Adaptive computation over dynamic and heterogeneous networks

Abstract

Over the last two decades, efficient message passing libraries have been developed for parallel scientific computation. Concurrently, programming languages have been created supporting dynamically reconfigurable distributed systems over the heterogeneous Internet. In this paper, we introduce SALSA-MPI, an actor programming language approach to scientific computing that extends MPI with a checkpointing and migration API and a runtime system that manages both periodic checkpoints and process or application migration. The goal is to enable dynamic network reconfiguration and load balancing without sacrificing application performance or requiring extensive code modifications. As driving technology for this effort of unifying parallel and distributed computing, we plan to use adaptive solvers of partial differential equations. Fields as diverse as fluid dynamics, material science, biomechanics, and ecology make use of parallel adaptive computation, but target architectures have traditionally been supercomputers and tightly-coupled clusters. SALSA-MPI is intended to allow these computations to make efficient use of more distributed and dynamic computing resources.