Limits on the cuSparse tridiagonal solver? - cuda

Question

I have decided to rewrite one of my serial codes to CUDA. A large section of the code is to invert a large tridiagonal matrix for differing right hand sides. I then came across cusparseSgtsv from the cuSparse library. I got a sample code to work for small matrices, but when the matrix size got above 1024, nothing but nan. Did I miss something in the documentation?
Here is the sample code. For N=1024, the code works fine. For N=1025, it is nan all the way down.
#include<iostream>
#include<cuda_runtime.h>
#include<cusparse_v2.h>
using namespace std;
__global__ void assignMat(float *a,float *b,float *c,float *r)
{
int tid=threadIdx.x+blockDim.x*blockIdx.x;
a[tid]=0;
b[tid]=1;
c[tid]=0;
r[tid]=tid;
}
int main()
{
float *d_a,*d_b,*d_c,*d_r;
float *h_r;
int N=1025;
cusparseStatus_t status;
cusparseHandle_t handle=0;
status=cusparseCreate(&handle);
h_r=(float *)malloc(N*sizeof(float));
cudaMalloc((void **)&d_a,N*sizeof(float));
cudaMalloc((void **)&d_b,N*sizeof(float));
cudaMalloc((void **)&d_c,N*sizeof(float));
cudaMalloc((void **)&d_r,N*sizeof(float));
assignMat<<<1,N>>>(d_a,d_b,d_c,d_r);
status=cusparseSgtsv(handle,N,1,d_a,d_b,d_c,d_r,N);
if (status != CUSPARSE_STATUS_SUCCESS)
{
cout << status << endl;
}
else
{
cudaMemcpy(h_r,d_r,N*sizeof(float),cudaMemcpyDeviceToHost);
for (int i=0;i<N;i++)
cout << i << " " << h_r[i] << endl;
}
free(h_r);
cudaFree(d_a);cudaFree(d_b);cudaFree(d_c);cudaFree(d_r);
}

Answer 1

Did I miss something in the documentation?
Not in the cuSparse documentation, no.
However, there is a hard limit on the number of threads per block, so your assignMat kernel stops working once N > 1024. You can read about how to select legal kernel launch parameters here. If your code contained error checking or you ran the program with cuda-memcheck, you probably would have been able to detect the problem yourself at runtime.