“The promising new parameter in place of the transistor count is the perceived increase in the capacity and bandwidth of storage, driven by device, architectural, as well as packaging innovations: DRAM-alternative Non-Volatile Memory (NVM) devices, 3-D memory and logic stacking evolving from VIAs to direct silicone stacking, as well as next-generation terabit optics and networks. The overall effect of this is that, the trend to increase the computational intensity as advocated today will no longer result in performance increase, but rather, exploiting the memory and bandwidth capacities will instead be the right methodology.”
Today AMD, ARM, Huawei, IBM, Mellanox, Qualcomm, and Xilinx announced a collaboration to bring the CCIX high-performance open acceleration framework to data centers. The companies are collaborating on the specification for the new Cache Coherent Interconnect for Accelerators (CCIX). For the first time in the industry, a single interconnect technology specification will ensure that processors using different instruction set architectures (ISA) can coherently share data with accelerators and enable efficient heterogeneous computing – significantly improving compute efficiency for servers running data center workloads.
“With NVIDIA GPU technology on IBM Cloud, we are one step closer to offering supercomputing performance on a pay-as-you-go basis, which makes this new approach to tackling big data problems accessible to customers of all sizes,” says Jerry Gutierrez, HPC leader for SoftLayer, an IBM Company. “We’re at an inflection point in our industry, where GPU technology is opening the door for the next wave of breakthroughs across multiple industries.”
Steve Oberlin, chief technology officer for accelerated computing at NVIDIA, will give two NCSA 30th Anniversary Featured Lectures on May 26. The morning talk is tailored for NCSA staff, Computer Science, and Electrical and Computer Engineering students and faculty. The second talk is open to the public.
Any performance improvements that could be wrung out of supercomputers by adding more power have long been exhausted. New supercomputers demand new options that will give scientists a sleek, efficient partner in making new discoveries such as the new supercomputer called Summit that’s being developed and is to arrive at Oak Ridge National Lab in the next couple of years. “If necessity is the mother of invention, we’ll have some inventions happening soon,” says deputy division director of Argonne Leadership Computing Facility Susan Coghlan.
In this special guest feature, Robert Roe from Scientific Computing World describes why Nvidia is in the driver’s seat for Deep Learning. “Nvidia CEO Jen-Hsun Huang’s theme for the opening keynote was based on “a new computing model.” Huang explained that Nvidia builds computing technologies for the most demanding computer users in the world and that the most demanding applications require GPU acceleration. ‘The computers you need aren’t run of the mill. You need supercharged computing, GPU accelerated computing’ said Huang.”
In this video, Oklahoma State Director of HPC Dana Brunson describes how the Cowboy supercomputer powers research. “High performance computing is often used for simulations that may be too big, too small, too fast, too slow, too dangerous or too costly, another thing it’s used for involves data. So you may remember the human genome project it took nearly a decade and cost a billion dollars, these sorts of things can now be done over the weekend for under a thousand dollars. Our current super computer is named Cowboy and it was funded by a 2011 National Science Foundation Grant and it has been serving us very well.”
In this podcast, the Radio Free HPC team recaps the ASC16 Student Cluster Competition in China and the 2016 MSST Conference in Santa Clara. Dan spent a week in Wuxi interviewing ASC16 student teams, he came back impressed with the Linpack benchmark tricks from the team at Zhejiang University, who set a new student LINPACK record with 12.03 TFlop/s. Meanwhile, Rich was in Santa Clara for the MSST conference, where he captured two days of talks on Mass Storage Technologies.
In this video from the GPU Hackathon at the University of Delaware, attendees tune their code to accelerate their application performance. The 5-day intensive GPU programming Hackathon was held in collaboration with Oak Ridge National Lab (ORNL). “Thanks to a partnership with NASA Langley Research Center, Oak Ridge National Laboratory, National Cancer Institute, National Institutes of Health (NIH), Brookhaven National Laboratory and the UD College of Engineering, UD students had access to the world’s second largest supercomputer — the Titan — to help solve real-world problems.”
Over at the Nvidia Blog, George Millington writes that, the fourth consecutive year, the Nvidia Tesla Accelerated Computing Platform helped set new milestones in the Asia Student Supercomputer Challenge, the world’s largest supercomputer competition.