October 25, 2010
If there is one consistent use case for cloud that emerges in daily HPC and cloud news scavenging missions, it is more often than not in the pharmaceutical industry. This industry has big data demands that have, until relatively recently, required big machines to crunch the massive amounts of information required for drug discovery quests and other internal development projects.
The relatively high cloud adoption rate among pharmaceutical companies means that for other enterprises—those who have nothing to do with finding cures or improving health—can look to this industry for insights about real-world cloud use.
While many such companies have yet to go public about how they’re using cloud specifically or for what types of workloads, those who have, including Eli Lilly, are offloading many of their non-mission critical applications onto public resources like Amazon’s EC2 to improve efficiency and free up their computational resources for other projects.
Ellen Rubin, founder of CloudSwitch, a company that allows enterprises to run their applications in the cloud without application retooling or restructuring of management solutions weighed in on the value of the cloud for pharmaceutical companies this week, suggesting that the “beta” phase of cloud computing for many drug companies is closing as more look to cloud as a way to secure on-demand access to shorten time to market.
As Rubin noted, there are a number of reasons why the cloud is an ideal fit for pharmaceutical companies. “They need massive computing power for the complex informatics that go into scientific and drug development research. They’re familiar with high-performance grid computing and the need to scale resources to support their R&D work” but until the arrival of cloud, they’ve had to handle the costs and wait times associated with making such resources available internally. These delays can result in millions of dollars of lost revenue, thus for this industry in particular, on-demand access is key—and is something the cloud can provide.
In Rubin’s experiences with customers, the key goals that have emerged (and yes, we should remember that her company is providing a range of solutions that fit this bill) for users in this industry are related to burst/peak scale out capabilities, improving application lifecycles and the need for enhanced ways to collaborate with other researchers or teams. The cloud can assist with all three of these things and in her view, has already gone a long way in helping this industry blaze a trail for other enterprises to follow.
Full story at DatacenterKnowledge
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.
Read more...
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).
Read more...
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.
Read more...
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.