Convey and Nimbix to give away $25,000 of processing time on hybrid-core cluster, allowing qualified applicants to try accelerated genomics workflows for free.

Convey Computer today announced that Nimbix, a leader in accelerated high-performance cloud computing, has partnered with Convey to expand its Convey hybrid-core (HC) infrastructure, as part of “The Accelerated Genomics Cloud” (TAGC) promotion, which provides free runtime for qualified applicants. The Convey HC-2ex platform will be used in research projects for customers who take advantage of the promotion.

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A total of $25,000 worth of cloud processing time will be awarded to genomics researchers to boost their bioinformatics analysis. Top award recipients will receive $1,000 of runtime each, which is enough to map up to 3 Tbases of reads, providing the ability to analyze, for example, a dozen human genomes at significant coverage. Remaining qualified applicants will receive $500 of runtime.

TAGC promotion will begin April 30, and the first awards will be granted as soon as the application review process allows. The promotion will end July 1 or once all funding has been awarded. Therefore, interested participants are encouraged to apply quickly by registering at http://www.nimbix.net/tagcpromo/.

The Convey HC-2ex platform will be used in research projects for Nimbix customers who take advantage of the promotion. Image courtesy of Convey Computer

For those applicants selected, runtime will include a pool of Nimbix resources, which includes a mix of Convey and standard large memory systems configured to provide the best performance across a range of applications and workflows. These may include reference mapping, de novo assembly, functional annotation, variant analysis and RNA expression profiling. For example, participants will have access to the full Convey Bioinformatics Suite, as well as third-party applications optimized for the hybrid-core architecture.

“Genomics is perhaps the clearest example where progress is accelerated by access to the right HPC resource and stymied when those resources are missing,” stated Dr. George Vacek, Director of Convey Computer’s Life Sciences business unit. “Heterogeneous computing has become a necessity in life sciences, where the data production from next-generation sequencing instruments is increasing much more quickly than traditional computing resources can handle.”

The combination of heterogeneous computing and cloud computing is an ideal solution for the high performance computing demands in life sciences. Budget constraints are limiting access to necessary compute resources at the very time when the explosive growth in life sciences data makes access increasingly desirable.

“HPC-oriented clouds supporting the latest heterogeneous architectures can provide even small research groups with affordable access to diverse computer resources,” said Steve Hebert, cofounder of Nimbix. “Our goal through this promotion is to give genomics researchers access to world-class HPC resources and to show them that heterogeneous cloud computing is extremely powerful, yet simple and affordable.”

Nimbix installed their first Convey system in 2011 when the two companies partnered to deliver Convey’s unique hybrid-core architecture and bioinformatics personalities as a cloud-based HPC solution. Since then, users of the Nimbix Accelerated Compute Cloud have achieved greater than 50x speed up of sequence searches using Convey’s hybrid-core system. Users have also seen impressive acceleration, inclusive of data transfer times, for mapping and de novo assembly—both in terms of improving runtimes and increasing throughput.

Convey’s hybrid-core architecture pairs classic Intel® x86 microprocessors with a coprocessor comprised of FPGAs. Particular algorithms—DNA sequence assembly, for example—are optimized and translated into code that’s loadable onto the FPGAs at runtime. The Convey architecture also features a highly parallel memory subsystem to further increase performance. Convey’s approach provides very fast access to random access memory, which is useful for the hashing functions so widely used in bioinformatics.