Although both the enterprise and HPC can benefit from virtualization, the two have had dissimilar requirements. This article is the second in an editorial series that explores the benefits the HPC community can achieve by adopting HPC virtualization and cloud technologies.
Over the past several years, virtualization has made major inroads into enterprise IT infrastructures. And now it is moving into the realm of high performance computing (HPC), especially for such compute intensive applications as electronic design automation (EDA), life sciences, financial services and digital media entertainment. This article is the first in a series that explores the benefits the HPC community can achieve by adopting proven virtualization and cloud technologies.
Everything from life sciences to the financial industry are relying on HPC clusters to perform complex and critical operations. Moving forward, there will be a lot more reliance on various HPC systems. So the all-important question comes in – How do you select, deploy and manage it all? Fortunately, IBM, Intel and NCAR have teamed up to explain their view on best practices selecting an HPC cluster using the process behind building the NCAR Wyoming Supercomputing Center.
High performance technical computing continues to transform the capabilities of organizations across a range of industries—helping them to tackle unprecedented big data analysis, generate competitive business advantage, and expand the limits of science and medicine. To keep pushing those boundaries, organizations are continually seeking ways to get more out of their technical computing systems.
“How can capital markets firms handle the computational challenges presented by regulatory mandates and big data? Chances are the solution will involve high-performance computing powered by parallelism, or the ability to leverage multiple hardware resources to run code simultaneously. But while hardware architectures have been moving in that direction for years, many firms’ software isn’t written to take advantage of multiple threads of execution.”