Coyote: an open source simulation tool to enable RISC-V in HPC

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The confluence of technology trends and economics has reincarnated computer architecture and specifically, software-hardware co-design. We are entering a new era of a completely open ecosystem, from applications to chips and everything in between. The software-hardware co-design of supercomputers for tomorrow requires flexible tools today that will take us to the Exascale and beyond. The MareNostrum Experimental Exascale Platform (MEEP) addresses this by proposing a flexible FPGA-based emulation platform, designed to explore hardware-software co-designs for future RISC-V supercomputers. This platform is part of an open ecosystem, allowing its infrastructure to be reused in other projects. MEEP's inaugural emulated system will be a RISC- V based self-hosted HPC vector and systolic array accelerator, with a special aim at efficient data movement. Early development stages for such an architecture require fast, scalable and easy to modify simulation tools, with the right granularity and fidelity, enabling rapid design space exploration. Being a part of MEEP, this paper introduces Coyote, a new open source, execution-driven simulator based on the open source RISC- VISA and which can provide detailed insights at various levels and granularities. Coyote focuses on data movement and the modelling of the memory hierarchy of the system, which is one of the main hurdles for high performance sparse workloads, while omitting lower level details. As a result, performance evaluation shows that Coyote achieves an aggregate simulation of up to 6 MIPS when modelling up to 128 cores. This enables the fast comparison of different designs for future RISC- V based HPC architectures.

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Pérez, B.; Fell, A.; Davis, J.D. Coyote: an open source simulation tool to enable RISC-V in HPC. A: Design, Automation and Test in Europe Conference and Exhibition. "2021 Design, Automation & Test in Europe Conference & Exhibition (DATE): Grenoble, France, 1-5 February 2021: proceedings". Institute of Electrical and Electronics Engineers (IEEE), 2021, p. 130-135. ISBN 978-3-9819263-5-4. DOI 10.23919/DATE51398.2021.9474080.

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978-3-9819263-5-4

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1558-1101

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