benchmark/matmul/matmul_benchmark_logic.hpp

Directory:	./
File:	benchmark/matmul/matmul_benchmark_logic.hpp
Date:	2025-10-20 13:18:31

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      //
    
      // SPDX-FileCopyrightText: Copyright 2025 Arm Limited and/or its affiliates <open-source-office@arm.com>
    
      //
    
      // SPDX-License-Identifier: Apache-2.0
    
      //
    
      #ifndef KLEIDIAI_BENCHMARK_MATMUL_MATMUL_BENCHMARK_LOGIC_HPP
    
      #define KLEIDIAI_BENCHMARK_MATMUL_MATMUL_BENCHMARK_LOGIC_HPP
    
      #include <cstddef>
    
      #include <cstdint>
    
      #include <functional>
    
      #include <vector>
    
      #include "kai/kai_common.h"
    
      #include "matmul_interface.hpp"
    
      #include "matmul_runner.hpp"
    
      #ifdef __GNUC__
    
      #pragma GCC diagnostic push
    
      #pragma GCC diagnostic ignored "-Wswitch-default"
    
      #endif  // __GNUC__
    
      #include <benchmark/benchmark.h>
    
      #ifdef __GNUC__
    
      #pragma GCC diagnostic pop
    
      #endif  // __GNUC__
    
      namespace kai::benchmark {
    
      using Buffer = std::vector<uint8_t>;
    
      using CpuRequirement = std::function<bool()>;
    
      /// High level description of the matrix multiplication operation.
    
      enum class MatMulOp : uint8_t {
    
          GEMM,
    
          GEMV,
    
      };
    
      /// Benchmarks a matrix multiplication micro-kernel.
    
      ///
    
      /// @tparam MatMulInterface Interface of the matrix multiplication micro-kernel.
    
      /// @param state            State for the benchmark to use.
    
      /// @param matmul_interface Abstraction containing the micro-kernel to run.
    
      /// @param dst_type         Output type of the micro-kernel. Required for the micro-kernel to make certain assumptions
    
      ///                         internally about the stride of the data.
    
      /// @param matmul_op        Type of matrix multiplication operation.
    
      /// @param is_cpu_supported Function that checks the CPU feature requirement to run this benchmark.
    
      template <typename MatMulInterface>
    
      83
      void kai_benchmark_matmul(
    
          ::benchmark::State& state, const MatMulInterface matmul_interface, const DataType dst_type,
    
          const MatMulOp matmul_op, const CpuRequirement& is_cpu_supported) {
    
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      83
          if (!is_cpu_supported()) {
    
      ✗
              state.SkipWithMessage("Unsupported CPU feature");
    
      ✗
          }
    
      83
          const size_t m = state.range(0);
    
      83
          const size_t n = state.range(1);
    
      83
          const size_t k = state.range(2);
    
      83
          const size_t bl = state.range(3);
    
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      83
          if (m > 1 && matmul_op == MatMulOp::GEMV) {
    
      ✗
              state.SkipWithMessage("GEMV optimized for m=1 only");
    
      ✗
          }
    
          if constexpr (
    
              std::is_same_v<MatMulInterface, MatMulBlockwiseDynamicQuantInterface> ||
    
              std::is_same_v<MatMulInterface, MatMulBlockwiseDynamicQuantGenericDstInterface>) {
    
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      32
              if (k % bl != 0) {
    
      ✗
                  state.SkipWithMessage("K must be a multiple of block size");
    
      ✗
              }
    
          }
    
          // Create sufficiently large buffers
    
      83
          size_t lhs_size = m * k * sizeof(uint64_t);
    
      83
          size_t rhs_size = n * k * sizeof(uint64_t);
    
      83
          size_t dst_size = m * n * sizeof(uint32_t);
    
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      83
          if (test::cpu_has_sme() || test::cpu_has_sme2()) {
    
      83
              lhs_size *= kai_get_sme_vector_length_u32();
    
      83
              rhs_size *= kai_get_sme_vector_length_u32();
    
      83
              dst_size *= kai_get_sme_vector_length_u32();
    
      83
          }
    
      83
          const Buffer lhs(lhs_size);
    
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          const Buffer rhs(rhs_size);
    
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          Buffer dst(dst_size);
    
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      83
          MatMulRunner matmul_runner(matmul_interface, dst_type);
    
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      83
          matmul_runner.set_mnk(m, n, k);
    
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      83
          matmul_runner.set_bl(bl);
    
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      166
          for (auto _ : state) {
    
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      83
              matmul_runner.run(lhs.data(), rhs.data(), dst.data());
    
      83
          }
    
      83
      }
    
      }  // namespace kai::benchmark
    
      #endif  // KLEIDIAI_BENCHMARK_MATMUL_MATMUL_BENCHMARK_LOGIC_HPP

Line	Branch	Exec	Source
1			//
2			// SPDX-FileCopyrightText: Copyright 2025 Arm Limited and/or its affiliates <open-source-office@arm.com>
3			//
4			// SPDX-License-Identifier: Apache-2.0
5			//
6
7			#ifndef KLEIDIAI_BENCHMARK_MATMUL_MATMUL_BENCHMARK_LOGIC_HPP
8			#define KLEIDIAI_BENCHMARK_MATMUL_MATMUL_BENCHMARK_LOGIC_HPP
9
10			#include <cstddef>
11			#include <cstdint>
12			#include <functional>
13			#include <vector>
14
15			#include "kai/kai_common.h"
16			#include "matmul_interface.hpp"
17			#include "matmul_runner.hpp"
18
19			#ifdef __GNUC__
20			#pragma GCC diagnostic push
21			#pragma GCC diagnostic ignored "-Wswitch-default"
22			#endif // __GNUC__
23
24			#include <benchmark/benchmark.h>
25
26			#ifdef __GNUC__
27			#pragma GCC diagnostic pop
28			#endif // __GNUC__
29
30			namespace kai::benchmark {
31			using Buffer = std::vector<uint8_t>;
32			using CpuRequirement = std::function<bool()>;
33
34			/// High level description of the matrix multiplication operation.
35			enum class MatMulOp : uint8_t {
36			GEMM,
37			GEMV,
38			};
39
40			/// Benchmarks a matrix multiplication micro-kernel.
41			///
42			/// @tparam MatMulInterface Interface of the matrix multiplication micro-kernel.
43			/// @param state State for the benchmark to use.
44			/// @param matmul_interface Abstraction containing the micro-kernel to run.
45			/// @param dst_type Output type of the micro-kernel. Required for the micro-kernel to make certain assumptions
46			/// internally about the stride of the data.
47			/// @param matmul_op Type of matrix multiplication operation.
48			/// @param is_cpu_supported Function that checks the CPU feature requirement to run this benchmark.
49			template <typename MatMulInterface>
50		83	void kai_benchmark_matmul(
51			::benchmark::State& state, const MatMulInterface matmul_interface, const DataType dst_type,
52			const MatMulOp matmul_op, const CpuRequirement& is_cpu_supported) {
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54		✗	state.SkipWithMessage("Unsupported CPU feature");
55		✗	}
56
57		83	const size_t m = state.range(0);
58		83	const size_t n = state.range(1);
59		83	const size_t k = state.range(2);
60		83	const size_t bl = state.range(3);
61
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63		✗	state.SkipWithMessage("GEMV optimized for m=1 only");
64		✗	}
65
66			if constexpr (
67			std::is_same_v<MatMulInterface, MatMulBlockwiseDynamicQuantInterface> \|\|
68			std::is_same_v<MatMulInterface, MatMulBlockwiseDynamicQuantGenericDstInterface>) {
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70		✗	state.SkipWithMessage("K must be a multiple of block size");
71		✗	}
72			}
73
74			// Create sufficiently large buffers
75		83	size_t lhs_size = m * k * sizeof(uint64_t);
76		83	size_t rhs_size = n * k * sizeof(uint64_t);
77		83	size_t dst_size = m * n * sizeof(uint32_t);
78
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80		83	lhs_size *= kai_get_sme_vector_length_u32();
81		83	rhs_size *= kai_get_sme_vector_length_u32();
82		83	dst_size *= kai_get_sme_vector_length_u32();
83		83	}
84
85		83	const Buffer lhs(lhs_size);
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88
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92
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95		83	}
96		83	}
97			} // namespace kai::benchmark
98
99			#endif // KLEIDIAI_BENCHMARK_MATMUL_MATMUL_BENCHMARK_LOGIC_HPP
100