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: Nilesh Chaturvedi (Institute for Advanced Computational Science, Stony Brook University; Stony Brook University, Department of Applied Mathematics and Statistics), Joseph Schuchart (Institute for Advanced Computational Science, Stony Brook University), Robert J. Harrison (Institute for Advanced Computational Science, Stony Brook University; Stony Brook University, Department of Applied Mathematics and Statistics)
Supervisor:
Abstract: We present a framework that implements multiresolution analysis (MRA) on top of Template Task Graph (TTG), a distributed, task-based data-flow programming model. MRA is broadly applied across scientific domains for its ability to capture both local and global features with high accuracy, and its adaptive tree-based structure maps naturally onto data-flow execution models. TTG addresses central challenges in modern high performance computing by improving programmer productivity and enabling performance portability across heterogeneous architectures. To the best of our knowledge, this ongoing work is the first demonstration of a multiwavelet-based MRA achieving substantial performance gains on GPUs. We will present our work using visual artifacts in the poster to demonstrate the challenges and proposed solution.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF