PROJECT #17605 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE

PROJECT SUMMARY

This project is an attempt at implementing umbrella sampling in Folding@home.

Umbrella sampling is a way of "pulling" the protein to new configurations by attaching a spring to specific atoms to move into a certain configuration. Identifying druggable states or exploring conformational state space relevant to disease is an existing challenge.

The embarassingly parallel nature of Folding@home allows us to massively scale up our exploration.

However, the underlying methods still rely on luck to a large extent – we must discover the states in work units as the dataset grows in size and more work units are run.

This can be an incredibly inefficient and slow process.

To help speed up state discovery and exploration, we can place 'springs' at regularly spaced intervals in our configuration space, and pull any independent simulation to one of these springs.

This "spring pulled simulation" is called Umbrella sampling (because the shape of the space explored around the spring looks like an parabola/umbrella).

With FAH, we can run multiple umbrellas at once, pulling each individual RUN to a unique point in conformational space independently of other RUNs.

In doing so we are able to massively scale up our sampling and discovery of unique states in a protein's conformational landscape. This project is identical in calculation to 16497, exploring conformations of MET kinase, involved in non-small-cell lung carcinoma, but acting as a test bed..

PROJECT INFO

Manager(s): Sukrit Singh

Institution: Memorial Sloan-Kettering Cancer-Center

Project URL: http://sukritsingh.github.io/

PROJECT WORK UNIT SUMMARY

Atoms: 59,897

Core: OPENMM_22

Status: Public

PROJECT FOLDING PPD AVERAGES BY GPU

PPDDB data as of Sunday, 02 October 2022 12:16:33

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 Lite Hash Rate
GA102 [GeForce RTX 3080 Lite Hash Rate]
Nvidia GA102 4,840,581 413,517 11.71 2 hrs 3 mins
2 GeForce RTX 3090
GA102 [GeForce RTX 3090]
Nvidia GA102 4,711,914 415,699 11.33 2 hrs 7 mins
3 GeForce RTX 3080 Ti
GA102 [GeForce RTX 3080 Ti]
Nvidia GA102 4,621,147 414,497 11.15 2 hrs 9 mins
4 GeForce RTX 2080 Ti
TU102 [GeForce RTX 2080 Ti] M 13448
Nvidia TU102 4,496,540 414,494 10.85 2 hrs 13 mins
5 GeForce RTX 3090 Ti
GA102 [GeForce RTX 3090 Ti]
Nvidia GA102 4,288,021 409,144 10.48 2 hrs 17 mins
6 GeForce RTX 2080 Ti Rev. A
TU102 [GeForce RTX 2080 Ti Rev. A] M 13448
Nvidia TU102 4,005,680 398,534 10.05 2 hrs 23 mins
7 GeForce RTX 3080
GA102 [GeForce RTX 3080]
Nvidia GA102 3,954,788 394,934 10.01 2 hrs 24 mins
8 GeForce RTX 3070 Ti
GA104 [GeForce RTX 3070 Ti]
Nvidia GA104 3,809,872 388,713 9.80 2 hrs 27 mins
9 GeForce RTX 3080 12GB
GA102 [GeForce RTX 3080 12GB]
Nvidia GA102 3,624,362 347,957 10.42 2 hrs 18 mins
10 GeForce RTX 3070 Lite Hash Rate
GA104 [GeForce RTX 3070 Lite Hash Rate]
Nvidia GA104 3,367,570 374,633 8.99 3 hrs 40 mins
11 GeForce RTX 3070
GA104 [GeForce RTX 3070]
Nvidia GA104 3,231,115 370,061 8.73 3 hrs 45 mins
12 GeForce RTX 3080 Mobile / Max-Q 8GB/16GB
GA104M [GeForce RTX 3080 Mobile / Max-Q 8GB/16GB]
Nvidia GA104M 2,928,546 366,138 8.00 3 hrs 0 mins
13 TITAN X
GP102 [TITAN X] 6144
Nvidia GP102 2,884,464 357,650 8.07 3 hrs 59 mins
14 GeForce RTX 2080 Super
TU104 [GeForce RTX 2080 SUPER]
Nvidia TU104 2,699,394 350,779 7.70 3 hrs 7 mins
15 GeForce RTX 3060 Ti Lite Hash Rate
GA104 [GeForce RTX 3060 Ti Lite Hash Rate]
Nvidia GA104 2,469,351 335,900 7.35 3 hrs 16 mins
16 GeForce RTX 3060
GA104 [GeForce RTX 3060]
Nvidia GA104 2,112,148 321,725 6.57 4 hrs 39 mins
17 GeForce GTX 1080 Ti
GP102 [GeForce GTX 1080 Ti] 11380
Nvidia GP102 2,110,410 323,528 6.52 4 hrs 41 mins
18 GeForce RTX 2060 Super
TU106 [GeForce RTX 2060 SUPER]
Nvidia TU106 1,886,278 312,632 6.03 4 hrs 59 mins
19 GeForce RTX 2070 SUPER
TU104 [GeForce RTX 2070 SUPER] 8218
Nvidia TU104 1,758,482 306,531 5.74 4 hrs 11 mins
20 GeForce RTX 3060 Lite Hash Rate
GA106 [GeForce RTX 3060 Lite Hash Rate]
Nvidia GA106 1,637,251 287,562 5.69 4 hrs 13 mins
21 GeForce GTX 1080
GP104 [GeForce GTX 1080] 8873
Nvidia GP104 1,383,048 282,836 4.89 5 hrs 54 mins
22 GeForce RTX 3060 Ti
GA104 [GeForce RTX 3060 Ti]
Nvidia GA104 1,225,103 271,468 4.51 5 hrs 19 mins
23 GeForce GTX 1660 Ti
TU116 [GeForce GTX 1660 Ti]
Nvidia TU116 1,218,375 273,520 4.45 5 hrs 23 mins
24 GeForce RTX 3060 Mobile / Max-Q
GA106M [GeForce RTX 3060 Mobile / Max-Q]
Nvidia GA106M 1,210,195 262,320 4.61 5 hrs 12 mins
25 Quadro RTX 4000
TU104GL [Quadro RTX 4000]
Nvidia TU104GL 1,208,452 267,702 4.51 5 hrs 19 mins
26 GeForce GTX 1070 Ti
GP104 [GeForce GTX 1070 Ti] 8186
Nvidia GP104 1,159,426 258,908 4.48 5 hrs 22 mins
27 GeForce RTX 2060
TU106 [Geforce RTX 2060]
Nvidia TU106 1,132,996 273,551 4.14 6 hrs 48 mins
28 GeForce GTX 1070
GP104 [GeForce GTX 1070] 6463
Nvidia GP104 1,105,303 262,514 4.21 6 hrs 42 mins
29 GeForce GTX Titan X
GM200 [GeForce GTX Titan X] 6144
Nvidia GM200 1,054,832 270,388 3.90 6 hrs 9 mins
30 Geforce RTX 3050
GA106 [Geforce RTX 3050]
Nvidia GA106 998,989 254,403 3.93 6 hrs 7 mins
31 Tesla M40
GM200GL [Tesla M40] 6844
Nvidia GM200GL 926,011 246,093 3.76 6 hrs 23 mins
32 GeForce GTX 980
GM204 [GeForce GTX 980] 4612
Nvidia GM204 864,546 239,761 3.61 7 hrs 39 mins
33 GeForce GTX 1660 SUPER
TU116 [GeForce GTX 1660 SUPER]
Nvidia TU116 850,515 225,632 3.77 6 hrs 22 mins
34 GeForce GTX 1060 6GB
GP106 [GeForce GTX 1060 6GB] 4372
Nvidia GP106 757,289 232,603 3.26 7 hrs 22 mins
35 GeForce GTX 1650 SUPER
TU116 [GeForce GTX 1650 SUPER]
Nvidia TU116 703,639 234,681 3.00 8 hrs 0 mins
36 GeForce GTX 980 Ti
GM200 [GeForce GTX 980 Ti] 5632
Nvidia GM200 675,508 200,153 3.37 7 hrs 7 mins
37 GeForce GTX 1660
TU116 [GeForce GTX 1660]
Nvidia TU116 647,022 221,336 2.92 8 hrs 13 mins
38 GeForce GTX 1060 3GB
GP106 [GeForce GTX 1060 3GB] 3935
Nvidia GP106 628,567 215,245 2.92 8 hrs 13 mins
39 P106-100
GP106 [P106-100]
Nvidia GP106 603,107 230,869 2.61 9 hrs 11 mins
40 GeForce GTX 970
GM204 [GeForce GTX 970] 3494
Nvidia GM204 486,089 209,011 2.33 10 hrs 19 mins
41 GeForce GTX 1060 Mobile
GP106M [GeForce GTX 1060 Mobile]
Nvidia GP106M 419,577 164,335 2.55 9 hrs 24 mins
42 GeForce GTX 980M
GM204 [GeForce GTX 980M] 3189
Nvidia GM204 407,873 186,143 2.19 11 hrs 57 mins
43 P106-090
GP106 [P106-090]
Nvidia GP106 353,151 177,911 1.98 12 hrs 5 mins
44 GeForce GTX 960
GM206 [GeForce GTX 960] 2308
Nvidia GM206 345,996 175,657 1.97 12 hrs 11 mins
45 GeForce GTX 1050 Ti
GP107 [GeForce GTX 1050 Ti] 2138
Nvidia GP107 343,856 176,485 1.95 12 hrs 19 mins
46 Quadro M4000
GM204GL [Quadro M4000]
Nvidia GM204GL 321,276 172,401 1.86 13 hrs 53 mins
47 GeForce GTX 750 Ti
GM107 [GeForce GTX 750 Ti] 1389
Nvidia GM107 184,184 143,498 1.28 19 hrs 42 mins
48 Quadro P1000
GP107GL [Quadro P1000]
Nvidia GP107GL 165,312 136,484 1.21 20 hrs 49 mins
49 Quadro M2000
GM206GL [Quadro M2000]
Nvidia GM206GL 153,011 144,199 1.06 23 hrs 37 mins
50 GeForce GT 1030
GP108 [GeForce GT 1030]
Nvidia GP108 139,310 130,551 1.07 22 hrs 29 mins
51 Quadro P620
GP107GL [Quadro P620]
Nvidia GP107GL 122,625 117,268 1.05 23 hrs 57 mins
52 Quadro K2200
GM107GL [Quadro K2200]
Nvidia GM107GL 96,985 115,899 0.84 29 hrs 41 mins
53 Quadro K1200
GM107GL [Quadro K1200]
Nvidia GM107GL 74,534 105,585 0.71 34 hrs 60 mins
54 Quadro K620
GM107GL [Quadro K620]
Nvidia GM107GL 74,448 99,883 0.75 32 hrs 12 mins

PROJECT FOLDING PPD AVERAGES BY CPU BETA

PPDDB data as of Sunday, 02 October 2022 12:16:33

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