Abstract

As HPC progresses toward exascale, writing applications that are highly efficient, portable, and support programmer productivity is becoming more challenging than ever. The growing scale, diversity, and heterogeneity in compute platforms increases the burden on software to efficiently use available distributed parallel resources. This burden has fallen on developers who, increasingly, are experts in application domains rather than traditional computer scientists and engineers. We propose CASPER-Compiler Abstractions Supporting high Performance on Extreme-scale Resources-a novel domain-specific compiler and runtime framework to enable domain scientists to achieve high performance and scalability on complex HPC systems. CASPER extends domain-specific languages with machine learning to map software tasks to distributed, heterogeneous resources, and provides a runtime framework to support a …

Date

November 11, 2020

Authors

Connor Imes, Alexei Colin, Naifeng Zhang, Ajitesh Srivastava, Viktor Prasanna, John Paul Walters

Conference

2020 IEEE/ACM Fifth International Workshop on Extreme Scale Programming Models and Middleware (ESPM2)

Pages

1-7

Publisher

IEEE