In order to analyze the current performance, we port a suite of representative benchmarks, and the mature mini-apps TeaLeaf, CloverLeaf, and SNAP to the Clang OpenMP 4.5 compiler. We then collect performance results for those ports, and their equivalent CUDA ports, on an NVIDIA Kepler GPU. Through manual analysis of the generated code, we are able to discover the root cause of the performance differences between OpenMP and CUDA.
A number of improvements can be made to the existing compiler implementation to enable performance that approaches that of hand-optimized CUDA. Our first observation was that the generated code did not use fused-multiply-add instructions, which was resolved using an existing flag. Next we saw that the compiler was not passing any loads through non-coherent cache, and added a new flag to the compiler to assist with this problem.
We then observed that the compiler partitioning of threads and teams could be improved upon for the majority of kernels, which will guide future work to ensure that the compiler can pick more optimal defaults. We uncovered a register allocation issue with the existing implementation that, when fixed alongside the other issues, enables performance that is close to CUDA.
Finally, we use some different kernels to emphasize that support for managing memory hierarchies needs to be introduced into the specification, and propose a simple option for programming shared caches.
|Title of host publication||Proceedings of PMBS 2016|
|Subtitle of host publication||7th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems - Held in conjunction with SC 2016: The International Conference for High Performance Computing, Networking, Storage and Analysis|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Number of pages||11|
|Publication status||Published - Mar 2017|
|Event||7th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems, PMBS 2016 - Salt Lake City, United States|
Duration: 14 Nov 2016 → …
|Conference||7th International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computing Systems, PMBS 2016|
|City||Salt Lake City|
|Period||14/11/16 → …|