Skip to content

Latest commit

 

History

History
74 lines (53 loc) · 4.11 KB

README.md

File metadata and controls

74 lines (53 loc) · 4.11 KB
Raw

Sampa-Benchmarks

Which machine should I use? Well, it depends on what you are running. Here we collect results from specific structures to determine the best way to use our computational resources. The structures are:

  1. Calcite + water, 337 atoms, self-consistent calculation (qe, pw)
  2. Gold surface, 112 atoms, self-consistent calculation (qe, pw)
  3. CO2 liquid-phase, 81 atoms, ab-initio molecular dynamics (VASP, IBRION=0, MDALGO=2)

Results

How many seconds/minutes/hours are needed to solve these calculations? Please include basic analysis of the data and a suggestion in case someone is running something similar.

1_calcite337

Benchmark input files and results by Prof. James Moraes de Almeida (Jul 2020).

Machine Cores/Boards PWSCF (CPU, s) Cost Efficiency
Tesla V100 SXM2 32GB GPU 008 165 65.91 %
--- 004 255 76.35 %
AMD Epyc 7532 (cpu) 128 348 100.00 %
--- 064 623 111.71 %
nanopetro-intel (cpu) 028 1799 38.69 %
nanopetro-amd (cpu) 064 3137 19.86 %

Observations

  • It was considered a price ratio (GPU/CPU) = 3.2 to estimate the cost efficiency;
  • GPU/CPU price ratio has to go down to lower than 2.5 to favor GPUs over CPUs
  • CPUs still present an advantage over GPUs considering price;
  • For DFT, the best strategy is still scaling down CPU cores until max. performance;
  • nanopetro nodes included as a reference.

2_ausurf112

This SCF calculation test was forked from here. Calculations were performed in May 2020 by @camilofs.

Machine Cores PWSCF (CPU, h) Efficiency
nanopetro-intel (cpu) 28 0.14244 100.00 %
--- 14 0.27366 104.11 %
--- 12 0.29512 112.62 %
--- 08 0.37400 133.00 %
nanopetro-amd (cpu) 64 0.36804 100.00 %
--- 32 0.65282 112.75 %
--- 16 1.26667 116.75 %
--- 08 2.01667 146.00 %

Observations

  • CPU time only; running quantum-espresso 6.4.0 & openmpi-3.1.4, Jul 2020. Efficiency estimated based on a full node allocation;
  • nanopetro-amd --> AMD Opteron 6376;
  • nanopetro-intel --> Intel Xeon Gold 5120;
  • Best options are highlighted. In nanopetro-intel, use a combination of 12+8+8 cores (three jobs).

3_co2aimd_vasp

Benchmark from the leda/dia project (RCGI1, 2021). It comprises 10.000 ab-initio molecular dynamics steps using VASP. The system has 81 atoms (27 CO_2 molecules). Integration step (POTIM) is 1 fs. Please, refer to the folder to acess all the input files. Calculations were performed in Feb 2021 by @camilofs.

Machine Cores Time for 10k steps (min) Efficiency
nanopetro-intel (cpu) 28 19040 100.00 %
--- 14 24110 157.94 %
nanopetro-amd (cpu) 64 7488 100.00 %
--- 32 9060 165.29 %

Observations

  • CPU time only; running VASP 5.4.4 with a gcc 9.2.0 compilation, 2020. Efficiency estimated based on a full node allocation;
  • nanopetro-amd --> AMD Opteron 6376;
  • nanopetro-intel --> Intel Xeon Gold 5120;
  • The best option is highlighted; nanopetro-amd cores perform way better in AIMD. They are the only ones that run each MD step in less than 1 min.