Improving ALS research with Google Cloud, Schrödinger, and Cycle Computing

Today we published a case study describing how the use of Google Cloud enabled one professor to do work she never thought possible. May Khanna, Assistant Professor of Pharmacology at the University of Arizona, studies pharmacological treatments for pain. Her specific area of expertise focuses on research that uses protein binding to develop possible treatments. Using our CycleCloud™ software to manage a 5,000 core Google Cloud Preemptible VM cluster running Schrödinger® Glide™ has enabled research she never thought possible. This cluster was used to run 20,000 hours of docking computations in four hours for $192, thanks to the simple, consistent pricing of GCP’s Preemptible VMs. The n1-highcpu-16 instances she used have 16 virtual cores and 60 gigabyte of RAM, so they’re well-suited for this kind of compute-heavy workload. For this project, Professor Khanna wanted to analyze a protein associated with amyotrophic lateral sclerosis, also known as “ALS” or “Lou Gerhig’s disease”. ALS has no known cure and causes pain and eventual death for some 20,000 people in the United States every year. Protein binding simulation is compute-intensive, even under the constraints researchers often apply to achieve their results in a reasonable time. For example, proteins are often simulated in isolation and the binding sites are restricted to a set of known-or-expected active locations on the protein. With those constraints, Professor Khanna was only able to simulate 50,000 compounds, which yielded a grand total of four possible hits. She was about to give up on the project when she approached Cycle Computing. Using her Google Cloud cluster, she was able to simulate binding of a million compounds in just a...
Simulating Hyperloop pods on Microsoft Azure

Simulating Hyperloop pods on Microsoft Azure

Earlier today, we published a case study and press release about some work we did with the HyperXite team from the University of California, Irvine team and their efforts in the Hyperloop competition. This team leveraged CycleCloud to run ANSYS Fluent™ on Microsoft Azure Big Compute to to complete their iterations in 48 hours, enabling them to get results fast enough to make adjustments and modifications to the design then rerun the simulations until they were able to converge on a final solution. All for less than $600 in simulation costs. This was a case where Cloud enabled them to do something they could not have done any other way. As a bit of background, Elon Musk’s SpaceX started the Hyperloop project as a way to accelerate development of a fast, safe, low-power, and cheap method of transporting people and freight. HyperXite was one of 27 teams that competed recently. Nima Mohseni, the team’s simulation lead, used the popular computational fluid dynamics software ANSYS Fluent™ to perform modeling of the pod. Key areas that the team modeled were related to the braking approach that they were using. Through the use of simulation, they were able to show that they could brake with just the use of magnetic force, removing the need for mechanical brakes. This reduced weight, increased efficiency, and improved the overall design, which was recognized with a Pod Technical Excellence award last year. Using the CycleCloud software suite, the HyperXite team created an Open Grid Scheduler cluster leveraging Azure’s memory-optimized instances in the East US region. Each instance has 16 cores based on the 2.4 GHz Intel...

LAMMPS scaling on Azure InfiniBand

While public clouds have gained a reputation as strong performers and a good fit for batch and throughput-based workloads, we often still hear that clouds don’t work for “real” or “at scale” high performance computing applications. That’s not necessarily true, however, as Microsoft Azure has continued its rollout of Infiniband-enabled virtual machines. InfiniBand is the most common interconnect among TOP500 supercomputers, and Microsoft has deployed the powerful and stable iteration known as “FDR” Infiniband. Best of all, these exceptionally high levels of interconnect performance are now available to everyone on Azure’s new H-series and N-series virtual machines. To see how well Azure’s Infiniband works, we benchmarked LAMMPS, an open source molecular dynamics simulation package developed by Sandia National Laboratories. LAMMPS is used widely-used across government, academia, and industry, and is frequently a computational tool of choice for some of the most advanced science and engineering teams. LAMMPS relies heavily on MPI to achieve sustained high performance on real-world workloads, and can scale to many hundreds of thousands of CPU cores. Armed with H16r virtual machines, we used the Lennard-Jones liquid benchmark. We selected the “LJ” benchmark and tested two scenarios: “weak scaling”, in which every core simulated 32,000 atoms no matter how many cores were utilized, and “strong scaling” which used a fixed problem size of 512,000 atoms with an increasing number of cores. Both scenarios simulated 1,000 time steps. We performed no “data dumps” (i.e. intermediate output to disk) in order to isolate solver performance, and ran 30 test jobs per data point in order to obtain statistical significance and associated averages. In summary, the results were impressive...

Cycle Computing Collaborates with ANSYS on its Enterprise Cloud HPC Offering

CycleCloud to provide orchestration and management for leading engineering simulation cloud offering New York, NY – (Marketwired – February 2, 2017) – Cycle Computing, the global leader in Big Compute and Cloud HPC orchestration, today announced that ANSYS has officially chosen its CycleCloud product to spearhead the orchestration and management behind the ANSYS® Enterprise Cloud™. ANSYS is the global leader in engineering simulation bringing clarity and insight to its customers’ most complex design challenges. Many ANSYS customers require simulation workloads to be migrated to the cloud, as customers look to leverage dynamic cloud capacity to accelerate time to result, shorten product development cycles and reduce costs. ANSYS Enterprise Cloud, an enterprise-level engineering simulation platform, delivered on the Amazon Web Service (AWS) global platform using the CycleCloud software platform, enables this migration, including secure storage and data management and access to resources for interactive and batch execution that scales on demand for virtual-private cloud (VPC) for enterprise simulation. “Our collaboration with Cycle Computing enables the ANSYS Enterprise Cloud to meet the elastic capacity and security requirements of enterprise customers,” said Ray Milhem, vice president, Enterprise Solutions and Cloud, ANSYS. “CycleCloud has run some of the largest Cloud Big Compute and Cloud HPC projects in the world, and we are excited to bring their associated, proven software capability to our global customers with the ANSYS Enterprise Cloud.” Cycle Computing’s CycleCloud will optimize ANSYS Enterprise Cloud with the orchestration of cloud HPC clusters with ANSYS software applications in the cloud, ensuring optimal AWS Spot instance usage, and ensuring that appropriate resources are used for the right amount of time in the ANSYS...