 	printf("Finished.  nsamps=%d\n", nsamps_tot);
 	printf("Computing Sample mean...\n");
 	compute_sample_mean<<<N, 1>>>(samples, sample_mean, nsamps_tot, N);
-	compute_sample_covariance<<<N*(N+1)/2, 1>>>(samples, sample_covariance, nsamps_tot, N);
+	compute_sample_covariance<<<N, N>>>(samples, sample_covariance, nsamps_tot, N);
 	/*copy back sample  mean*/
 	cudaMemcpy(sample_mean_res, sample_mean, mean_size, cudaMemcpyDeviceToHost);
 	cudaMemcpy(samples_res, samples, samples_size, cudaMemcpyDeviceToHost);
-	cudaMemcpy(sample_covariance_res, sample_covariance, cov_size, cudaMemcpyDeviceToHost);
+	cudaMemcpy(sample_covariance_res, sample_covariance, full_cov_size, cudaMemcpyDeviceToHost);
 
 	/* Display*/
 	for(i=0; i<N; i++)

__global__ void compute_sample_covariance(float* samples, float* sample_covariance, int nsamps, int N)
{
	int i = blockIdx.x;
	
	sample_covariance[i] = 0.0;
	for(int samp = 0; samp<nsamps; samp++)
	{
		sample_covariance[i] += samples[samp*N+i]*samples[samp*N+j];
	}
	sample_covariance[i] = sample_covariance[i]/nsamps;

}


	dim3 cov_block(N, N);

	cudaMalloc(&sample_mean, mean_size);
	cudaMalloc(&sample_covariance, full_cov_size);
	cudaMalloc(&samples, samples_size);
	cudaMalloc(&alpha, mean_size);
	cudaMalloc(&beta, cov_size);
