Project News - GPUGrid

[kashi]

Thanks for the info. Downloaded a task and am crunching away. 

Hadn't been back for a fair while. As you said, got discouraged by the too frequent shortages of work.

[Dingo]

There is a New Test version ACEMD v2.10 (cuda100) that will run on the new Nvidia Turing type cards like GTX 1660Ti and all the RTX cards.  Until now GPUGRID did not support thse new cards.

I have two tasks running on my GTX 1660Ti's and they are almost finished so I think thy will run OK, will see in the morning.   I have run a few on my 1080Ti as well to make sure they work on the older GPUs as well.

I was still awake when the tasks completed and were valdated with credit.

https://www.gpugrid.net/show_host_detail.php?hostid=517492

As a side note the GTX1080Ti out performs the 1660Ti by almost 5000 seconds 1.38 hours per tasks.

https://www.gpugrid.net/show_host_detail.php?hostid=453402

[JugNut]

Yea that's great I was starting to think they might never support Turing cards.  It's definitely one of the best GPU projects out there.   

[Daniel]

Looks like Folding@home isn't the only project getting more support recently, yesterday the admin at GPUGrid posted ...

If I am not missing anything, GPUGRID volunteers doubled the number of active hosts in the last month. It may have been either due to the closing of seti@home, or a consequence of folding at home's covid effort.

Maybe people leaving seti@home, or maybe the Coronavirus outbreak has got people thinking more about biomedical research.
Maybe also because they have enough work at the moment - there were times in the past when I would have liked to do some GPUGrid, but had trouble getting tasks.

[tazzduke]

Well I might go back to GPUGRID, at least you can get work there.

Just wait till the end of March when the new work stops at Seti.

Cheers

[Dingo]

[GPUGrid.net] PYSCFbeta: Quantum chemistry calculations on GPU
Hello GPUGRID! We are deploying a new app "PYSCFbeta: Quantum chemistry calculations on GPU". It is currently in testing/beta stage. It is only on Linux at the moment. The app performs quantum chemistry calculations. At the moment we are using it specifically for Density Functional Theory calculations: http://en.wikipedia.org/wiki/Density_functional_theory These types of calculations allow us to accurately compute specific properties of small molecules. The current test work units have a runtime of the order 1hr (very much dependent on the GPU speed and size of molecule). Each work unit currently contains 1 molecule with ~10 configurations. The app will not work on GPUs with compute capability less than 6.0. It should not be sending them to these cards but I think at the moment this functionality is not working properly. The work-units require a lot of GPU memory. It works best if the work-unit is the only thing running on the GPU. If other programs are using significant GPU memory the work-unit might fail. Looking forward to hearing feedback from you. Steve

View article · Fri, 12 Jan 2024 13:03:21 +0000

[Dingo]

[GPUGrid.net] Discord channel for GPUGRID
Hi, I have created a discord channel for GPUGRID. It kind of duplicates this in some aspects but maybe people are more used to Discord. It is an additional channel that may help to build up the community. JOIN: https://discord.gg/abpWXawZ7v GDF

View article · Tue, 13 Feb 2024 11:29:01 +0000

[Dingo]

[GPUGrid.net] In-silico Binding Assay (ISBA/ACEMD3)
This is a message Adrià posted in our discord channel. Since he doesn't have an account in the GPUGRID forum I open the thread for him. If you want to be more up to date to the news related to this project and others please join our discord, we are usually more active there: https://discord.gg/dCMkcafPpX

Hello GPUGRID! Here Adrià. I'll be recovering the ACEMD3 application again, and sending new jobs of standard MD simulations (We've been testing it these past weeks to make sure it worked well for both Windows and Linux) The main goal of these new batch of simulations will be to validate further our capacity to predict the binding mode of ligands using simulations and adaptive sampling methods. Those of you that have been around for some time here might already be familiar with these simulations, such as the Benzamidin-Trypsin system (https://www.pnas.org/doi/abs/10.1073/pnas.1103547108) or the Dopamine D3 receptor with an antagonist ligand (https://www.nature.com/articles/s41598-018-19345-7#Ack1), which we were able to simulate thanks to GPUGRID and all your effort! Now, we are revisiting this method, which we call in-silico binding assay (ISBA). During drug discovery campaings, it's common that you know of ligands that bind to your target, but you don't know their binding mode, the exact conformation and structure that both the ligand and the protein have when bound. Knowing the binding mode is critical for further development of the molecule into a potent and usable drug. The most precise way of discovering the binding mode is with crystallization. However, that can take too much time or be directly impossible, depending on the protein. Therefore, we want to optimize and refine ISBA for binding mode prediction, so it can be usable during drug discovery projects. To summarize a bit our objectives, we want to predict binding modes for larger molecules than Benzamidin, with the same precision, but with less simulation time that was needed for the D3 receptor system. To do so, we'll be using the latest version of adaptive sampling that we developed, AdaptiveBandit (https://pubs.acs.org/doi/abs/10.1021/acs.jctc.0c00205). The objective of these new simulations I'll be sending will be to benchmark AdaptiveBandit in an ISBA scenario, improve the algorithm if required and fine-tune its hyperparameters. Let me know if there's any issue with the simulations. I'll be sending 100ns trajectories for the most part, divided in two steps.
View article · Thu, 2 May 2024 09:28:34 +0000