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:
The end-user experience for using CycleCloud is: