The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: Research Posters
Author: Dhabaleswar K. (DK) Panda (The Ohio State University), Sameer Shende (University of Oregon; ParaTools, Inc.), Ahmad Abdelfattah (University of Tennessee, Knoxville), Yifeng Cui (San Diego Supercomputer Center (SDSC))
Supervisor:
Abstract: We propose a co-design approach that integrates two powerful tools—MVAPICH and TAU—to demonstrate the new possibilities for performance-guided control and optimization for two large-scale applications—AWP-ODC and heFFTe. AWP-ODC is a highly scalable parallel finite-difference application with point-to-point operations that enables 3D earthquake calculations, while heFFTe is a massively parallel application that provides scalable and efficient implementations of the widely used Fast Fourier Transform using several MPI primitives. Through a deep integration between MVAPICH and TAU, the two applications can identify their performance bottlenecks on various supercomputers with different architectures. AWP-ODC and heFFTe can also act as representative real-world benchmarks to MVAPICH and TAU. We show how the co-design approach enables AWP-ODC and heFFTe to deliver better performance on cutting-edge HPC architectures. This is achieved using 1) more optimized and fine-tuned collective operations, and 2) reduced network traffic through real-time data compression.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF