Cycle Computing ramps global 50,000-core cluster for Schrodinger molecular research

19 Apr 2012 New York - Cycle Computing provisioned a 50,000-core utility supercomputer in the Amazon Web Services (AWS) Cloud for Schrödinger and Nimbus Discovery to accelerate lead identification via virtual screening. This milestone - the largest of its kind - is Cycle Computing's fifth massive cluster in less than two years on the heels of a 30,000 cluster in October 2011, illustrating Cycle's continued leadership in delivering full-featured and scalable cluster deployments. Cycle Computing revealed the cluster creation during today's opening keynote at the AWS Summit in New York City.

Schrödinger's widely used computational docking application, Glide, performs high-throughput virtual screening of compound libraries for identification of drug discovery leads. Computing resource and time constraints traditionally limit the extent with which ligand conformations can be explored, potentially leading to false negative while the same constraints may require a less accurate level of scoring, which can lead to false positives. Tapping into Cycle's utility supercomputing, Schrödinger ran a virtual screen in collaboration with Nimbus Discovery of 21 million compounds against a protein target. The run required 12.5 processor years and completed in less than three hours.

"Typically, we have to weigh tradeoffs between time and accuracy in a project", stated Ramy Farid, President, Schrödinger. "With Cycle's utility supercomputing, we didn't have to compromise the accuracy in favor of faster throughput, and we were able to run the virtual screen using the appropriate levels of scoring and sampling."

The global 50,000-core cluster was run with CycleCloud, Cycle's flagship HPC in the Cloud service that runs on AWS. Replicating data across seven AWS regions while automating provisioned resources, CycleCloud run time per job averaged 11 minutes and the total work completed topped 100,000 hours. Schrödinger's researchers completed over 4,480 days of work, nearing 12.5 years of computations in a few hours, with cost under $4,900 per hour at peak requiring no upfront capital.

"By leveraging AWS, Cycle Computing is able to perform highly sophisticated computations in minutes at a fraction of what it would cost for businesses to purchase the high performance computing infrastructure themselves", stated Terry Wise, Director of Business Development, Amazon Web Services. "Cycle Computing brings an incredible amount of innovation to our partner ecosystem and we're excited to continue working with them to enable businesses to take advantage of AWS's highly scalable, elastic and low cost technology infrastructure."

Cluster and performance analytics software CycleServer tracked utilization, diagnosed performance and managed scientific workflow. Replicating the success of employing next generation developments, Cycle engineers continued open source strategies, including Condor, Linux, and Opscode's Chef Cloud infrastructure automation system. Cycle's Chef monitoring and analytics plug-in, called Grill, provided visualization into scaling the infrastructure environment and eliminated the need for additional Chef servers with alert technology supporting data around installations, driving down preparation and operational overhead.

Leveraging CycleCloud software and Cycle's HPC proficiency delivered these stats:

• Infrastructure: 6,742 Amazon EC2 instances /58.79 TB RAM
• Global-scale: Multi-datacenter clusters with simple user interfaces
• Cluster Size: 51,132 cores, 58.78TB RAM
• Security: Engineered with HTTPS, SSH & 256-bit AES encryption
• AWS Regions:7 (us-east, us-west1, us-west2, eu-west, sa-east, ap-northeast, ap-southeast)

The end-user experience for using CycleCloud is:

• User Effort: One-click global cluster at massive scale
• Start-up Time: Thousands of cores in minutes, full cluster in 2 hours
• Up-front Capital Investment: $0
• Total Infrastructure Cost: $4,828.85/hour

"Researchers can now meet their aspirations and bottom line through secure, mega-elastic and fully-supported utility supercomputers", stated Jason Stowe, founder and CEO, Cycle Computing. "By harvesting the raw infrastructure from AWS, we empower Schrödinger's scientific accuracy while allowing them to push the boundaries of computation research. Creating robust, reliable and importantly repeatable supercomputers means any industry from life sciences, risk management, quantitative finance to product design can reap the benefits as we tip the scales towards the next generation of massive clusters."