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hpc-2022-g3/OpenMP/linear-algebra/kernels/atax/atax.c

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#include <stdio.h>
#include <unistd.h>
#include <string.h>
#include <math.h>
/* Include polybench common header. */
#include <polybench.h>
/* Include benchmark-specific header. */
/* Default data type is double, default size is 4000. */
#include "atax.h"
// Workaround for the editor not finding M_PI
// It is exclusive to the GNU C compiler
// https://www.gnu.org/software/libc/manual/html_node/Mathematical-Constants.html
#ifndef M_PI
#define M_PI 3.141
#endif
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/* Array initialization. */
static void init_array(int nx, int ny,
DATA_TYPE POLYBENCH_2D(A, NX, NY, nx, ny),
DATA_TYPE POLYBENCH_1D(x, NY, ny))
{
int i, j;
/// Initialize the `x` array with PI and its multiples.
#ifdef TOGGLE_INIT_ARRAY_1
#pragma omp parallel for num_threads(THREAD_COUNT) schedule(static)
#endif
for (i = 0; i < ny; i++) {
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x[i] = i * M_PI;
}
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/// Initialize the `A` matrix
#ifdef TOGGLE_INIT_ARRAY_2
#pragma omp parallel for num_threads(THREAD_COUNT) schedule(static)
#endif
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for (i = 0; i < nx; i++) {
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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}
/* DCE code. Must scan the entire live-out data.
Can be used also to check the correctness of the output. */
static void print_array(int nx,
DATA_TYPE POLYBENCH_1D(y, NX, nx))
{
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]);
}
fprintf(stderr, "\n");
}
/* Main computational kernel. The whole function will be timed,
including the call and return. */
static void kernel_atax(int nx, int ny,
DATA_TYPE POLYBENCH_2D(A, NX, NY, nx, ny),
DATA_TYPE POLYBENCH_1D(x, NY, ny),
DATA_TYPE POLYBENCH_1D(y, NY, ny))
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{
int i, j;
#ifdef TOGGLE_KERNEL_ATAX_1
#pragma omp parallel for num_threads(THREAD_COUNT) schedule(static)
#endif
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for (i = 0; i < _PB_NY; i++)
y[i] = 0;
/// This computes... something? I guess whatever ATAX is?
// Now this gives a nice speedup, especially with a lot more threads than the count!
// THREAD_COUNT * 4 seems to be the best on my local computer. What's the best for the Jetson Nano?
#ifdef TOGGLE_KERNEL_ATAX_2
#pragma omp parallel for num_threads(THREAD_COUNT) schedule(static)
#endif
for (i = 0; i < _PB_NX; i++)
{
/// Every iteration has its own tmp variable
DATA_TYPE tmp = 0;
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for (j = 0; j < _PB_NY; j++) {
/// Which gets increased by a bit on every iteration
tmp += A[i][j] * x[j];
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}
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for (j = 0; j < _PB_NY; j++) {
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/// Which is later used for to compute ATAX
y[j] = y[j] + A[i][j] * tmp;
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}
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}
}
int main(int argc, char **argv)
{
/* Retrieve problem size. */
int nx = NX;
int ny = NY;
/* Variable declaration/allocation. */
POLYBENCH_2D_ARRAY_DECL(A, DATA_TYPE, NX, NY, nx, ny);
POLYBENCH_1D_ARRAY_DECL(x, DATA_TYPE, NY, ny);
POLYBENCH_1D_ARRAY_DECL(y, DATA_TYPE, NY, ny);
/* Start timer. */
polybench_start_instruments;
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/* Initialize array(s). */
init_array(nx, ny, POLYBENCH_ARRAY(A), POLYBENCH_ARRAY(x));
/* Run kernel. */
kernel_atax(nx, ny,
POLYBENCH_ARRAY(A),
POLYBENCH_ARRAY(x),
POLYBENCH_ARRAY(y));
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/* Stop and print timer. */
polybench_stop_instruments;
polybench_print_instruments;
/* Prevent dead-code elimination. All live-out data must be printed
by the function call in argument. */
polybench_prevent_dce(print_array(nx, POLYBENCH_ARRAY(y)));
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/* Be clean. */
POLYBENCH_FREE_ARRAY(A);
POLYBENCH_FREE_ARRAY(x);
POLYBENCH_FREE_ARRAY(y);
return 0;
}