|
||||
|
||||
if (slid < 4) {
|
||||
regB.s0123 = read_imagef(src1, (slid * 2 + k * 8));
|
||||
regB.s4567 = read_imagef(src1, (1 + slid * 2 + k * 8));
|
||||
}
|
||||
|
||||
// load half weights for two blocks in consecutive rows
|
||||
regA.s0 = read_imageui(src0_q, (gid + k * BLOCK_STRIDE_A + LINE_STRIDE_A * 0)).x;
|
||||
regA.s1 = read_imageui(src0_q, (gid + k * BLOCK_STRIDE_A + LINE_STRIDE_A * 1)).x;
|
||||
regA.s2 = read_imageui(src0_q, (gid + k * BLOCK_STRIDE_A + LINE_STRIDE_A * 2)).x;
|
||||
regA.s3 = read_imageui(src0_q, (gid + k * BLOCK_STRIDE_A + LINE_STRIDE_A * 3)).x;
|
||||
#ifdef VECTOR_SUB_GROUP_BROADCAST
|
||||
dequantizeBlockAccum_ns_sgbroadcast_8_hi(totalSum, as_ushort8(regA), regS, regM, regB);
|
||||
#else
|
||||
dequantizeBlockAccum_ns_sgbroadcast_1_hi(totalSum, as_ushort8(regA), regS, regM, regB);
|
||||
#endif // VECTOR_SUB_GROUP_BROADCAST
|
||||
|
||||
regA.s0 = read_imageui(src0_q, (gid + k * BLOCK_STRIDE_A + LINE_STRIDE_A * 4)).x;
|
||||
regA.s1 = read_imageui(src0_q, (gid + k * BLOCK_STRIDE_A + LINE_STRIDE_A * 5)).x;
|
||||
regA.s2 = read_imageui(src0_q, (gid + k * BLOCK_STRIDE_A + LINE_STRIDE_A * 6)).x;
|
||||
regA.s3 = read_imageui(src0_q, (gid + k * BLOCK_STRIDE_A + LINE_STRIDE_A * 7)).x;
|
||||
#ifdef VECTOR_SUB_GROUP_BROADCAST
|
||||
dequantizeBlockAccum_ns_sgbroadcast_8_lo(totalSum, as_ushort8(regA), regS, regM, regB);
|
||||
#else
|
||||
dequantizeBlockAccum_ns_sgbroadcast_1_lo(totalSum, as_ushort8(regA), regS, regM, regB);
|
||||
#endif // VECTOR_SUB_GROUP_BROADCAST
|
||||
}
|
||||
|
||||
// reduction in local memory, assumes #wave=4
|
||||
local float2 reduceLM[SUBGROUP_SIZE * 3];
|
||||
if (groupId == 1) {
|
||||
reduceLM[SUBGROUP_SIZE * 0 + slid] = totalSum;
|
||||
}
|
||||
if (groupId == 2) {
|
||||
reduceLM[SUBGROUP_SIZE * 1 + slid] = totalSum;
|
||||
}
|
||||
if (groupId == 3) {
|
||||
reduceLM[SUBGROUP_SIZE * 2 + slid] = totalSum;
|
||||
}
|
||||
|
||||
barrier(CLK_LOCAL_MEM_FENCE);
|
||||
|
||||
if (groupId == 0) {
|
||||
totalSum += reduceLM[SUBGROUP_SIZE * 0 + slid];
|
||||
}
|
||||
if (groupId == 0) {
|
||||
totalSum += reduceLM[SUBGROUP_SIZE * 1 + slid];
|
||||
}
|
||||
if (groupId == 0) {
|
||||
totalSum += reduceLM[SUBGROUP_SIZE * 2 + slid];
|
||||
}
|
||||
|
||||
// 2 outputs per fiber in wave 0
|
||||
if (groupId == 0) {
|
||||
dst = (global float*)((global char*)dst + offsetd);
|
||||
vstore2(totalSum, 0, &(dst[gid * 2]));
|
||||
}
|
||||
|
||||
}
|
||||
Loading…
Reference in New Issue