CycleCloud 6.5.3 released

Last week we pushed the button on the latest release of our CycleCloud software for managing cloud HPC and Big Compute workloads. This release has one particular feature that many customers customers asked for: Cost Alerting. This new feature will give you the ability to easily set cost alerts on a per-cluster basis. You can set the alert to be dollars per day or per week. This gives you a great way to manage consumption and assure that users aren’t blowing through budgets. After all, you want to give your users access to unlimited compute, but you don’t want to give them an unlimited budget. Clusters from any supported cloud service provider display an estimated compute cost along with the core-hour usage. Daily or monthly budgets are set from the cluster page and trigger alerts when the threshold is crossed. Because the appropriate action when a cluster goes over budget varies, the CycleCloud software does not take any automated enforcement action. We find most customers try to set it the threshold to some percentage of total budget to give them a heads up before exceeding the budget. The percentage can be a function of the type of work and size of budget. In addition to the cost alerting, we’ve added additional features to our Microsoft Azure support. CycleCloud now uses Azure Managed Disks and Images for virtual machines, simplifying management of storage and improving performance. Azure instances will automatically use CycleCloud’s standalone DNS configuration to improve the experience for Open Grid Scheduler users. Current customers can download CycleCloud 6.5.3 from the Cycle Computing Portal. If you’d like to learn...
How do we describe the changes cloud HPC brings?

How do we describe the changes cloud HPC brings?

Last week on Twitter, Kim McMahon asked “What word do you use for a disruptive technology – one that changes how things are done – other than ‘disruptive’?” That’s a great question. We like the word “transformative”. In fact, we recently published a solution brief describing how our customers have transformed their businesses with cloud HPC and big compute. Moving a big compute workload into the cloud is more than just changing where the jobs run. The scale and flexibility that cloud computing offers has the ability to fundamentally change business processes. Sure, you could call this “disruptive”, but that implies a single event and it sounds unpleasant. “Transformative” has a more positive connotation and it represents an ongoing change. If you’re interested in how cloud HPC and big compute can transform your business, contact us for a free cloud readiness...

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...