February 24, 2010
Cluster computing systems have caused disruptive changes in the HPC market. One consequence of the range of requirements for cluster networking is that the leading interconnects in HPC are Gigabit Ethernet (GbE), which is based on Ethernet networking standard, and InfiniBand, delivering upwards of 10X performance vs. GbE. Both show significant deployment in HPC. Read more…
June 15, 2009
So far, 10GbE has been a high-end luxury for environments that want maximum performance regardless of cost, but that's changing fast. The per-port pricing gap between 10GbE and alternate network options is narrowing rapidly as more vendors increase the competitive pressure on pricing for related components. Read more…
January 7, 2009
The advent of 10 Gigabit Ethernet created major opportunities for equipment startups, but this may not be the case for the future 40 and 100 Gigabit Ethernet markets. 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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