September 22, 2016
Declining DNA sequencing costs and the rush to do whole genome sequencing (WGS) of large cohort populations – think 5000 subjects now, but many more thousands Read more…
September 5, 2013
When it comes to mainstream adoption of the use of GPUs and other accelerators, one of the primary barriers lies in programmability. While the vendor communities around accelerators have pushed to flatten the learning curve, the fact remains that it takes special effort on the part of ordinary developers to undertake the educational process. In this in-depth audio feature, we talk to Rice University researcher, Max Grossman about how Java... Read more…
March 4, 2010
Cray and Microsoft Research partner on cloud computing project; IBM donates a POWER7-based supercomputer to Rice University; and the Kavli Foundation hosts a dialogue on the convergence of nanoscience and neuroscience. We recap those stories and more in our weekly wrapup. 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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