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Time Iterated Dataflow: A Dataflow Execution Model for HPC Programs
SESSION: Doctoral Research Showcase (1 of 2)
EVENT TYPE: Doctoral Research Showcase
TIME: 2:15PM - 2:30PM
SESSION CHAIR: Volodymyr Kindratenko
ABSTRACT: This work presents the Time Iterated Dataflow (TIEFlow) execution model. The TIEFlow model extends the Dynamic Dataflow model to efficiently develop and execute HPC programs in multicore processors. The TIEFlow model addresses the fact that parallel loops are abundant in HPC programs by expresses programs as graphs where each node represents a parallel loop. Program graphs in TIEFlow use weighted arcs to represent loop carried dependencies. The resulting graph model allows simple representation of commonly used constructs such as task parallelism, task pipelining, and program composability.
TIEFlow has been implemented and has resulted in a number of research and commercial tools including the SWARM system currently offered by ET International, a fully distributed runtime system that does not require support from an OS and a programming model with its associated compiler. Preliminary results where sample HPC kernels were developed show that TIEFlow is appropriate to develop and execute HPC programs.