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.
In quieter times, sounding the bell of funding big science with big systems tends to resonate further than when ears are already burning with sour economic and national security news. For exascale's future, however, the time could be ripe to instill some sense of urgency....
Read more...
In a recent solicitation, the NSF laid out needs for furthering its scientific and engineering infrastructure with new tools to go beyond top performance, Having already delivered systems like Stampede and Blue Waters, they're turning an eye to solving data-intensive challenges. We spoke with the agency's Irene Qualters and Barry Schneider about..
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...
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.
04/15/2013 | Bull | “50% of HPC users say their largest jobs scale to 120 cores or less.” How about yours? Are your codes ready to take advantage of today’s and tomorrow’s ultra-parallel HPC systems? Download this White Paper by Analysts Intersect360 Research to see what Bull and Intel’s Center for Excellence in Parallel Programming can do for your codes.
In this demonstration of SGI DMF ZeroWatt disk solution, Dr. Eng Lim Goh, SGI CTO, discusses a function of SGI DMF software to reduce costs and power consumption in an exascale (Big Data) storage datacenter.
The Cray CS300-AC cluster supercomputer offers energy efficient, air-cooled design based on modular, industry-standard platforms featuring the latest processor and network technologies and a wide range of datacenter cooling requirements.