PROJECT #17619 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: 0x22
Status: Public
PROJECT FOLDING PPD AVERAGES BY GPU
PPDDB data as of Tuesday, 07 February 2023 06:14:52
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 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 6,851,308 | 1,910,059 | 3.59 | 7 hrs 41 mins |
2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 5,833,444 | 1,746,460 | 3.34 | 7 hrs 11 mins |
3 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,449,871 | 1,478,213 | 2.33 | 10 hrs 17 mins |
4 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,428,539 | 1,473,704 | 2.33 | 10 hrs 19 mins |
5 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,314,241 | 1,292,508 | 1.79 | 13 hrs 24 mins |
6 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 1,690,831 | 1,280,276 | 1.32 | 18 hrs 10 mins |
7 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 1,400,442 | 1,633,012 | 0.86 | 28 hrs 59 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
PPDDB data as of Tuesday, 07 February 2023 06:14:52
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
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