PROJECT #17625 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 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	6,417,591	1,885,417	3.40	7 ^hrs 3 ^mins
2	GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate]	Nvidia	GA102	5,764,025	1,777,984	3.24	7 ^hrs 24 ^mins
3	GeForce RTX 2080 Ti TU102 [GeForce RTX 2080 Ti] M 13448	Nvidia	TU102	4,060,326	1,558,019	2.61	9 ^hrs 13 ^mins
4	GeForce RTX 3070 Mobile / Max-Q GA104M [GeForce RTX 3070 Mobile / Max-Q]	Nvidia	GA104M	2,851,939	1,384,040	2.06	12 ^hrs 39 ^mins
5	GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate]	Nvidia	GA104	2,794,274	1,401,262	1.99	12 ^hrs 2 ^mins
6	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	2,113,209	1,234,408	1.71	14 ^hrs 1 ^mins
7	GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632	Nvidia	GM200	1,481,904	1,114,885	1.33	18 ^hrs 3 ^mins
8	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	460,156	756,808	0.61	39 ^hrs 28 ^mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA