PROJECT #17769 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE
PROJECT SUMMARY
Projects 17745-17750 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: 90,887
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 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 8,054,859 | 159,086 | 50.63 | 0 hrs 28 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 7,117,804 | 152,835 | 46.57 | 1 hrs 31 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 7,020,882 | 154,394 | 45.47 | 1 hrs 32 mins |
| 4 | GeForce RTX 3080 GA102 [GeForce RTX 3080] |
Nvidia | GA102 | 5,916,695 | 143,809 | 41.14 | 1 hrs 35 mins |
| 5 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 5,418,946 | 139,472 | 38.85 | 1 hrs 37 mins |
| 6 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 4,557,709 | 131,878 | 34.56 | 1 hrs 42 mins |
| 7 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,528,854 | 131,993 | 34.31 | 1 hrs 42 mins |
| 8 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 4,116,663 | 128,645 | 32.00 | 1 hrs 45 mins |
| 9 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 3,399,037 | 119,950 | 28.34 | 1 hrs 51 mins |
| 10 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 3,320,622 | 119,142 | 27.87 | 1 hrs 52 mins |
| 11 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,817,336 | 114,128 | 24.69 | 1 hrs 58 mins |
| 12 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,671,634 | 111,318 | 24.00 | 1 hrs 60 mins |
| 13 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,516,277 | 108,706 | 23.15 | 1 hrs 2 mins |
| 14 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,254,889 | 113,643 | 19.84 | 1 hrs 13 mins |
| 15 | GeForce RTX 2060 Super TU106 [GeForce RTX 2060 SUPER] |
Nvidia | TU106 | 2,209,073 | 104,178 | 21.20 | 1 hrs 8 mins |
| 16 | GeForce RTX 3060 Lite Hash Rate GA106 [GeForce RTX 3060 Lite Hash Rate] |
Nvidia | GA106 | 2,044,604 | 100,954 | 20.25 | 1 hrs 11 mins |
| 17 | GeForce RTX 2070 TU106 [GeForce RTX 2070] |
Nvidia | TU106 | 1,842,315 | 97,969 | 18.81 | 1 hrs 17 mins |
| 18 | GeForce GTX 980 Ti GM200 [GeForce GTX 980 Ti] 5632 |
Nvidia | GM200 | 1,294,769 | 86,917 | 14.90 | 2 hrs 37 mins |
| 19 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 1,269,950 | 84,264 | 15.07 | 2 hrs 36 mins |
| 20 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,239,968 | 85,623 | 14.48 | 2 hrs 39 mins |
| 21 | Tesla M40 GM200GL [Tesla M40] 6844 |
Nvidia | GM200GL | 1,203,203 | 85,406 | 14.09 | 2 hrs 42 mins |
| 22 | GeForce GTX 1070 GP104 [GeForce GTX 1070] 6463 |
Nvidia | GP104 | 1,177,646 | 84,487 | 13.94 | 2 hrs 43 mins |
| 23 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 550,579 | 65,406 | 8.42 | 3 hrs 51 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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