Scalable and distributed computing systems are widely deployed but hide a large toll in terms of energy consumption. A wider adoption of dataflow concepts at any level of the software/hardware stack of HPC system can lead to a reduction of the intrinsic inefficiency of current systems. By leveraging structured parallel programming based on FastFlow, we are exploring the effectiveness of DataFlow Threads (DF-Threads) in tandem with such programming model for Edge Computing and HPC.
Giorgi, R. (2024). DF-Threads: A Scalable and Efficient Execution Paradigm for Edge Computing and HPC. In 2nd Special Track on Big Data and High-PerformanceComputing (BigHPC 2024) co-located with the 3rd ItalianConference on Big Data and Data Science (ITADATA 2024) (pp.44-51). CEUR-WS.
DF-Threads: A Scalable and Efficient Execution Paradigm for Edge Computing and HPC
Giorgi, Roberto
Writing – Original Draft Preparation
2024-01-01
Abstract
Scalable and distributed computing systems are widely deployed but hide a large toll in terms of energy consumption. A wider adoption of dataflow concepts at any level of the software/hardware stack of HPC system can lead to a reduction of the intrinsic inefficiency of current systems. By leveraging structured parallel programming based on FastFlow, we are exploring the effectiveness of DataFlow Threads (DF-Threads) in tandem with such programming model for Edge Computing and HPC.
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https://hdl.handle.net/11365/1277977