The International Conference for High Performance Computing, Networking, Storage, and Analysis
The International Conference for High Performance Computing, Networking, Storage, and Analysis
Poster Type: ACM Student Research Competition, Undergraduate
Author: Matthew Chung (University of California, Riverside; Oak Ridge National Laboratory (ORNL))
Supervisor: Keita Teranishi (Oak Ridge National Laboratory (ORNL))
Abstract: There is a growing need for the efficient solution of many small eigenvalue problems (up to N = 1500) that arise in emerging scientific applications. These small-to-medium sized problems present unique computational challenges, particularly when thousands or millions of such problems must be solved repeatedly. This work presents Orchid, a novel distributed, heterogeneous, batched eigenvalue solver based on the IRIS runtime. Orchid can utilize all compute platforms in both heterogeneous nodes and clusters by harnessing the capabilities of the IRIS architecture. Orchid leverages heterogeneous architectures across multiple nodes by partitioning the application task DAG intelligently and orchestrates multiple instances of the IRIS runtime via MPI. We evaluate our proposal against two heterogeneous hardware configurations and Frontier, demonstrating Orchid’s performance utilizing both intra-node and inter-node heterogeneity.
Best Poster Finalist (BP): no
Poster: PDF
Poster Summary: PDF