Methodologies for Mapping Tasks onto Heterogeneous Processing Systems

摘要

Complete application tasks, of the type that would be of interest to RomeLaboratory, are large and complex. One approach to dealing with them is heterogeneous computing. Two types of heterogeneous computing systems are: (1) mixed-mode, wherein multiple types of parallelism are available on a single machine; and (2) mixed-machine, wherein a suite of different high-performance computers is connected by high-speed links. In this effort, we studied ways to decompose an application into subtasks and then match each subtask to the mode or machine, which results in the smallest total task execution time. Our accomplishments include: (1) conducting a mixed-mode case study; (2) developing an approach for automatically decomposing a task for mixed-mode execution, and assigning modes to subtasks; (3) extending this approach for use as an heuristic for a particular class of mixed-machine heterogeneous computing systems; (4) surveying the state-of-the-art of heterogeneous computing, and constructing a conceptual framework for automatic mixed-machine heterogeneous computing; (5) examining how to estimate non-deterministic execution of subtasks and complete tasks; and (6) devising an optimal scheme for inter-machine data transfers for a given matching of subtasks to machines.