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Teratec 2022 Forum
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Among the broad variety of challenges that arise from HPC and HPDA workloads, data movement is of paramount importance, especially on coming exascale systems featuring multiple tiers of memory and storage. While the focus has, for years, been primarily on optimizing computations, the importance of improving data handling on such architectures is now well understood. As optimization techniques can be applied at different stages (operating system, run-time system, programming environment, and so on), a middleware providing a uniform and consistent data awareness becomes necessary. In this presentation, we introduce a novel memory- and data-aware middleware called Maestro, designed for data orchestration, by a Horizon 2020 project consortium of major European actors.
Biography : Christopher Haine earned in 2017 a Ph.D. from the University of Bordeaux, on the topic of loop kernel optimisation and data layout restructuring. Christopher then joined Cray (now HPE) in the HPC/AI EMEA Research Lab, where he works as a research scientist. Christopher’s works focus on data-aware middleware, data movement in complex memory hierarchies, and optimisation and programmability of scientific applications and workflows. |