“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.
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 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.
The NVIDIA DGX-1 features up to 170 teraflops of half precision (FP16) peak performance, 8 Tesla P100 GPU accelerators with 16GB of memory per GPU, 7TB SSD DL Cache, and a NVLink Hybrid Cube Mesh. Packaged with fully integrated hardware and easily deployed software, it is the world’s first system built specifically for deep learning and with NVIDIA’s revolutionary, Pascal-powered Tesla P100 accelerators, interconnected with NVIDIA’s NVLink. NVIDIA designed the DGX-1 to meet the never-ending computing demands of artificial intelligence and claims it can provide the throughput of 250 CPU-based servers delivered via a single box.
In this podcast, the Radio Free HPC team recaps the GPU Technology Conference, which wrapped up last week in San Jose.
Since Rich is traveling around in some desert somewhere, Dan and Henry go it alone and discuss the new Pascal (P1000) GPU, NVIDIA’s new server, and what happened at the concurrent OpenPOWER conference.”
“Cavium ThunderX has significant differentiation in the 64-bit ARM market as Cavium is the first ARMv8 vendor to deliver dual socket support with full ARMv8.1 implementation and significant advantage in CPU cores with 48 cores per socket. In addition, ThunderX supports large memory capacity (512GB per socket, 1TB in a 2S system) with excellent memory bandwidth and low memory latency. In addition, ThunderX includes multiple 10 GbE / 40GbE network interfaces delivering excellent IO throughput. These features enable ThunderX to deliver the core performance & scale out capability that the HPC market requires.”
In this video from the 2016 GPU Technology Conference, Jason Pai from Supermicro describes the new 1028GQ-TRT SuperServer. With support for up to four Nvidia Tesla K80 GPUs, the 1U superserver offers extreme compute density in 1U of rack space. “From HPC to Deep Learning and Big Data Analytics, denser, more powerful GPU solutions have become a necessity in order to service the next generation of GPU-accelerated applications. At GTC, Supermicro demonstrated how these applications have progressed, and how its GPU solutions are influencing this evolution.”