CUDA architectures are frequently used alongside MPI parallelism and host-side multicore and multi-thread parallelism. CUDA introduces developers to a number of new concepts that are not encountered in serial or other parallel programming paradigms.
Visibility into these elements is critical for troubleshooting and tuning applications that make use of CUDA. HPC developers need to be able to harness the power of the GPU and reduce the time that it takes their applications to run and generate results.
Debug CUDA Applications Quickly
Download the white paper to learn:
- Challenges of CUDA and heterogeneous acceleration architectures.
- How to successfully harness the power of GPUs.
- How to view all three levels of parallelism within a single debugging session.