Hi,
Hi everyone!
I am following Jonas Hahnfeld’s blog post
(Building and Using LLVM/Clang 7.0 with OpenMP Offloading to NVIDIA GPUs)
to build clang to test some simple target offloading workloads.
The complete code can be found at the end.
I tried clang 7.0.1 and llvm trunk (9.0.0). omp_get_num_devices()
returned 0 for both compilers although the server I am running this on
has Quadro P4000 on it. As an attempt to fix the issue, I added
compute compatibility 61 and set it to default. This did not help.
Additionally, the binary built by trunk cannot even offload to CPU
targets, reporting error
"Libomptarget fatal error 1: default offloading policy must switched
to mandatory or disabled”
May I get some help from the community on what to look into to get
this microbenchmark to run on the GPU?
Thanks!
######################################################################################################
#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <omp.h>
#define VALUE_TYPE double
#define ARR_SIZE 128 * 1024 * 1024
struct timespec timespec_diff(struct timespec t1, struct timespec t2)
{
struct timespec diff;
diff.tv_nsec = t1.tv_nsec - t2.tv_nsec;
diff.tv_sec = t1.tv_sec - t2.tv_sec;
if (diff.tv_nsec < 0) {
diff.tv_nsec += 1000000000;
diff.tv_sec -= 1;
}
return diff;
}
double timespec_to_sec(struct timespec t) {
double sec = (double)t.tv_sec;
double nsec = (double)t.tv_nsec;
return sec + nsec * 1E-9;
}
void gen_rand_number(VALUE_TYPE *arr, int size) {
for (int i = 0; i < size; i++) {
arr[i] = (VALUE_TYPE)rand();
}
}
void cpu_add(VALUE_TYPE *out, VALUE_TYPE *in_1, VALUE_TYPE *in_2, int
size) {
for (int i = 0; i < size; i++) {
out[i] = in_1[i] + in_2[i];
}
}
void omp_cpu_add(VALUE_TYPE *out, VALUE_TYPE *in_1, VALUE_TYPE *in_2,
int size) {
#pragma omp parallel for
for (int i = 0; i < size; i++) {
out[i] = in_1[i] + in_2[i];
}
}
void omp_gpu_add(VALUE_TYPE *out, VALUE_TYPE *in_1, VALUE_TYPE *in_2,
int size) {
#pragma omp target map(to:in_1, in_2) map(from:out)
I think the compiler will have trouble to correctly map / transfer the arrays here. Can you try specifying array sections?
Should be as easy as "map(to:in_1[0:size], in_2[0:size]) map(from:out[0:size])"
Hope this helps and fixes the problem 
Jonas