benchmark/matmul/matmul_benchmark_logic.hpp

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    benchmark/matmul/matmul_benchmark_logic.hpp
    
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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>
      
        534
        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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        534
            if (!is_cpu_supported()) {
      
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        122
                state.SkipWithMessage("Unsupported CPU feature");
      
        122
                return;
      
            }
      
        412
            const size_t m = state.range(0);
      
        412
            const size_t n = state.range(1);
      
        412
            const size_t k = state.range(2);
      
        412
            const size_t bl = state.range(3);
      
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        412
            if (m > 1 && matmul_op == MatMulOp::GEMV) {
      
        ✗
                state.SkipWithMessage("GEMV optimized for m=1 only");
      
        ✗
                return;
      
            }
      
            if constexpr (
      
                std::is_same_v<MatMulInterface, MatMulBlockwiseDynamicQuantInterface> ||
      
                std::is_same_v<MatMulInterface, MatMulBlockwiseDynamicQuantGenericDstInterface>) {
      
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        178
                if (k % bl != 0) {
      
        ✗
                    state.SkipWithMessage("K must be a multiple of block size");
      
        ✗
                    return;
      
                }
      
            }
      
            // Create sufficiently large buffers
      
        412
            size_t lhs_size = m * k * sizeof(uint64_t);
      
        412
            size_t rhs_size = n * k * sizeof(uint64_t);
      
        412
            size_t dst_size = m * n * sizeof(uint32_t);
      
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        412
            if (test::cpu_has_sme() || test::cpu_has_sme2()) {
      
        170
                lhs_size *= kai_get_sme_vector_length_u32();
      
        170
                rhs_size *= kai_get_sme_vector_length_u32();
      
        170
                dst_size *= kai_get_sme_vector_length_u32();
      
        170
            }
      
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        412
            const Buffer lhs(lhs_size);
      
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        412
            const Buffer rhs(rhs_size);
      
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        412
            Buffer dst(dst_size);
      
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        412
            MatMulRunner matmul_runner(matmul_interface, dst_type);
      
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        412
            matmul_runner.set_mnk(m, n, k);
      
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        412
            matmul_runner.set_bl(bl);
      
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        824
            for (auto _ : state) {
      
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        412
                matmul_runner.run(lhs.data(), rhs.data(), dst.data());
      
        412
            }
      
        534
        }
      
        }  // namespace kai::benchmark
      
        #endif  // KLEIDIAI_BENCHMARK_MATMUL_MATMUL_BENCHMARK_LOGIC_HPP

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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		534	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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55		122	return;
56			}
57
58		412	const size_t m = state.range(0);
59		412	const size_t n = state.range(1);
60		412	const size_t k = state.range(2);
61		412	const size_t bl = state.range(3);
62
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64		✗	state.SkipWithMessage("GEMV optimized for m=1 only");
65		✗	return;
66			}
67
68			if constexpr (
69			std::is_same_v<MatMulInterface, MatMulBlockwiseDynamicQuantInterface> \|\|
70			std::is_same_v<MatMulInterface, MatMulBlockwiseDynamicQuantGenericDstInterface>) {
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72		✗	state.SkipWithMessage("K must be a multiple of block size");
73		✗	return;
74			}
75			}
76
77			// Create sufficiently large buffers
78		412	size_t lhs_size = m * k * sizeof(uint64_t);
79		412	size_t rhs_size = n * k * sizeof(uint64_t);
80		412	size_t dst_size = m * n * sizeof(uint32_t);
81
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83		170	lhs_size *= kai_get_sme_vector_length_u32();
84		170	rhs_size *= kai_get_sme_vector_length_u32();
85		170	dst_size *= kai_get_sme_vector_length_u32();
86		170	}
87
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91
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95
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98		412	}
99		534	}
100			} // namespace kai::benchmark
101
102			#endif // KLEIDIAI_BENCHMARK_MATMUL_MATMUL_BENCHMARK_LOGIC_HPP
103

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