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// SPDX-FileCopyrightText: Copyright 2025 Arm Limited and/or its affiliates <open-source-office@arm.com> |
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// |
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// SPDX-License-Identifier: Apache-2.0 |
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// |
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#if (!defined(__aarch64__)) && !defined(_M_ARM64) |
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#error This file must be compiled for AArch64. |
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#else // Architectural features check. |
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#include "kai_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla.h" |
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#include <stddef.h> |
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#include <stdint.h> |
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#include "kai/kai_common.h" |
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typedef struct { |
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float maxval; |
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float minval; |
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unsigned int num_strings; |
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const unsigned int* string_lengths; |
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size_t N; |
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const void* B_ptr; |
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size_t output_offset; |
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size_t input_initial_col; |
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size_t input_offset; |
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void* output_ptr; |
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const void* bias; |
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} KernelArgs; |
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void kai_kernel_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla( |
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const void* input_ptr, size_t m, KernelArgs* args_ptr, unsigned long flags); |
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static const size_t kai_mr = 6; |
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static const size_t kai_nr = 16; |
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static const size_t kai_kr = 1; |
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static const size_t kai_sr = 1; |
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size_t kai_get_m_step_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(void) { |
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return kai_mr; |
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} |
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size_t kai_get_n_step_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(void) { |
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return kai_nr; |
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} |
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size_t kai_get_nr_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(void) { |
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return kai_nr; |
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} |
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size_t kai_get_kr_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(void) { |
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return kai_kr; |
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} |
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size_t kai_get_sr_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(void) { |
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return kai_sr; |
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} |
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size_t kai_get_lhs_offset_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(size_t m_idx, size_t stride) { |
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KAI_ASSUME(m_idx % kai_get_m_step_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla() == 0); |
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return m_idx * stride; |
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} |
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size_t kai_get_rhs_packed_offset_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(size_t n_idx, size_t k) { |
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KAI_ASSUME(n_idx % kai_get_n_step_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla() == 0); |
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return n_idx / kai_nr * (kai_nr * sizeof(float) + kai_nr * k * sizeof(float)); |
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} |
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size_t kai_get_dst_offset_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(size_t m_idx, size_t n_idx, size_t stride) { |
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KAI_ASSUME(m_idx % kai_get_m_step_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla() == 0); |
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KAI_ASSUME(n_idx % kai_get_n_step_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla() == 0); |
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return m_idx * stride + n_idx * sizeof(float); |
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} |
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size_t kai_get_dst_size_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(size_t m, size_t n) { |
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return m * n * sizeof(float); |
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} |
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void kai_run_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla( |
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size_t m, size_t n, size_t k, // |
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const void* lhs, size_t lhs_stride, // |
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const void* rhs_packed, // |
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void* dst, size_t dst_stride_row, size_t dst_stride_col, // |
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float clamp_min, float clamp_max) { |
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KAI_UNUSED(dst_stride_col); |
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KernelArgs ka; |
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unsigned long flags = 0; |
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unsigned int string_length = k; |
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ka.num_strings = 1; |
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ka.string_lengths = &string_length; |
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ka.N = n; |
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ka.B_ptr = rhs_packed; |
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ka.bias = NULL; |
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// Direct input. |
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const void* input_ptr = lhs; |
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ka.input_offset = lhs_stride / sizeof(float); |
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ka.input_initial_col = 0; |
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// Direct output. |
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ka.output_ptr = dst; |
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ka.output_offset = dst_stride_row / sizeof(float); |
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// Clamping output. |
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flags |= 0x2; |
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ka.maxval = clamp_max; |
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ka.minval = clamp_min; |
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kai_kernel_matmul_clamp_f32_f32_f32p16x1b_6x16_neon_mla(input_ptr, m, &ka, flags); |
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} |
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#endif // Architectural features check. |
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