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DOI

10.20371/INAF/PUB/2018_00006

Creators 
(name, orcid, 
affilation)

Goz David, ORCID: 0000-0001-9808-2283, INAF-OATs
Tornatore Luca, ORCID: 0000-0003-1751-0130, INAF-OATs
Sara Bertocco, ORCID: 0000-0003-2386-623X, INAF-OATs
Giuliano Taffoni, ORCID: 0000-0002-4211-6816, INAF-OATs

Main Affiliation OATs
Titles Performance of direct N-body code on ARM64 SoC
Series INAF-OATs Technical Report
Series Number 241
Publication Year 2018
Resource type text
Language en
abstract  The ExaNeSt H2020 project will produce a prototype based on ARM64 CPUs and FPGA-based accelerators  implementing a co-design approach where scientific applications requirements are driving the hardware design.
We present strategies adopted in order to port our direct N-body code on an ARM SoC cluster, called INCAS, deployed at INAF-OATs. Each computational node is based on 64-bit ARMv8 Cortex-A72/Cortex-A53 core design, powered by the Mali-T864 GPU. We present the strategies to optimize the code and we discuss in details results of performance tests carried on ARM CPUs and GPUs, showing that embedded GPUs can be effectivelyused to accelerate the calculation, and that are promising also because of their energy efficiency, which is an important design in future exascale platforms.
pdf 

Performance of direct N-body code on ARM64 SoC