DGX-A100 Face to Face DGX-2—Performance, Power and Thermal Behavior Evaluation

Matej Špeťko, Ondřej Vysocký, Branislav Jansík and Lubomír Říha
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Matej Špeťko: IT4Innovations National Supercomputing Center, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic
Ondřej Vysocký: IT4Innovations National Supercomputing Center, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic
Branislav Jansík: IT4Innovations National Supercomputing Center, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic
Lubomír Říha: IT4Innovations National Supercomputing Center, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech Republic

Energies, 2021, vol. 14, issue 2, 1-18

Abstract: Nvidia is a leading producer of GPUs for high-performance computing and artificial intelligence, bringing top performance and energy-efficiency. We present performance, power consumption, and thermal behavior analysis of the new Nvidia DGX-A100 server equipped with eight A100 Ampere microarchitecture GPUs. The results are compared against the previous generation of the server, Nvidia DGX-2, based on Tesla V100 GPUs. We developed a synthetic benchmark to measure the raw performance of floating-point computing units including Tensor Cores. Furthermore, thermal stability was investigated. In addition, Dynamic Frequency and Voltage Scaling (DVFS) analysis was performed to determine the best energy-efficient configuration of the GPUs executing workloads of various arithmetical intensities. Under the energy-optimal configuration the A100 GPU reaches efficiency of 51 GFLOPS/W for double-precision workload and 91 GFLOPS/W for tensor core double precision workload, which makes the A100 the most energy-efficient server accelerator for scientific simulations in the market.

Keywords: DGX-A100; DGX-2; tensor cores; performance analysis; energy efficient computing; DVFS; power-aware computing; high performance computing (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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