SC15 Austin, TX

Active Global Address Space (AGAS): Global Virtual Memory for Dynamic Adaptive Many-Tasking Runtimes


Student: Abhishek Kulkarni (Indiana University)
Advisor: Andrew Lumsdaine (Indiana University)
Abstract: While the communicating sequential processes model, as realized by the Message Passing Interface, is presently the dominant scalable computing paradigm, such programs neither excel at the irregular computation patterns present in big data and adaptive execution, nor obviously scale to exascale. Dynamic and adaptive many-tasking execution models are suggested as alternatives to MPI in these realms. In such models, programs are described as lightweight tasks concurrently operating on data residing in a global address space. By their nature, these models need load balancing to be effective. When work follows data this naturally takes the form of dynamically balancing data. We present High Performance ParalleX (HPX), a dynamic adaptive many-tasking runtime that maintains a scalable high-performance virtual global address space using distributed memory hardware. We describe the design and implementation of active global address space (AGAS) in HPX and demonstrate its benefit for global load balancing.

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