March 01, 2013
Without a proper toolkit, running HPC applications and computations in the cloud can be a tedious exercise, especially for those who run those with relative infrequency.
StarCluster may help with that problem. StarCluster, according to Admin Magazine's Gavin Burris, is a project developed by MIT's Software Tools for Academics and Researchers team, hence the STAR. It caters to those in the scientific and researching fields and in particular those who wish to utilize clusters to perform computations but have not the tools in house to do so.
In order to get started on StarCluster, one must, according to Burris, have an Amazon Web Services (AWS) account, as the toolkit that codes in Python runs on Amazon's Elastic Compute Cloud (EC2).
Burris proceeded to walk through the process of installing and configuring StarCluster before ultimately showing how a test computation would run. He used a fairly common test case, using a Monte Carlo simulation to approximate the value of pi.
Understanding how to set up these clusters and perform jobs and tasks on them on a case-by-case basis can be critical for system programmers who only intermittently require the use of an HPC cluster and thus have no use for an onsite cluster.
"The cloud has become a key resource in the support of HPC," said Burris has he discussed the value of StarCluster within HPC in the cloud in his conclusion. "Given the proper use case, cloud offerings are an affordable fit for a variety of different workflows. A key tool in any systems programmer's arsenal should be the StarCluster toolkit, which provides a powerful interface for harnessing these cloud resources in an effective manner."
Burris espoused the notion of utilizing cloud-based high performance computing in general, noting that it allows programmers and administrators to build and develop custom ecosystems for researchers. "Cloud computing is the next level of abstraction, allowing for the programmable out-sourcing of the data center," Burris mentioned in his endorsement of using HPC in the cloud. "What would traditionally be a locally managed room, full of physical hardware with a three- to five-year life cycle, situated within a managed facility that provides electricity and cooling, is now available through a programmable API."
Other advantages according to Burris include outsourcing the task of chasing loose red lights and failed servers to a group in Amazon that specifically is trained for that.
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.
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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.