PROJECT #17623 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

The previous FEC work unit test was completed successfully so now we're running larger "full size" WUs that are more scientifically useful for studying protein mutations with Free Energy Calculations.

As before, the approach and technology are similar to the Moonshot, but these set of projects instead are studying protein mutations and are much larger (since proteins are also much larger) In this case we are trying out multiple mutations and their impact upon a protein-protein of a dimerization complex (RIPK2), the most complex case.

PROJECT INFO

Manager(s): Sukrit Singh

Institution: Memorial Sloan-Kettering Cancer-Center

Project URL: http://sukritsingh.github.io/

PROJECT WORK UNIT SUMMARY

Atoms: 329,840

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Sunday, 02 October 2022 12:16:32

Rank
Project
Model Name
Folding@Home Identifier
Make
Brand
GPU
Model
PPD
Average
Points WU
Average
WUs Day
Average
WU Time
Average
1 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 5,902,970 1,924,277 3.07 8 hrs 49 mins
2 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 1,774,505 1,316,222 1.35 18 hrs 48 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Sunday, 02 October 2022 12:16:32

Rank
Project
CPU Model Logical
Processors (LP)
PPD-PLP
AVG PPD per 1 LP
ALL LP-PPD
(Estimated)
Make