February 14, 2012
Life science companies are increasingly looking to the cloud as a way of facilitating more efficient business models. That was the case with Metrum Research Group, a Connecticut-based biotech firm that transferred its entire IT infrastructure onto the Amazon cloud.
While many companies are comfortable taking cloud baby steps, Metrum made the big leap into the fluffy white stuff. According to an article in Bio-IT World, the company "is leveraging the capabilities of Amazon Web Services (AWS) for its core pharmacometrics technology platform, with Elastic Compute Cloud (EC2), Simple Storage Service (S3), and Elastic Block Storage (EBS) services. Highly secure VPC environments are under development and nearing deployment."
Before the switch, Metrum, ran its modeling and simulation workloads on a traditional co-located computational grid system comprised of six servers and 32 cores. Due to uneven resource demand, it was common for the grid to be over- or under-subscribed, not the best use of resources. During busy times, 32 cores was not enough, Jeffrey Hane, CIO and COO of Metrum Research Group, tells BIO-IT World, and other times a portion of the cores sat idle.
As the company grew, it became clear that they needed to expand their computing infrastructure. "Unlimited, flexible compute power was the driving force to go to the cloud. We also wanted to simplify, and we didn’t want a hybrid system. So we opted to move everything up," explains Hane.
The cloud deployment has been up and running for several months now and Hane outlines several benefits. Whereas the entire company previously shared 32 cores, now each scientist has access to at least 100 multicore instances launched on demand from their workstations. This increase in computational power has led to quicker turnaround times. In some cases, this means a return measured in hours instead of days. Hane explains that while the system is much easier to manage, costs are about the same as before. Plus he anticipates that increased customer satisfaction will result in a higher ROI.
As for potential drawbacks, the COO notes that despite having increased control over system compliance, he fully expects to be challenged under FDA compliance guidelines (21 CFR Part 11). Being able to identify improvements and employing security tools will assist the company in explaining their position.
The ever-growing complexity of scientific and engineering problems continues to pose new computational challenges. Thus, we present a novel federation model that enables end-users with the ability to aggregate heterogeneous resource scale problems. The feasibility of this federation model has been proven, in the context of the UberCloud HPC Experiment, by gathering the most comprehensive information to date on the effects of pillars on microfluid channel flow.
Large-scale, worldwide scientific initiatives rely on some cloud-based system to both coordinate efforts and manage computational efforts at peak times that cannot be contained within the combined in-house HPC resources. Last week at Google I/O, Brookhaven National Lab’s Sergey Panitkin discussed the role of the Google Compute Engine in providing computational support to ATLAS, a detector of high-energy particles at the Large Hadron Collider (LHC).
Frank Ding, engineering analysis & technical computing manager at Simpson Strong-Tie, discussed the advantages of utilizing the cloud for occasional scientific computing, identified the obstacles to doing so, and proposed workarounds to some of those obstacles.
05/10/2013 | Cleversafe, Cray, DDN, NetApp, & Panasas | From Wall Street to Hollywood, drug discovery to homeland security, companies and organizations of all sizes and stripes are coming face to face with the challenges – and opportunities – afforded by Big Data. Before anyone can utilize these extraordinary data repositories, however, they must first harness and manage their data stores, and do so utilizing technologies that underscore affordability, security, and scalability.
04/02/2012 | AMD | Developers today are just beginning to explore the potential of heterogeneous computing, but the potential for this new paradigm is huge. This brief article reviews how the technology might impact a range of application development areas, including client experiences and cloud-based data management. As platforms like OpenCL continue to evolve, the benefits of heterogeneous computing will become even more accessible. Use this quick article to jump-start your own thinking on heterogeneous computing.