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authorFrancesco.Petrogalli@arm.com <francesco.petrogalli@arm.com>2022-04-05 10:31:08 +0000
committerFrancesco Petrogalli <francesco.petrogalli@arm.com>2022-05-24 14:28:27 +0000
commit5fcf22dadf092efd7aafb359f9229aa270eb1129 (patch)
treef309426ed19bd6710329da3b530167db72d1c6b2 /src/core/NEON/kernels/arm_gemm/kernels/sve_ffhybrid_fp32bf16fp32_mmla_4x6VL.hpp
parenta8caa023f0d7b71b3a250a14ceee935052fcc74a (diff)
downloadComputeLibrary-5fcf22dadf092efd7aafb359f9229aa270eb1129.tar.gz
[arm_gemm] Import fixed-format kernels from gemm_linux.
This is a No Functional Change Intended (NFCI) patch. It imports the kernel in the code, but the interface to select them and expose the format of the weight tensors to the user will be provided in a subsequent patch. Kernels and kernel selection code in arm_gemm has been provided by David.Mansell <David.Mansell@arm.com>. The kernels are not compiled in the library by default, but need to be selected via the `scons` option `experimental_fixed_format_kernels=1`. Resolves: ONCPUML-829 Signed-off-by: Francesco.Petrogalli@arm.com <francesco.petrogalli@arm.com> Change-Id: If00ccb2b9b7221e01b214cf9783111226ccc8bf4 Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7380 Tested-by: Arm Jenkins <bsgcomp@arm.com> Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com> Reviewed-by: SiCong Li <sicong.li@arm.com> Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/NEON/kernels/arm_gemm/kernels/sve_ffhybrid_fp32bf16fp32_mmla_4x6VL.hpp')
-rw-r--r--src/core/NEON/kernels/arm_gemm/kernels/sve_ffhybrid_fp32bf16fp32_mmla_4x6VL.hpp109
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diff --git a/src/core/NEON/kernels/arm_gemm/kernels/sve_ffhybrid_fp32bf16fp32_mmla_4x6VL.hpp b/src/core/NEON/kernels/arm_gemm/kernels/sve_ffhybrid_fp32bf16fp32_mmla_4x6VL.hpp
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index 0000000000..3ee3e31206
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+++ b/src/core/NEON/kernels/arm_gemm/kernels/sve_ffhybrid_fp32bf16fp32_mmla_4x6VL.hpp
@@ -0,0 +1,109 @@
+/*
+ * Copyright (c) 2022 Arm Limited.
+ *
+ * SPDX-License-Identifier: MIT
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to
+ * deal in the Software without restriction, including without limitation the
+ * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
+ * sell copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+ * FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS
+ * IN THE SOFTWARE.
+ */
+#pragma once
+#ifdef ARM_COMPUTE_ENABLE_SVE
+
+#include "../std_transforms_sve.hpp"
+#include "../bfloat.hpp"
+#include "../kernel_weight_format.hpp"
+#include "../performance_parameters.hpp"
+
+#define ARGLIST \
+ unsigned int, const unsigned int *, \
+ IndirectInputArg<float>, \
+ size_t, size_t, \
+ const bfloat16 *, \
+ size_t, \
+ IndirectOutputArg<float>, \
+ const float *, Activation, bool
+
+namespace arm_gemm
+{
+// Actual kernel implementations
+void sve_ffhybrid_fp32bf16fp32_mmla_4x6VL( ARGLIST );
+
+class cls_sve_ffhybrid_fp32bf16fp32_mmla_4x6VL
+{
+public:
+ typedef float lhs_operand_type;
+ typedef bfloat16 rhs_operand_type;
+ typedef float result_type;
+
+ typedef void (*kern_type)( ARGLIST );
+
+ /* Kernel blocking parameters */
+ static constexpr unsigned int out_height()
+ {
+ return 4;
+ }
+ static unsigned int stripe_width()
+ {
+ return get_vector_length<float>() * 1;
+ }
+
+ static KernelWeightFormat kernel_weight_format()
+ {
+ return KernelWeightFormat::VL2VL_BL64_BF16;
+ }
+
+ static unsigned int out_width()
+ {
+ return get_vector_length<float>() * 6;
+ }
+
+ static constexpr unsigned int k_unroll()
+ {
+ return 4;
+ }
+
+ static constexpr bool supports_accumulate()
+ {
+ return true;
+ }
+
+ StdTransformsSVE<rhs_operand_type, result_type, 4, 12, 4> transforms = {};
+ template<typename T>
+ static inline PerformanceParameters get_performance_parameters(const CPUInfo *ci)
+ {
+ if (std::is_same<T, float>::value) {
+ switch (ci->get_cpu_model()) {
+ default:
+ return { 32.35 };
+ }
+ }
+
+ return { 1.0 };
+ }
+
+ // Default to the generic kernel
+ kern_type kernel=sve_ffhybrid_fp32bf16fp32_mmla_4x6VL;
+ cls_sve_ffhybrid_fp32bf16fp32_mmla_4x6VL(const CPUInfo *)
+ {
+ }
+};
+
+} // namespace arm_gemm
+
+#undef ARGLIST
+#endif // ARM_COMPUTE_ENABLE_SVE