[gmx-users] Hyperthreading throughput increase

[mernst at tricity.wsu.edu]

>From my browsing of list archives I can only recall seeing advice that hyperthreading
cannot offer more Gromacs performance. For all I know this remains true if you're trying
to use MPI to accelerate single calculations on hyperthreaded processors. However, I
have discovered that it may be possible to increase throughput by running two
independent jobs on a recent hyperthreaded processor, and I don't recall seeing this
mentioned on the list before.

My typical job involves ~790 DNA atoms, a few Na+ ions, and 13000-14000 water molecules.
I use Gromacs with the Amber force field ported by the Pande group. My simulation
machines are 3.2 Ghz Pentium machines with 2 MB of cache (Pentium 640, I think) and 1 GB
RAM.

Typical performance for one of these systems running on an unloaded machine is 64.3
hours/ns, 1.4 gflop/s. I accidentally started some pairs of simulations on some of these
machines this week and discovered that the performance of each job was *not* cut in
half. With two systems running simultaneously, each shows performance of about 98.8
hours/ns, 908 mflop/s. Running two of these jobs on each machine thus appears to
increase throughput by about 30%.

If like me you run many independent calculations, throughput is more important than
turnaround, and you have hyperthreaded machines but have not previously tried to take
advantage of them, it may be worth testing. I suppose this issue may have been covered
on the mailing list before, but all I ever remember seeing were advisements that
hyperthreaded processors won't help performance, or even advice to disable
hyperthreading in the BIOS. A brief web search indicates that some folding at home
participants have discovered comparable throughput advantages to running two client
instances on hyperthreaded processors.

Matt Ernst
Washington State University