Avalanche: a fine-grained flow graph model for irregular applications on distributed-memory systems

  • Authors:

  • Jeremiah J. Willcock;Ryan R. Newton;Andrew Lumsdaine

  • Affiliations:

  • Indiana University, Bloomington, IN, USA;Indiana University, Bloomington, IN, USA;Indiana University, Bloomington, IN, USA

  • Venue:
  • Proceedings of the 1st ACM SIGPLAN workshop on Functional high-performance computing
  • Year:
  • 2012

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Abstract

Flow graph models have recently become increasingly popular as a way to express parallel computations. However, most of these models either require specialized languages and compilers or are library-based solutions requiring coarse-grained applications to achieve acceptable performance. Yet, graph algorithms and other irregular applications are increasingly important to modern high-performance computing, and these applications are not amenable to coarsening without complicating algorithm structure. One effective existing approach for these applications relies on active messages;. However, the separation of control flow between the main program and active message handlers introduces programming difficulties. To ameliorate this problem, we present Avalanche, a flow graph model for fine-grained applications that automatically generates active-message handlers. Avalanche is built as a C++ library on top of our previously-developed Active Pebbles model; a set of combinators builds graphs at compile-time, allowing several optimizations to be applied by the library and a standard C++ compiler. In particular, consecutive flow graph nodes can be fused; experimental results show that flow graphs built from small components can still efficiently operate on fine-grained data.