Motivation: Non-efficient exploitation of a large-scale of parallelism, by current programing models.
TERAFLUX:Develop a coarse grain dataflow solution to harness large-scale parallelism.
TERAFLUX tool chain targets programing models, compiler analysis, and a reliable architecture.
University of Delaware Objectives in TERAFLUX
- Survey state-of-the-art models in dataflow-inspired execution models and implementations.
- Propose new methods/tools applicable to dataflow-inspired teradevices.
- Evaluate the opportunity to add percolation and power-aware task scheduling directly using DF-thread.
- Evaluate the opportunity to add percolation and power-aware scheduling to the Codelet Model.
- Survey state-of-the-art techniques in code and data movement and power-aware task scheduling.
- Comparison between the Codelet Execution Model and the TERAFLUX model: DF-thread.
- Characterization of the differences between both the Codelet and DF-thread Models.
- Joint research papers between the university of Delaware and the university of Siena.