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Sigbjørn Skjæret
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·
332bcaf
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Parent(s):
d41b883
CUDA: don't convert BF16 weights to FP32 (ggml/1174)
Browse files* add bf16 support
* use convert_from_bf16_cuda instead of convert_unary_cuda for f32
* revert 7ec5085
* move functionality into convert_unary with constexpr
ggml/src/ggml-cuda/convert.cu
CHANGED
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@@ -579,7 +579,13 @@ static __global__ void convert_unary(const void * __restrict__ vx, dst_t * __res
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const src_t * x = (const src_t *) vx;
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-
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}
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template <typename src_t, typename dst_t>
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@@ -588,6 +594,17 @@ static void convert_unary_cuda(const void * __restrict__ vx, dst_t * __restrict_
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convert_unary<src_t><<<num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, 0, stream>>>(vx, y, k);
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}
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to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) {
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switch (type) {
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case GGML_TYPE_Q4_0:
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@@ -633,6 +650,8 @@ to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) {
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return dequantize_row_iq3_s_cuda;
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case GGML_TYPE_F32:
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return convert_unary_cuda<float>;
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default:
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return nullptr;
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}
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const src_t * x = (const src_t *) vx;
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if constexpr (std::is_same_v<src_t, nv_bfloat16>) {
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y[i] = __bfloat162float(x[i]);
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} else if constexpr (std::is_same_v<dst_t, nv_bfloat16> && std::is_same_v<src_t, half>) {
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y[i] = (float)x[i];
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} else {
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y[i] = x[i];
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}
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}
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template <typename src_t, typename dst_t>
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convert_unary<src_t><<<num_blocks, CUDA_DEQUANTIZE_BLOCK_SIZE, 0, stream>>>(vx, y, k);
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}
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to_bf16_cuda_t ggml_get_to_bf16_cuda(ggml_type type) {
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switch (type) {
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case GGML_TYPE_F32:
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return convert_unary_cuda<float>;
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case GGML_TYPE_F16:
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return convert_unary_cuda<half>;
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default:
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return nullptr;
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}
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}
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to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type) {
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switch (type) {
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case GGML_TYPE_Q4_0:
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return dequantize_row_iq3_s_cuda;
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case GGML_TYPE_F32:
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return convert_unary_cuda<float>;
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case GGML_TYPE_BF16:
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return convert_unary_cuda<nv_bfloat16>;
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default:
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return nullptr;
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}
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ggml/src/ggml-cuda/convert.cuh
CHANGED
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@@ -7,7 +7,10 @@ using to_t_cuda_t = void (*)(const void * __restrict__ x, T * __restrict__ y, in
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typedef to_t_cuda_t<float> to_fp32_cuda_t;
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typedef to_t_cuda_t<half> to_fp16_cuda_t;
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to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type);
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to_fp32_cuda_t ggml_get_to_fp32_cuda(ggml_type type);
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typedef to_t_cuda_t<float> to_fp32_cuda_t;
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typedef to_t_cuda_t<half> to_fp16_cuda_t;
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typedef to_t_cuda_t<nv_bfloat16> to_bf16_cuda_t;
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to_fp16_cuda_t ggml_get_to_fp16_cuda(ggml_type type);
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to_bf16_cuda_t ggml_get_to_bf16_cuda(ggml_type type);
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+
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to_fp32_cuda_t ggml_get_to_fp32_cuda(ggml_type type);
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ggml/src/ggml-cuda/ggml-cuda.cu
CHANGED
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@@ -1194,7 +1194,35 @@ static void ggml_cuda_op_mul_mat_cublas(
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const bool use_fp16 = (src0->type == GGML_TYPE_F16 || ggml_is_quantized(src0->type)) && ggml_is_contiguous(src0) && row_diff == src0->ne[1] && dst->op_params[0] == GGML_PREC_DEFAULT;
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-
if (
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// convert src0 and src1 to fp16, multiply as fp16, convert dst to fp32
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ggml_cuda_pool_alloc<half> src0_as_f16(ctx.pool(id));
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if (src0->type != GGML_TYPE_F16) {
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const bool use_fp16 = (src0->type == GGML_TYPE_F16 || ggml_is_quantized(src0->type)) && ggml_is_contiguous(src0) && row_diff == src0->ne[1] && dst->op_params[0] == GGML_PREC_DEFAULT;
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if (src0->type == GGML_TYPE_BF16 && ggml_is_contiguous(src0) && row_diff == src0->ne[1]) {
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ggml_cuda_pool_alloc<nv_bfloat16> src1_as_bf16(ctx.pool(id));
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if (src1->type != GGML_TYPE_BF16) {
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const to_bf16_cuda_t to_bf16_cuda = ggml_get_to_bf16_cuda(src1->type);
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GGML_ASSERT(to_bf16_cuda != nullptr);
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size_t ne = src1_ncols*ne10;
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src1_as_bf16.alloc(ne);
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to_bf16_cuda(src1_ddf_i, src1_as_bf16.get(), ne, stream);
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}
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const nv_bfloat16 * src1_ptr = src1->type == GGML_TYPE_BF16 ? (const nv_bfloat16 *) src1_ddf_i : src1_as_bf16.get();
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const nv_bfloat16 * src0_ptr = (const nv_bfloat16 *)src0_dd_i;
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ggml_cuda_pool_alloc<nv_bfloat16> dst_bf16(ctx.pool(id), row_diff*src1_ncols);
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const float alpha_f32 = 1.0f;
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const float beta_f32 = 0.0f;
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CUBLAS_CHECK(cublasSetStream(ctx.cublas_handle(id), stream));
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CUBLAS_CHECK(
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cublasGemmEx(ctx.cublas_handle(id), CUBLAS_OP_T, CUBLAS_OP_N,
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row_diff, src1_ncols, ne10,
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&alpha_f32, src0_ptr, CUDA_R_16BF, ne00,
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src1_ptr, CUDA_R_16BF, ne10,
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&beta_f32, dst_bf16.get(), CUDA_R_16BF, ldc,
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CUBLAS_COMPUTE_32F,
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CUBLAS_GEMM_DEFAULT_TENSOR_OP));
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const to_fp32_cuda_t to_fp32_cuda = ggml_get_to_fp32_cuda(GGML_TYPE_BF16);
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to_fp32_cuda(dst_bf16.get(), dst_dd_i, row_diff*src1_ncols, stream);
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} else if (((GGML_CUDA_CC_IS_NVIDIA(cc) && cc >= GGML_CUDA_CC_VOLTA) || GGML_CUDA_CC_IS_AMD(cc)) && use_fp16) {
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// convert src0 and src1 to fp16, multiply as fp16, convert dst to fp32
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ggml_cuda_pool_alloc<half> src0_as_f16(ctx.pool(id));
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if (src0->type != GGML_TYPE_F16) {
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