October 20, 2010
Autodesk, makers of software for engineers and designers, has slowly been rolling out an increasingly long list of applications that are cloud-ready via their own dedicated servers. The company is attempting to make access and use of their software easier while granting it to a broader range of users. Read more…
September 27, 2010
At this year's GPU Technology Conference in San Jose, GPU computing in the scientific and technical research space took center stage, almost to the point where it became possible, at least for a moment, to forget the gaming roots and movement from the mainstream to the deeply technical. Read more…
July 23, 2010
Autodesk requires significant hardware investment but until recently, most of the software offerings delivered in the SaaS model have been limited. The company's products are a perfect fit for cloud and the company sees clouds on the horizon for more of its simulation offerings. 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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