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SECTION C: ENGINEERING

Vol. 13 No. 2 (2021)

Low Energy Consumption on Post-Moore Platforms for HPC Research

DOI
https://doi.org/10.18272/aci.v13i2.2108
Submitted
December 2, 2020
Published
2021-11-11

Abstract

The increase in computational capacities has helped in the exploration, production and research process, this has allowed the use of applications that were infeasible years ago. This increase brings us a new Era (known as Post-Moore Era) and a wide range of promising devices, devices such as Single Board Computers (SBC) or Personal Computers (PC) that achieve performance that a decade ago was only found on a Server. This work presents high performance computing devices with low monetary cost and low energy cost that meet the needs for the development of research in Artificial Intelligent (AI) applications, in-situ data analysis and simulations that can be implemented on a large scale, these devices are compared in different tests, presenting advantages such as its performance per watt consumed, smart form, among others.

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References

  1. The T0P500 List. Fénix, (02, 2020). SYS-1029GQ-TRT, https://www.top500.org/system/179681, last accessed 2020/2/20.
  2. The T0P500 List, (02, 2020). Santos Dumont Hybrid - Bullx B710, https://www.top500.org/system/178569, last accessed.
  3. The T0P500 List, (06, 2020), https://www.top500.org/lists/top500/2020/06/, last accessed.
  4. M. Waldrop., (s.f.). The chips are down for Moore's law. Nature. 530 (7589): 144-147. DOI: http://dx.doi.org/10.1038/530144aISSN0028-0836. PMID 26863965.
  5. S. Matsuoka et al., (s.f.). From FLOPS to BYTES: Disruptive change in High-Performance Computing towards the Post-Moore Era. In CF '16 Proceedings of the ACM International Conference on Computing Frontiers. 2016-05-16. ACM New York, NY, USA. DOI: http://dx.doi.org/10.1145/2903150.2906830
  6. S. Matsuoka., (s.f.). Cambrian explosion of computing and big data in the Post-Moore era. In HPDC '18 Proceedings of the 27th International Symposium on High-Performance Parallel and Distributed Computing. 2018-06-11. ACM New York, NY, USA. DOI: https://doi.org/10.1145/3208040.3225055
  7. K. Barker et al., (2005). On the feasibility of optical circuit switching for high performance computing systems. In Proc. of IEEE/ACM SC 2005, pages 16-16.
  8. Take, Y., Matsutani, H., Sasaki, H., Koibuchi, M., Kuroda, T. and Amano. H., (2014). 3D noc with inductive- couplings for building-block SiPs. In IEEE Trans. on Computers, pages 748-763. 63 (3).
  9. Kagami, T., Matsutani, H., Koibuchi, M., Take, Y., Kuroda, T. and Amano, H., (02, 2016). Efficient 3-D bus architectures for inductive-coupling ThruChip Interfaces. In IEEE Trans. on VLSI systems, pages 493-506. Vol.24, No.2.
  10. Inadomi, Y., Patki, T., Inoue, K., Aoyagi, M., Rountree, R., Schulz, M., Lowenthal, D., Wada, Y., Fukazawa, K., Ueda, M., Kondo, M., and Miyoshi, I., (2015). Analyzing and mitigating the impact of manufacturing variability in power-constrained supercomputing. In Proc. of IEEE/ACM SC15.
  11. HPL- A Portable Implementation of the High-Performance Linpack Benchmark for Distributed-Memory Computers, (02, 2020). https://www.netlib.org/benchmark/hpl/
  12. Phoronix Test Suite, (02, 2020). https://www.phoronix-test-suite.com/, last accessed.
  13. Stress-ng, (02, 2020). https://wiki.ubuntu.com/Kernel/Reference/stress-ng, last accessed.
  14. Open benchmarking, (02, 2020). https://openbenchmarking.org/, last accessed.
  15. Nvidia, CUDA, (03, 2020), https://docs.nvidia.com/cuda/index.html last accessed.
  16. Kronos Group, OpenCL, (03, 2020), https://www.khronos.org/about/ last accessed.
  17. OpenACC, (03, 2020), https://www.openacc.org/resources last accessed.
  18. Raspberry Foundation, Raspberry pi, (04, 2020), https://www.raspberrypi.org/products/, last accessed.
  19. Orange pi, (04, 2020), http://www.orangepi.org/ last accessed.
  20. Asus, Asus Tinker Board, (04,2020), https://tinker-board.asus.com/product/tinker-board.html last accessed.
  21. Hardkernel, Odroid, (04,2020), https://wiki.odroid.com/, last accessed.
  22. Nvidia Developer, Sistemas Integrados Avanzados para la Computación en el Edge, (04, 2020), https://www.nvidia.com/es-la/autonomous-machines/embedded-systems/, last accessed.
  23. Nvidia Developer, Jetson TK1, (04,2020), https://developer.nvidia.com/embedded/jetson-tk1-developer-kit, last accessed.
  24. Nvidia Developer, Jetson TX2, (04, 2020), https://www.nvidia.com/es-la/autonomous-machines/embedded-systems/jetson-tx2/, last accessed.
  25. Nvidia Developer, Jetson Xavier NX, (04, 2020), https://www.nvidia.com/es-la/autonomous-machines/embedded-systems/jetson-xavier-nx/, last accessed.