December 15, 2011
The data deluge in the life sciences is no where more acute than at Chinese genomics powerhouse BGI, which probably sequences more DNA than any other organization in the world. To turn that data into something meaningful for genomic researchers, the institute has begun to employ GPU-accelerated HPC to greatly reduce processing times. In doing so, BGI was able to increase computational throughput by an order of magnitude or more. Read more…
April 11, 2011
Dr. Asoke K. Taukder discusses the range of biological applications that can be run in a cloud environment and provides an overview of how high performance computing in the cloud can reshape the way research in the life science is performed. Read more…
Whether an organization chooses a cloud for general business needs or a highly tailored workload, the spectrum of offerings and configurations can be overwhelming. To help you navigate the various cloud options available today, we're breaking down your options, exploring pros and cons, and sharing ways to keep your options open and your business agile as you execute your cloud strategy.
Researchers in academic labs and commercial R&D groups continue to need more compute capacity, which means leveraging the latest innovations in HPC technologies as well as an assortment of resources to meet the unique needs of different workloads. Increasingly, systems based on Arm processors are stepping into that role, offering low power consumption and strategic advantages for HPC workloads.
Whether it's for fraud detection, personalized medicine, manufacturing, smart cities, autonomous vehicles and many other areas, advanced-scale computing has exploded beyond the realm of academia and government and into the private sector. And with data-intensive workloads on the rise, commercial users are turning to HPC-based infrastructure to run the AI, ML and cognitive computing applications that their organizations depend on.
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