We believe in the power of science and a knowledge-based approach to life in general. So we’re proud to be a part of several community grid computing projects which work to solve open problems in medicine, environmental science, and mathematics.
Our work We’re currently active in World Community Grid, Rosetta@Home, Einstein@Home, GPUGrid, and Asteroids@Home. You can check out our detailed stats across all projects.
WCG brief stats Updated every 5 years of CPU time.
2020-03-21: Covid19 As grid computing efforts toward combatting Covid19 have come to the forefront, we have devoted more of our CPU time to Rosetta@Home.
We’ve also dialed back the GPU work we were doing for Einstein@Home and Asteroids@Home; we are now only crunching WUs for them when there are no WUs available from GPUGrid.
This means that our current blend of compute resources is 50/50 Rosetta and WCG on the CPU side of things, and 100% GPUGrid (again, unless they do not have work available) on the GPU side.
2019-11-03: 75 years; last update of the year Today we crossed 75 years of compute time for WCG.
Two other events happened earlier this week: the Africa Rainfall Project kicked off, and we finished our 3900X upgrade. We’re excited about both, especially since finishing the upgrades let us build two more nodes out of spare parts. We now have 128 threads in-house.
Here’s to next year!
2019-08-16: Top 1000; New hardware; Visiting friends Thanks to a visit from user Sheridon of Xstreme Systems Team, we broke into the top 1000 teams a few days earlier than expected.
The Firepear computing stack is currently all Ryzen. It’s simple cost-benefit analysis: I’m interested in crunching as much data as possible per unit time, at a reasonable cost (in both money and electricity). Right now, that’s Ryzen.
I’m upgrading all my machines to the new R9 3900X CPU. This provides an opportunity to compare all three generations of the Ryzen family.
3900X vs 3950X I want to throw as many cores as I can at the problems that I volunteer compute time for, but I also have a finite budget.
After months of pondering what GPU to use to get my compute farm back into crunching GPGPU workunits, I was persuaded by a recent review to order a GTX 1650 and give it a go.
Background and lead-up Years ago, I was reading stories about how Linux support on Steam had really improved. I decided to build a Linux box capable of running modern-ish games. This was in 2015, a time when AMD GPU support on Linux was abominable, so my choice for a video card boiled down to “which Nvidia card?
This is the development diary for Greenhouse, my attempt to build a DIY compute farm in a box. In other words, a multi-machine chassis.
2018-11-01 — Introduction and Plan The core idea is to assemble individual compute nodes on trays, in the most compact way feasible, and then to stack nodes atop each other in an enclosure.
The components of each node will be:
A tray made from some thin, rigid, wood-based board.
News and Updates 2018-12-24 After a week offline due to work on Homefarm, all our nodes are back up and crunching to close out the calendar year, and our first year as a team.
2018-12-12 So many milestones here at the end of the calendar year! Today we returned our 100,000th work unit for World Community Grid.
2018-12-03 We are now in the top 2000 teams on WGC, by both points and WUs returned – and we’re still not quite a year old!