Researchers Turn Big Data Problems into Advanced Biology and Drug Discoveries
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SGI announced that researchers in the compute-intensive field of biotechnology research are continuing to make breakthrough progress with their selection of the SGI(R) UV(TM) high performance computing (HPC) system. SGI UV is the leading scalable shared memory architecture in the industry today, and is being deployed to tackle many of the world's most difficult and complex compute challenges. The Center for Pharmaceutical Biotechnology, University of Illinois at Chicago (UIC) and The Genome Analysis Centre (TGAC) in the UK are two examples.
Researchers at the Center for Pharmaceutical Biotechnology at UIC are working on the development of new therapeutics focused on the treatment of infectious diseases, critical with the advent of new resistant bacterial strains and ineffective treatments for many diseases. The discovery of novel chemical compounds that form the basis for the development of molecular scaffolds of new antimicrobials is a daunting task. One promising approach is the use of diverse chemical compound libraries--thousands of chemical compounds--that are tested against unique targets to find effective inhibitors of bacterial growth. The approach is promising, but can be extremely time-consuming, expensive and resource-intensive.
A parallel approach is the virtual screening of chemical compounds against these unique targets since their three-dimensional structures have been determined. After a virtual library of molecules is screened, they are ranked. Literally millions of molecules can be screened in this fashion, and used to generate a smaller library of molecules for testing. This virtual--or in silico--screening requires the use of hundreds of processors working in parallel to screen millions of compounds in a timely manner.
"Researchers at the Center have been using SGI IRIX(R) OS-based clusters for the past decade, and have now migrated to an SGI UV high performance compute solution powered by large arrays of Intel(R) Xeon(R) series processors and NVIDIA(R) Tesla(R) series GPUs," said Michael E. Johnson, professor and director emeritus at the Center for Pharmaceutical Biotechnology at UIC. "These clusters provide computing flexibility in managing both serial and parallel calculations, and the forward compatibility of SGI systems have allowed us to seamlessly evolve and expand our computing power through the years and keep up with the increasing complexity of the problems we need to address."
In the UK, TGAC specializes in genomics and bioinformatics with a focus on the analysis and interpretation of plant, animal and microbial genomes. Launched in July 2009, TGAC has steadily grown its team to over 50 members, with half of the institute working in a bioinformatics capacity to interpret, assemble and analyze datasets generated from the sequencers housed in their lab. Located on the Norwich Research Park in Norwich, UK, TGAC receives strategic funding from the UK's Biotechnology and Biological Sciences Research Council (BBSRC).
"SGI UV was chosen because of the product's superior performance and scalability, reflecting the company's support and experience in high-end, high performance computing," said Paul Fretter, science computing team leader at the Norwich Bioscience Institutes. "The main benefit of using such a system is the ability to assemble and analyze large and complex multi-billion base genome sequences in memory."
TGAC researchers have been using an SGI UV 100 since early 2011. SGI Professional Services was involved in helping the centre drive the implementation of fusion_IO SSD and the integration of NVIDIA Tesla GPUs. At the time of installation, this was the world's largest Red Hat(R) Enterprise Linux(R) 6 system. The centre is also due to receive the world's largest shared memory system for genome research when it initiates service of the future generation SGI UV system powered by Intel(R) MIC series processors.
"The SGI UV family is quickly becoming the de facto industry standard for customers tackling some of the world's most complex big data challenges in the field of life sciences," said Rick Rinehart, senior vice president of services at SGI. "The versatility, flexibility and scalability of the UV system make it the proper foundation for a complete compute and storage solution for these massive data intensive challenges."
