Unable to use cublasXt - cuda

Question

I tried the following simple program using cublasXt to multiply two matrices. I get all zero output. Can someone let me know why? My computer can use other cuda libraries normally, and I have two GPUs. My machine is 64bit, as is required by cublasXt.
Btw, I've checked that none of the function calls in the program returns error.
#include <stdio.h>
#include "cublasXt.h"
#include <curand.h>
void fill(double* &x, long m, long n, double val) {
x = new double[m * n];
for (long i = 0; i < m; ++i) {
for (long j = 0; j < n; ++j) {
x[i * n + j] = val;
}
}
}
int main() {
cublasXtHandle_t xt_;
cublasXtCreate(&xt_);
double *A, *B, *C;
long m = 10, n = 10, k = 20;
fill(A, m, k, 0.2);
fill(B, k, n, 0.3);
fill(C, m, n, 0.0);
double alpha = 1.0;
double beta = 0.0;
cublasXtDgemm(xt_, CUBLAS_OP_N, CUBLAS_OP_N,
m, n, k, &alpha, A, m, B, k, &beta, C, m
);
cudaDeviceSynchronize();
for (int i = 0; i < m; ++i) {
for (int j = 0; j < n; ++j) {
printf ("%lf ", C[i *n + j]);
}
printf ("\n");
}
cublasXtDestroy(xt_);
return 0;
}

Answer 1

The first issue with your code is that you have no call to cublasXtDeviceSelect. This is a necessary part of a cublasXt code, to tell the CUBLAS runtime how many devices to use and which devices to use.
As a simple proof point, try adding the following immediately after your handle creation call:
if(cublasXtCreate(&xt_) != CUBLAS_STATUS_SUCCESS) {printf("handle create fail\n"); return 1;}
int devices[1] = { 0 }; // add this line
if(cublasXtDeviceSelect(xt_, 1, devices) != CUBLAS_STATUS_SUCCESS) {printf("set devices fail\n"); return 1;} // add this line
This should cause your output to change from all zero's to all 1.2 (although only using 1 GPU)
However you will probably want to read the section of the documentation I linked above (for example if you want to use 2 GPUs, and they are of the correct type). cublasXt functionality at this time, that is included in the toolkit, for multi-GPU usage is limited to 2 devices (but note my comments below) and those 2 GPUs must be on a dual-GPU board, such as a Tesla K10 or GeForce GTX 690 (I think Titan Z or Tesla K80 should also work, just to pick other examples).
Additional details of licensing are here. You can get an evaluation version of the "Premier" package that has fewer restrictions on GPUs.