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https://github.com/Steffo99/unimore-hpc-assignments.git
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127 lines
3.6 KiB
C
127 lines
3.6 KiB
C
#include <stdio.h>
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#include <unistd.h>
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#include <string.h>
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#include <math.h>
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/* Include polybench common header. */
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#include <polybench.h>
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/* Include benchmark-specific header. */
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/* Default data type is double, default size is 4000. */
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#include "atax.h"
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// Workaround for the editor not finding M_PI
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// It is exclusive to the GNU C compiler
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// https://www.gnu.org/software/libc/manual/html_node/Mathematical-Constants.html
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#ifndef M_PI
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#define M_PI 3.141
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#endif
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/* Array initialization. */
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static void init_array(int nx, int ny,
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DATA_TYPE POLYBENCH_2D(A, NX, NY, nx, ny),
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DATA_TYPE POLYBENCH_1D(x, NY, ny))
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{
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int i, j;
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/// Initialize the `x` array with PI and its multiples.
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#pragma omp parallel for num_threads(THREAD_COUNT) schedule(static)
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for (i = 0; i < ny; i++) {
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x[i] = i * M_PI;
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}
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/// Initialize the `A` matrix with [something?]
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#pragma omp parallel for num_threads(THREAD_COUNT) schedule(static)
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for (i = 0; i < nx; i++) {
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for (j = 0; j < ny; j++) {
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A[i][j] = ((DATA_TYPE)i * (j + 1)) / nx;
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}
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}
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}
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/* DCE code. Must scan the entire live-out data.
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Can be used also to check the correctness of the output. */
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static void print_array(int nx,
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DATA_TYPE POLYBENCH_1D(y, NX, nx))
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{
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int i;
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/// Print all numbers in the array sequentially.
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// Cannot parallelize this: prints have to be sequential to make sense!
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for (i = 0; i < nx; i++) {
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fprintf(stderr, DATA_PRINTF_MODIFIER, y[i]);
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}
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fprintf(stderr, "\n");
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}
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/* Main computational kernel. The whole function will be timed,
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including the call and return. */
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static void kernel_atax(int nx, int ny,
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DATA_TYPE POLYBENCH_2D(A, NX, NY, nx, ny),
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DATA_TYPE POLYBENCH_1D(x, NY, ny),
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DATA_TYPE POLYBENCH_1D(y, NY, ny))
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{
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int i, j;
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#pragma omp parallel for num_threads(THREAD_COUNT) schedule(static)
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for (i = 0; i < _PB_NY; i++)
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y[i] = 0;
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/// This computes... something? I guess whatever ATAX is?
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// Now this gives a nice speedup, especially with a lot more threads than the count!
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// THREAD_COUNT * 4 seems to be the best on my local computer. What's the best for the Jetson Nano?
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#pragma omp parallel for num_threads(THREAD_COUNT) schedule(static)
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for (i = 0; i < _PB_NX; i++)
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{
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/// Every iteration has its own tmp variable
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DATA_TYPE tmp = 0;
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for (j = 0; j < _PB_NY; j++)
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/// Which gets increased by a bit on every iteration
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tmp += A[i][j] * x[j];
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for (j = 0; j < _PB_NY; j++)
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/// Which is later used for [something else]
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y[j] = y[j] + A[i][j] * tmp;
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}
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}
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int main(int argc, char **argv)
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{
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/* Retrieve problem size. */
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int nx = NX;
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int ny = NY;
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/* Variable declaration/allocation. */
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POLYBENCH_2D_ARRAY_DECL(A, DATA_TYPE, NX, NY, nx, ny);
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POLYBENCH_1D_ARRAY_DECL(x, DATA_TYPE, NY, ny);
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POLYBENCH_1D_ARRAY_DECL(y, DATA_TYPE, NY, ny);
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/* Initialize array(s). */
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init_array(nx, ny, POLYBENCH_ARRAY(A), POLYBENCH_ARRAY(x));
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/* Start timer. */
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polybench_start_instruments;
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// polybench_start_instruments;
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/* Run kernel. */
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kernel_atax(nx, ny,
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POLYBENCH_ARRAY(A),
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POLYBENCH_ARRAY(x),
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POLYBENCH_ARRAY(y));
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/* Stop and print timer. */
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polybench_stop_instruments;
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polybench_print_instruments;
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/* Prevent dead-code elimination. All live-out data must be printed
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by the function call in argument. */
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polybench_prevent_dce(print_array(nx, POLYBENCH_ARRAY(y)));
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/* Be clean. */
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POLYBENCH_FREE_ARRAY(A);
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POLYBENCH_FREE_ARRAY(x);
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POLYBENCH_FREE_ARRAY(y);
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return 0;
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}
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