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75e8855 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 | /* alp-carry — carry-chain proof kernel
* Copyright (C) 2026 Ahmad Ali Parr
* SPDX-License-Identifier: AGPL-3.0-only
*/
#include "tensor.h"
#include <stdlib.h>
#include <string.h>
#include <immintrin.h>
Tensor tensor_new(size_t r, size_t c) {
size_t stride_bytes = (c * sizeof(float) + 63) & ~(size_t)63;
size_t stride = stride_bytes / sizeof(float);
float *d = NULL;
if (posix_memalign((void **)&d, 64, stride_bytes * r)) abort();
memset(d, 0, stride_bytes * r);
return (Tensor){ d, r, c, stride };
}
void tensor_free(Tensor *t) { free(t->data); t->data = NULL; }
void tensor_randomize(Tensor *t, float lo, float hi) {
for (size_t i = 0; i < t->rows; i++)
for (size_t j = 0; j < t->cols; j++) {
float u = (float)rand() / (float)RAND_MAX;
t->data[i * t->stride + j] = lo + u * (hi - lo);
}
}
void linear_avx2(const Tensor *x, const Tensor *w, const Tensor *b, Tensor *out) {
for (size_t i = 0; i < x->rows; i++) {
const float *xi = x->data + i * x->stride;
float *oi = out->data + i * out->stride;
memcpy(oi, b->data, b->cols * sizeof(float));
for (size_t k = 0; k < x->cols; k++) {
__m256 xv = _mm256_set1_ps(xi[k]);
size_t j = 0;
for (; j + 8 <= w->cols; j += 8) {
__m256 wv = _mm256_loadu_ps(w->data + k * w->stride + j);
__m256 ov = _mm256_loadu_ps(oi + j);
_mm256_storeu_ps(oi + j, _mm256_add_ps(ov, _mm256_mul_ps(xv, wv)));
}
for (; j < w->cols; j++)
oi[j] += xi[k] * w->data[k * w->stride + j];
}
}
}
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