CODEWITHSUNDEEP
c++cudathrust
postelrich
postelrich

Reputation: 3496

thrust::system::system_error in transform_reduce

I am running a monte carlo simulation using Thrust on an Nvidia card with 2.1 compute capability. If I try to transform_reduce the whole device_vector at once, I get the following error. Its not a matter of using up the memory on device because the vectors are that big (~1-10mb). I know my code is right because it works if I compile with openmp and run on the host only. What can be causing this problem?

Unhandled exception at 0x776e15de in mccva.exe: Microsoft C++ exception: thrust::system::system_error at memory location 0x0014cb28.

But if I do the transform_reduce in chunks it works fine until I scale the number of timesteps in the simulation which it then gives the same error.

//run the Monte Carlo simulation
zpath * norm_ptr = thrust::raw_pointer_cast(&z[0]);
cout << "initialized raw pointer" << endl;
thrust::device_vector<ctrparty> devctrp = ctrp;
assert(devctrp.size()==ctrp.size());
cout << "Initialized device vector" << endl;
cout << "copied host vec to device vec" << endl;

float cva = 0;
for(unsigned int i=0; i<5; i++)
{
    if(i<4)
        cva += (1-R) * thrust::transform_reduce(devctrp.begin()+i*2000, devctrp.begin() + (i+1)*2000 - 1, calc(norm_ptr, dt, r, sims, N), 0.0f, sum());
    else
        cva += (1-R) * thrust::transform_reduce(devctrp.begin()+i*2000, devctrp.begin() + (i+1)*2000, calc(norm_ptr, dt, r, sims, N), 0.0f, sum());
}

I get the error when I try this:

float cva = 0.0f;
try
{
    cva = thrust::transform_reduce(devctrp.begin(), devctrp.end(), calc(norm_ptr, dt, r, sims, N), 0.0f, sum()); //get the simulated CVA
}
catch(thrust::system_error e)
{
    printf(e.what());
}

I'm using VS2010 and when it breaks at the errors it points to the following in the dbgheap.c file.

__finally {
    /* unlock the heap
     */
    _munlock(_HEAP_LOCK);
}

Upvotes: 0

Views: 1221

Answers (1)

Rodion
Rodion

Reputation: 886

I had that kind of error with thrust when I forgot to adjust the Properties of the project to my CUDA card compute capability

Configuration Properties > CUDA C\C++ > Device > Code Generation change compute_10,sm_10 to your GPU compute capability

For Nvidia card with 2.1 compute capability it will be compute_20,sm_21

Upvotes: 2

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