Enabling extreme scale applications on heterogeneous hardware

We are working towards delivering a new validated programming environment, extending the programmability and maximizing the productivity of application development for large-scale heterogeneous computing systems.

EPiGRAM-HS is motivated by the increasing presence of heterogeneous technologies on pre-exascale supercomputers and by the need of porting key HPC and emerging applications to these systems on time for exascale.

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EPiGRAM-HS is consisted of 6 key European universities and enterprises focused on high performance computing.


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Dong Li from UC Merced on the development of runtimes for automatic data management on heterogeneous memories: a trade-off between the cost of memory profiling, online analysis and data migration. EPiGRAM-HS meeting at ETH. 👩‍💻👨‍💻

EPCC Dan Holmes explains how Epigram-HS @EU_H2020 project is progressing through heterogeneous network challenges to help programming models for #Exascale @epigramhs @Cray PDC/KTH @EPCCed @ETH @Juelich @Fraunhofer @ECMWF https://t.co/jv6d4NUvc2

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Delivering a new validated programming environment for large-scale heterogeneous computing systems for enabling HPC and emerging deep-learning frameworks to run on large-scale heterogeneous systems at maximum performance.

Extending the programmability of large-scale heterogeneous systems with GPUs, FPGAs, HBM and NVM, by introducing new concepts, adding functionalities and carrying out implementations in two widely-used HPC programming systems for large-scale supercomputers (MPI and GASPI)

Maximizing the productivity of application development on heterogeneous supercomputers by providing auto-tuned collective communication, a framework for automatic code generation for FPGAs, a memory abstraction device comprised of APIs and a runtime for automatic data placement on diverse memories, and a DSL for large-scale deep-learning frameworks.