Seminario: “A Data-Flow Execution Engine for Scalable Embedded Computing” di Marco Procaccini

Abstract: "The end of Dennard scaling, Moore’s law, and the resulting difficulty of increasing clock frequency, forced the engineering community to shift to the multi/many-core processors and multi-node systems as an alternative way to improve performance. An increased core number benefits many workloads, but programming limitations still reduce the performance due to the not fully exploited parallelism. From this perspective, new execution models are arising to overcome such limitations to scale up performance. Execution models like Data-Flow are capable of taking advantage of the full parallelism, thanks to the possibil- ity of creating many asynchronous threads that can run in parallel. These threads may encapsulate the data to be processed, their dependencies, and, once completed, write their output for other threads. Data-Flow Threads (DF-Threads) is a novel Data-Flow execution model for mapping threads on local or distributed cores transparently to the programmer. This model is capable of being parallelized massively among different cores, and it handles even hundreds of thousands or more Data-Flow threads with their associated data regions. Further implementation and evaluation of the DF-Threads model are presented in this seminar. The execution model can exploit the full parallelism of modern heterogeneous embedded architectures (e.g., the AXIOM-Board). The work relies on the introduction of ”Data-Flow engine” (DF-Engine) for accelerating the function execution and spawning many asynchronous, data-driven threads across several general-purpose cores of a multi-core/node system."

Il seminario si svolgerà in modalità telematica sul canale vocale #seminars di Discord.

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