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Improve perf by using less heap allocs #37

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merged 3 commits into from
Jul 7, 2024
Merged

Improve perf by using less heap allocs #37

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bed990b
Improve perf by using less heap allocs
rozukke Jul 7, 2024
6e8df3f
Style fix arghh
rozukke Jul 7, 2024
719a16b
Fix padding issue
rozukke Jul 7, 2024
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105 changes: 27 additions & 78 deletions src/main.c
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Original file line number Diff line number Diff line change
Expand Up @@ -25,101 +25,50 @@ char letters[52] = {'A', 'a', 'B', 'b', 'C', 'c', 'D', 'd', 'E', 'e', 'F', 'f',
'J', 'j', 'K', 'k', 'L', 'l', 'M', 'm', 'N', 'n', 'O', 'o', 'P', 'p', 'Q', 'q', 'R', 'r',
'S', 's', 'T', 't', 'U', 'u', 'V', 'v', 'W', 'w', 'X', 'x', 'Y', 'y', 'Z', 'z'};

void propagate_fwd(const matrix* weights, const vector* inputs, vector* results, const vector* biases) {
sgemv_t_tuned(weights->data, inputs->data, results->data, weights->cols, weights->rows);
void propagate_fwd(const matrix* weights, const float* inputs, float* results, const vector* biases) {
sgemv_t_tuned(weights->data, inputs, results, weights->cols, weights->rows);
// Add biases onto results
vector_add_inplace(biases->len, biases->data, results->data);
vector_add_inplace(biases->len, biases->data, results);
}

// Basic version, too many aligned_alloc
u8 infer(vector* input) {
vector* outputs[NUM_LAYERS];
outputs[0] = new_vec_aligned(98);
outputs[1] = new_vec_aligned(65);
outputs[2] = new_vec_aligned(50);
outputs[3] = new_vec_aligned(30);
outputs[4] = new_vec_aligned(25);
outputs[5] = new_vec_aligned(40);
outputs[6] = new_vec_aligned(52);

propagate_fwd(weights[0], input, outputs[0], biases[0]);
relu_inplace(outputs[0]->data, 98);
propagate_fwd(weights[1], outputs[0], outputs[1], biases[1]);
relu_inplace(outputs[1]->data, 65);
propagate_fwd(weights[2], outputs[1], outputs[2], biases[2]);
relu_inplace(outputs[2]->data, 50);
propagate_fwd(weights[3], outputs[2], outputs[3], biases[3]);
relu_inplace(outputs[3]->data, 30);
propagate_fwd(weights[4], outputs[3], outputs[4], biases[4]);
relu_inplace(outputs[4]->data, 25);
propagate_fwd(weights[5], outputs[4], outputs[5], biases[5]);
relu_inplace(outputs[5]->data, 40);
propagate_fwd(weights[6], outputs[5], outputs[6], biases[6]);
softmax_inplace(outputs[6]->data, 52);

u8 pred = argmax(outputs[6]->data, 52);

free(outputs[0]->data);
free(outputs[0]);
free(outputs[1]->data);
free(outputs[1]);
free(outputs[2]->data);
free(outputs[2]);
free(outputs[3]->data);
free(outputs[3]);
free(outputs[4]->data);
free(outputs[4]);
free(outputs[5]->data);
free(outputs[5]);
free(outputs[6]->data);
free(outputs[6]);

return pred;
}

// Somewhat experimental, minumum number of alligned_alloc without breaking things.
// This code fucking sucks but its fast so uhhhh
// Minumum number of alligned_alloc without breaking things.
// This code f***ing sucks but its fast so uhhhh
u8 infer_reuse_layers_thread(vector* input, matrix** weights, vector** biases) {
vector* outputs[2];
outputs[0] = new_vec_aligned(98);
outputs[1] = new_vec_aligned(65);
float out0[98] __attribute__((aligned(SIMD_ALIGN))) = {0};
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float out1[65] __attribute__((aligned(SIMD_ALIGN))) = {0};
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propagate_fwd(weights[0], input, outputs[0], biases[0]);
relu_inplace(outputs[0]->data, 98);
propagate_fwd(weights[1], outputs[0], outputs[1], biases[1]);
relu_inplace(outputs[1]->data, 65);
propagate_fwd(weights[0], input->data, out0, biases[0]);
relu_inplace(out0, 98);

memset(outputs[0]->data, 0, 50 * sizeof(f32));
propagate_fwd(weights[1], out0, out1, biases[1]);
relu_inplace(out1, 65);

propagate_fwd(weights[2], outputs[1], outputs[0], biases[2]);
relu_inplace(outputs[0]->data, 50);
memset(out0, 0, 50 * sizeof(f32));

memset(outputs[1]->data, 0, 30 * sizeof(f32));
propagate_fwd(weights[2], out1, out0, biases[2]);
relu_inplace(out0, 50);

propagate_fwd(weights[3], outputs[0], outputs[1], biases[3]);
relu_inplace(outputs[1]->data, 30);
memset(out1, 0, 30 * sizeof(f32));

memset(outputs[0]->data, 0, 25 * sizeof(f32));
propagate_fwd(weights[3], out0, out1, biases[3]);
relu_inplace(out1, 30);

propagate_fwd(weights[4], outputs[1], outputs[0], biases[4]);
relu_inplace(outputs[0]->data, 25);
memset(out0, 0, 25 * sizeof(f32));

memset(outputs[1]->data, 0, 40 * sizeof(f32));
propagate_fwd(weights[4], out1, out0, biases[4]);
relu_inplace(out0, 25);

propagate_fwd(weights[5], outputs[0], outputs[1], biases[5]);
relu_inplace(outputs[1]->data, 40);
memset(out1, 0, 40 * sizeof(f32));

memset(outputs[0]->data, 0, 52 * sizeof(f32));
propagate_fwd(weights[5], out0, out1, biases[5]);
relu_inplace(out1, 40);

propagate_fwd(weights[6], outputs[1], outputs[0], biases[6]);
softmax_inplace(outputs[0]->data, 52);
memset(out0, 0, 52 * sizeof(f32));

u8 prediction = argmax(outputs[0]->data, 52);
propagate_fwd(weights[6], out1, out0, biases[6]);
softmax_inplace(out0, 52);

free(outputs[0]->data);
free(outputs[0]);
free(outputs[1]->data);
free(outputs[1]);
u8 prediction = argmax(out0, 52);

return prediction;
}
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