PROJECT #17603 RESEARCH FOR CANCER
FOLDING PERFORMANCE PROFILE
PROJECT SUMMARY
This project is an attempt at implementing adaptive sampling in Folding@home.
Adaptive sampling is a way of enhancing sampling of protein conformational space by selectively launching simulations from the most "valuable" work units. 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 process, wasting work units on regions of state space that are irrelevant or uninteresting to the question at hand.
Adaptive Sampling is a way to tackle this inefficiency.
Using iterative rounds, where we collect the work units so far and select the "best/most valuable" conformational state worth exploring.
New simulations and work units are launched from these most valuable work units, hopefully more efficiently exploring state space.
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: Beta
PROJECT FOLDING PPD AVERAGES BY GPU
PPDDB data as of Saturday, 01 April 2023 12:14:48
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 | 5,590,626 | 288,223 | 19.40 | 1 hrs 14 mins |
2 | GeForce RTX 3090 GA102 [GeForce RTX 3090] |
Nvidia | GA102 | 4,947,845 | 275,336 | 17.97 | 1 hrs 20 mins |
3 | GeForce RTX 3070 Lite Hash Rate GA104 [GeForce RTX 3070 Lite Hash Rate] |
Nvidia | GA104 | 3,331,531 | 241,653 | 13.79 | 2 hrs 44 mins |
4 | GeForce RTX 2080 Rev. A TU104 [GeForce RTX 2080 Rev. A] 10068 |
Nvidia | TU104 | 3,095,323 | 227,725 | 13.59 | 2 hrs 46 mins |
5 | GeForce RTX 3060 Ti Lite Hash Rate GA104 [GeForce RTX 3060 Ti Lite Hash Rate] |
Nvidia | GA104 | 2,719,187 | 225,335 | 12.07 | 2 hrs 59 mins |
6 | GeForce RTX 2060 TU104 [GeForce RTX 2060] |
Nvidia | TU104 | 2,013,689 | 204,814 | 9.83 | 2 hrs 26 mins |
PROJECT FOLDING PPD AVERAGES BY CPU BETA
PPDDB data as of Saturday, 01 April 2023 12:14:48
Rank Project |
CPU Model |
Logical Processors (LP) |
PPD-PLP AVG PPD per 1 LP |
ALL LP-PPD (Estimated) |
Make |
---|