My pal Joe at Scalable Informatics (during the day, and scalability.org during the late nights he keeps) sent me an email with news of an NVIDIA CUDA extension of MPI-HMMER, a scalable platform for “protein homology analysis”
Scalable Informatics (www.scalableinformatics.com), provider of high performance computing and storage solutions, in cooperation with researchers at the University at Buffalo, announced the introduction of GPU-HMMER, an NVIDIA CUDA implementation and extension of MPI-HMMER. GPU-HMMER and MPI-HMMER are open-source implementations of the HMMER protein sequence analysis suite that profoundly reduce computation times.
The MPI-HMMER implementation capitalizes on the computational power of multiple processors on large clusters, whereas GPU-HMMER is designed to leverage NVIDIA GPUs (graphics processing units) to accelerate processing on computing systems.
SI has tied their efforts on the software with preconfigured hardware offerings in storage and compute
In support of this software, Scalable Informatics offers NVIDIA Tesla-based Pegasus many-core workstations and JackRabbit servers pre-configured to run mpiHMMER, allowing end users to leverage the hardware’s high-end performance.
“The phenomenal speedups achieved by GPU-HMMER represents a fundamental shift in productivity for bio-informatics researchers,” said Sumit Gupta, Sr. Product Manager, Tesla GPU Computing at NVIDIA. “We are excited about the acceleration in the pace of research this will enable. Compute-intensive applications such as HMMER are perfectly suited to the NVIDIA Tesla GPU’s massively parallel, many-core CUDA architecture. GPU-HMMER is an excellent example of how to leverage the GPU to get supercomputer-class performance at the desktop.”
You can download MPI-HMMER and GPU-HMMER from http://mpihmmer.org. Support, as well as hardware, are available from Scalable Informatics.