mtx_avx2_arr_i8.cpp

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 *
 * Copyright (C) Akiel Aries, <akiel@akiel.org>, et al.
 *
 * This software is licensed as described in the file LICENSE, which
 * you should have received as part of this distribution. The terms
 * among other details are referenced in the official documentation
 * seen here : https://akielaries.github.io/openGPMP/ along with
 * important files seen in this project.
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 * and/or sell copies of the Software, and permit persons to whom
 * the Software is furnished to do so, under the terms of the
 * LICENSE file. As this is an Open Source effort, all implementations
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 *
 * This software is distributed on an AS IS basis, WITHOUT
 * WARRANTY OF ANY KIND, either express or implied.
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 ************************************************************************/
#include <cassert>
#include <cstddef>
#include <cstdint>
#include <cstring>
#include <iostream>
#include <openGPMP/linalg/mtx.hpp>
#include <vector>
 
#if defined(__x86_64__) || defined(__amd64__) || defined(__amd64)
 
/************************************************************************
 *
 * Matrix Operations for AVX ISA
 *
 ************************************************************************/
#if defined(__AVX2__)
 
// AVX family intrinsics
#include <immintrin.h>
 
/************************************************************************
 *
 * Matrix Operations on Arrays
 *
 ************************************************************************/
// matrix addition for 8-bit integers using 256-bit SIMD registers
void gpmp::linalg::Mtx::mtx_add(const int8_t *A,
                                const int8_t *B,
                                int8_t *C,
                                int rows,
                                int cols) {
    // BUG FIXME
    for (int i = 0; i < rows; ++i) {
        int j = 0;
        for (; j < cols - 31; j += 32) {
            __m256i a = _mm256_loadu_si256(
                reinterpret_cast<const __m256i *>(&A[i * cols + j]));
            __m256i b = _mm256_loadu_si256(
                reinterpret_cast<const __m256i *>(&B[i * cols + j]));
            __m256i c = _mm256_loadu_si256(
                reinterpret_cast<const __m256i *>(&C[i * cols + j]));
 
            // Perform vectorized addition and accumulate the result
            c = _mm256_add_epi8(c, _mm256_add_epi8(a, b));
 
            // Store the result back to the C matrix
            _mm256_storeu_si256(reinterpret_cast<__m256i *>(&C[i * cols + j]),
                                c);
        }
 
        for (; j < cols; ++j) {
            C[i * cols + j] = A[i * cols + j] + B[i * cols + j];
        }
    }
}
 
void gpmp::linalg::Mtx::mtx_sub(const int8_t *A,
                                const int8_t *B,
                                int8_t *C,
                                int rows,
                                int cols) {
    for (int i = 0; i < rows; ++i) {
        int j = 0;
        for (; j < cols - 31; j += 32) {
            __m256i a = _mm256_loadu_si256(
                reinterpret_cast<const __m256i *>(&A[i * cols + j]));
            __m256i b = _mm256_loadu_si256(
                reinterpret_cast<const __m256i *>(&B[i * cols + j]));
            __m256i c = _mm256_loadu_si256(
                reinterpret_cast<const __m256i *>(&C[i * cols + j]));
 
            // Perform vectorized subtraction and accumulate the result
            c = _mm256_sub_epi8(a, b);
 
            // Store the result back to the C matrix
            _mm256_storeu_si256(reinterpret_cast<__m256i *>(&C[i * cols + j]),
                                c);
        }
 
        for (; j < cols; ++j) {
            C[i * cols + j] = A[i * cols + j] - B[i * cols + j];
        }
    }
}
 
void gpmp::linalg::Mtx::mtx_mult(const int8_t *A,
                                 const int8_t *B,
                                 int8_t *C,
                                 int rows_a,
                                 int cols_a,
                                 int cols_b) {
 
    for (int i = 0; i < rows_a; ++i) {
        for (int j = 0; j < cols_b; j += 32) {
            __m256i c = _mm256_setzero_si256();
 
            for (int k = 0; k < cols_a; ++k) {
                __m256i a = _mm256_set1_epi8(A[i * cols_a + k]);
                __m256i b = _mm256_loadu_si256(
                    reinterpret_cast<const __m256i *>(&B[k * cols_b + j]));
 
                __m256i prod = _mm256_maddubs_epi16(a, b);
                c = _mm256_add_epi16(c, prod);
            }
 
            c = _mm256_srai_epi16(c, 8);
            c = _mm256_packs_epi16(c, _mm256_setzero_si256());
 
            _mm256_storeu_si256(reinterpret_cast<__m256i *>(&C[i * cols_b + j]),
                                c);
        }
 
        // Handle remaining elements
        for (int j = cols_b - cols_b % 32; j < cols_b; ++j) {
            int sum = 0;
 
            for (int k = 0; k < cols_a; ++k) {
                sum += A[i * cols_a + k] * B[k * cols_b + j];
            }
 
            C[i * cols_b + j] = sum;
        }
    }
}
 
#endif
 
// x86
#endif