PROJECT #17785 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

Molecular basis of secondary active transporters. Secondary active membrane transporters are proteins that utilize ions to transport an assortment of molecules across cell membranes.

These proteins are found in all domains in life and surprisingly, despite vastly different structures, operate under the same mechanism by using an ion gradient to assist in small molecule transport.

Furthermore, many of these secondary active transporters are drug targets to treat diseases like cancer, diabetes, and neurological disorders.

The simulations in this project will allow us to understand a universal role of ion-coupling across different families of proteins.

PROJECT INFO

Manager(s): Matthew Chan

Institution: University of Illinois at Urbana-Champaign

PROJECT WORK UNIT SUMMARY

Atoms: 90,906

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Sunday, 22 May 2022 15:22:32

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	7,340,282	152,944	47.99	1 ^hrs 30 ^mins
2	GeForce RTX 3090 GA102 [GeForce RTX 3090]	Nvidia	GA102	6,988,898	149,883	46.63	1 ^hrs 31 ^mins
3	GeForce RTX 3080 GA102 [GeForce RTX 3080]	Nvidia	GA102	6,328,391	146,491	43.20	1 ^hrs 33 ^mins
4	GeForce RTX 3070 GA104 [GeForce RTX 3070]	Nvidia	GA104	4,611,667	133,439	34.56	1 ^hrs 42 ^mins
5	RTX A5000 GA102GL [RTX A5000]	Nvidia	GA102GL	4,330,692	130,322	33.23	1 ^hrs 43 ^mins
6	GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448	Nvidia	TU102	4,328,143	130,256	33.23	1 ^hrs 43 ^mins
7	GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti]	Nvidia	GA104	4,280,781	129,840	32.97	1 ^hrs 44 ^mins
8	GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate]	Nvidia	GA102	4,163,385	127,626	32.62	1 ^hrs 44 ^mins
9	GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068	Nvidia	TU104	3,713,648	124,648	29.79	1 ^hrs 48 ^mins
10	GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380	Nvidia	GP102	2,567,024	109,930	23.35	1 ^hrs 2 ^mins
11	GeForce RTX 2060 TU104 [GeForce RTX 2060]	Nvidia	TU104	2,003,544	101,439	19.75	1 ^hrs 13 ^mins
12	GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873	Nvidia	GP104	1,201,173	84,805	14.16	2 ^hrs 42 ^mins
13	GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER]	Nvidia	TU116	1,128,146	80,937	13.94	2 ^hrs 43 ^mins
14	Tesla M40 GM200GL [Tesla M40] 6844	Nvidia	GM200GL	1,004,227	80,485	12.48	2 ^hrs 55 ^mins
15	GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]	Nvidia	GA104M	770,439	73,301	10.51	2 ^hrs 17 ^mins
16	GeForce GTX 980 GM204 [GeForce GTX 980] 4612	Nvidia	GM204	555,923	65,730	8.46	3 ^hrs 50 ^mins
17	GeForce GTX 1050 Ti GP107 [GeForce GTX 1050 Ti] 2138	Nvidia	GP107	310,915	54,562	5.70	4 ^hrs 13 ^mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Sunday, 22 May 2022 15:22:32

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

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