Benchmarking RELION2 GPU-accelerated jobs on Comet-GPU nodes

Below you will find the results of running the standard RELION2 benchmark on a number of different node configurations to optimize speed vs. ‘cost’ (in service units, SUs).

Optimal configuration for COSMIC² users: 8 x K80 GPUs (which is across 2 nodes) is worth it – nearly double the speed, but only a fraction more SUs to pay for it.

Fastest analysis: 12 x P100 GPUs (which made it also the most ‘expensive’)

RELION benchmarking test set (link)

  • Job type: RELION 3D Classification – v2.1.b1; 25 iterations
  • Data info: 105,247 particles; 360 x 360 pixels
  • Elapsed time: 3 hr 14 min
  • Compute type: GPU (4 x P100)
  • SUs: 19.5

 

  • Job type: RELION 3D Classification – v2.1.b1; 25 iterations
  • Data info: 105,247 particles; 360 x 360 pixels
  • Elapsed time: 1 hr 43 min
  • Compute type: GPU (8 x P100)
  • SUs: 21

 

  • Job type: RELION 3D Classification – v2.1.b1; 25 iterations
  • Data info: 105,247 particles; 360 x 360 pixels
  • Elapsed time: 1 hr 25 min
  • Compute type: GPU (12 x P100)
  • SUs: 23

 

  • Job type: RELION 3D Classification – v2.1.b1; 25 iterations
  • Data info: 105,247 particles; 360 x 360 pixels
  • Elapsed time: 3 hr 42 min
  • Compute type: GPU (4 x K80)
  • SUs: 15

 

  • Job type: RELION 3D Classification – v2.1.b1; 25 iterations
  • Data info: 105,247 particles; 360 x 360 pixels
  • Elapsed time: 2 hr 2 min
  • Compute type: GPU (8 x K80)
  • SUs: 16

 

  • Job type: RELION 3D Classification – v2.1.b1; 25 iterations
  • Data info: 105,247 particles; 360 x 360 pixels
  • Elapsed time: 1 hr 42 min
  • Compute type: GPU (12 x K80)
  • SUs: 20.4

 

 

Posted in Uncategorized.

Leave a Reply

Your email address will not be published. Required fields are marked *