The time-consuming scientific research behind drug discovery can be accelerated with the launch of Amber 11, a software tool that enables bio-scientists to achieve supercomputing on their desktop PC.
Amber 11 is optimised to run on Nvidia graphics processing units (GPUs), which speed up the tool by up to 100-fold over a traditional CPU-based server, the company said.
GPUs deliver performance from a desktop workstation that previously could only be achieved on a supercomputer, improving productivity.
Amber 11 is designed to take advantage of Nvidia Tesla 20-series GPUs, which utilise the massively parallel Cuda architecture for the specific needs of high-performance computing applications.
In early trials with the Amber user community, Dr Ross Walker, research professor at the San Diego Supercomputer Center, at the University of California, and a principle Amber contributor, received more than a dozen reports of speedups over 30-times on a range of bio-molecular simulations.
Walker noted that just one Tesla GPU provides as much processing power as a high-performance cluster of 512 CPU cores when simulating one nanosecond in the lifetime of a 25,000 atom implicit solvent nucleosome.
In a simpler explicit solvent simulation, such as the JAC benchmark, he noted that one Tesla GPU provides the equivalent processing power of 48 cores of the NSF Ranger supercomputer.
