"The computer models needed to accurately simulate surfactant properties are extremely demanding in terms of computational power," said Axel Kohlmeyer of the Institute for Computational Molecular Science at Temple University. "We discovered that by adding just two NVIDIA Tesla C1060 GPUs, each node in our newest cluster can do 16 times more work, and thus multiplies our local compute capacity far beyond what we could previously get through the national supercomputing centers."
"To put this into context, we can run a single GPU-optimized molecular dynamics simulation on two Tesla GPUs as fast as we can on 128 CPU cores of a Cray XT3 supercomputer or on 1024 CPUs of an IBM BlueGene/L machine with conventional software," continues Dr.Kohlmeyer. "With the NVIDIA Tesla GPU-based solution, we now have a more powerful, cost-effective solution that will enable us to advance critical research at a much faster pace. We?re moving rapidly ahead to deploy a larger Tesla GPU cluster at Temple, which will give another huge boost to our work."
The Temple researchers are using GPU-accelerated HOOMD (Highly Optimized Object Oriented Molecular Dynamics) simulation software, written by researchers at the Department of Energy?s Ames Laboratory to leverage the NVIDIA GPUs.
In addition to deploying a small local GPU cluster, the university team will also look to scale its work using the NCSA Lincoln cluster, where the computational output has been boosted to 47 TeraFLOPS through the addition of Tesla S1070 1U GPU systems.