Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application
New challenges in Astronomy and Astrophysics (AA) are urging the need for many exceptionally computationally intensive simulations. “Exascale” (and beyond) computational facilities are mandatory to address the size of theoretical problems and data coming from the new generation of observational faci...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-04-01
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| Series: | Computation |
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| Online Access: | https://www.mdpi.com/2079-3197/8/2/34 |
| _version_ | 1827718459234975744 |
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| author | David Goz Georgios Ieronymakis Vassilis Papaefstathiou Nikolaos Dimou Sara Bertocco Francesco Simula Antonio Ragagnin Luca Tornatore Igor Coretti Giuliano Taffoni |
| author_facet | David Goz Georgios Ieronymakis Vassilis Papaefstathiou Nikolaos Dimou Sara Bertocco Francesco Simula Antonio Ragagnin Luca Tornatore Igor Coretti Giuliano Taffoni |
| author_sort | David Goz |
| collection | DOAJ |
| description | New challenges in Astronomy and Astrophysics (AA) are urging the need for many exceptionally computationally intensive simulations. “Exascale” (and beyond) computational facilities are mandatory to address the size of theoretical problems and data coming from the new generation of observational facilities in AA. Currently, the High-Performance Computing (HPC) sector is undergoing a profound phase of innovation, in which the primary challenge to the achievement of the “Exascale” is the power consumption. The goal of this work is to give some insights about performance and energy footprint of contemporary architectures for a real astrophysical application in an HPC context. We use a state-of-the-art N-body application that we re-engineered and optimized to exploit the heterogeneous underlying hardware fully. We quantitatively evaluate the impact of computation on energy consumption when running on four different platforms. Two of them represent the current HPC systems (Intel-based and equipped with NVIDIA GPUs), one is a micro-cluster based on ARM-MPSoC, and one is a “prototype towards Exascale” equipped with ARM-MPSoCs tightly coupled with FPGAs. We investigate the behavior of the different devices where the high-end GPUs excel in terms of time-to-solution while MPSoC-FPGA systems outperform GPUs in power consumption. Our experience reveals that considering FPGAs for computationally intensive application seems very promising, as their performance is improving to meet the requirements of scientific applications. This work can be a reference for future platform development for astrophysics applications where computationally intensive calculations are required. |
| first_indexed | 2024-03-10T20:24:18Z |
| format | Article |
| id | doaj.art-82c7516d9af3454aa21f9ed3e1696569 |
| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-03-10T20:24:18Z |
| publishDate | 2020-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-82c7516d9af3454aa21f9ed3e16965692023-11-19T21:57:24ZengMDPI AGComputation2079-31972020-04-01823410.3390/computation8020034Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics ApplicationDavid Goz0Georgios Ieronymakis1Vassilis Papaefstathiou2Nikolaos Dimou3Sara Bertocco4Francesco Simula5Antonio Ragagnin6Luca Tornatore7Igor Coretti8Giuliano Taffoni9INAF-Osservatorio Astronomico di Trieste, 35122 Padova, ItalyICS-FORTH, GR-700 13 Heraklion, Crete, GreeceICS-FORTH, GR-700 13 Heraklion, Crete, GreeceICS-FORTH, GR-700 13 Heraklion, Crete, GreeceINAF-Osservatorio Astronomico di Trieste, 35122 Padova, ItalyINFN-Sezione di Roma, 00185 Rome, ItalyINAF-Osservatorio Astronomico di Trieste, 35122 Padova, ItalyINAF-Osservatorio Astronomico di Trieste, 35122 Padova, ItalyINAF-Osservatorio Astronomico di Trieste, 35122 Padova, ItalyINAF-Osservatorio Astronomico di Trieste, 35122 Padova, ItalyNew challenges in Astronomy and Astrophysics (AA) are urging the need for many exceptionally computationally intensive simulations. “Exascale” (and beyond) computational facilities are mandatory to address the size of theoretical problems and data coming from the new generation of observational facilities in AA. Currently, the High-Performance Computing (HPC) sector is undergoing a profound phase of innovation, in which the primary challenge to the achievement of the “Exascale” is the power consumption. The goal of this work is to give some insights about performance and energy footprint of contemporary architectures for a real astrophysical application in an HPC context. We use a state-of-the-art N-body application that we re-engineered and optimized to exploit the heterogeneous underlying hardware fully. We quantitatively evaluate the impact of computation on energy consumption when running on four different platforms. Two of them represent the current HPC systems (Intel-based and equipped with NVIDIA GPUs), one is a micro-cluster based on ARM-MPSoC, and one is a “prototype towards Exascale” equipped with ARM-MPSoCs tightly coupled with FPGAs. We investigate the behavior of the different devices where the high-end GPUs excel in terms of time-to-solution while MPSoC-FPGA systems outperform GPUs in power consumption. Our experience reveals that considering FPGAs for computationally intensive application seems very promising, as their performance is improving to meet the requirements of scientific applications. This work can be a reference for future platform development for astrophysics applications where computationally intensive calculations are required.https://www.mdpi.com/2079-3197/8/2/34astrophysicsHPCN-bodyARM-MPSoCGPUsFPGAs |
| spellingShingle | David Goz Georgios Ieronymakis Vassilis Papaefstathiou Nikolaos Dimou Sara Bertocco Francesco Simula Antonio Ragagnin Luca Tornatore Igor Coretti Giuliano Taffoni Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application Computation astrophysics HPC N-body ARM-MPSoC GPUs FPGAs |
| title | Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application |
| title_full | Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application |
| title_fullStr | Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application |
| title_full_unstemmed | Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application |
| title_short | Performance and Energy Footprint Assessment of FPGAs and GPUs on HPC Systems Using Astrophysics Application |
| title_sort | performance and energy footprint assessment of fpgas and gpus on hpc systems using astrophysics application |
| topic | astrophysics HPC N-body ARM-MPSoC GPUs FPGAs |
| url | https://www.mdpi.com/2079-3197/8/2/34 |
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