PROJECT #17777 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 Urbana-Champaign
PROJECT WORK UNIT SUMMARY
Atoms: 116,699
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 | 7,505,210 | 208,040 | 36.08 | 1 hrs 40 mins |
| 2 | GeForce RTX 3080 Ti GA102 [GeForce RTX 3080 Ti] |
Nvidia | GA102 | 6,933,639 | 204,363 | 33.93 | 1 hrs 42 mins |
| 3 | GeForce RTX 3080 Lite Hash Rate GA102 [GeForce RTX 3080 Lite Hash Rate] |
Nvidia | GA102 | 6,073,688 | 192,601 | 31.54 | 1 hrs 46 mins |
| 4 | GeForce RTX 3070 Ti GA104 [GeForce RTX 3070 Ti] |
Nvidia | GA104 | 4,484,908 | 175,614 | 25.54 | 1 hrs 56 mins |
| 5 | GeForce RTX 2080 Ti Rev. A TU102 [GeForce RTX 2080 Ti Rev. A] M 13448 |
Nvidia | TU102 | 4,476,277 | 174,856 | 25.60 | 1 hrs 56 mins |
| 6 | GeForce RTX 3070 GA104 [GeForce RTX 3070] |
Nvidia | GA104 | 4,448,641 | 175,062 | 25.41 | 1 hrs 57 mins |
| 7 | RTX A5000 GA102GL [RTX A5000] |
Nvidia | GA102GL | 4,376,018 | 174,136 | 25.13 | 1 hrs 57 mins |
| 8 | GeForce RTX 2070 SUPER TU104 [GeForce RTX 2070 SUPER] 8218 |
Nvidia | TU104 | 3,248,914 | 157,933 | 20.57 | 1 hrs 10 mins |
| 9 | GeForce RTX 2070 Rev. A TU106 [GeForce RTX 2070 Rev. A] |
Nvidia | TU106 | 2,492,125 | 144,220 | 17.28 | 1 hrs 23 mins |
| 10 | GeForce GTX 1080 Ti GP102 [GeForce GTX 1080 Ti] 11380 |
Nvidia | GP102 | 2,492,044 | 144,215 | 17.28 | 1 hrs 23 mins |
| 11 | Radeon RX 6800/6800 XT / 6900 XT Navi 21 [Radeon RX 6800/6800 XT / 6900 XT] |
AMD | Navi 21 | 1,637,854 | 125,337 | 13.07 | 2 hrs 50 mins |
| 12 | GeForce GTX 1080 GP104 [GeForce GTX 1080] 8873 |
Nvidia | GP104 | 1,211,971 | 113,900 | 10.64 | 2 hrs 15 mins |
| 13 | GeForce GTX 1660 SUPER TU116 [GeForce GTX 1660 SUPER] |
Nvidia | TU116 | 751,331 | 96,693 | 7.77 | 3 hrs 5 mins |
| 14 | GeForce GTX 980 GM204 [GeForce GTX 980] 4612 |
Nvidia | GM204 | 659,674 | 92,604 | 7.12 | 3 hrs 22 mins |
| 15 | GeForce RTX 3080 Mobile / Max-Q 8GB/16GB GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB] |
Nvidia | GA104M | 644,820 | 92,248 | 6.99 | 3 hrs 26 mins |
| 16 | GeForce GTX 1060 3GB GP106 [GeForce GTX 1060 3GB] 3935 |
Nvidia | GP106 | 458,499 | 82,428 | 5.56 | 4 hrs 19 mins |
| 17 | Radeon RX 6700/6700 XT / 6800M Navi 22 [Radeon RX 6700/6700 XT / 6800M] |
AMD | Navi 22 | 450,908 | 82,254 | 5.48 | 4 hrs 23 mins |
| 18 | Radeon RX 470/480/570/580/590 Ellesmere XT [Radeon RX 470/480/570/580/590] |
AMD | Ellesmere XT | 341,069 | 60,332 | 5.65 | 4 hrs 15 mins |
| 19 | GeForce GTX 980M GM204 [GeForce GTX 980M] 3189 |
Nvidia | GM204 | 332,760 | 74,170 | 4.49 | 5 hrs 21 mins |
| 20 | GeForce GTX 770 GK104 [GeForce GTX 770] 3213 |
Nvidia | GK104 | 116,700 | 52,342 | 2.23 | 11 hrs 46 mins |
| 21 | GeForce GTX 760 GK104 [GeForce GTX 760] 2258 |
Nvidia | GK104 | 60,396 | 41,798 | 1.44 | 17 hrs 37 mins |
| 22 | Radeon Vega Series / Radeon Vega Mobile Series Raven Ridge [Radeon Vega Series / Radeon Vega Mobile Series] |
AMD | Raven Ridge | 53,087 | 40,121 | 1.32 | 18 hrs 8 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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