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