In this podcast, the Radio Free HPC team looks at the new OpenCAPI interconnect standard. “Released this week by the newly formed OpenCAPI Consortium, OpenCAPI provides an open, high-speed pathway for different types of technology – advanced memory, accelerators, networking and storage – to more tightly integrate their functions within servers. This data-centric approach to server design, which puts the compute power closer to the data, removes inefficiencies in traditional system architectures to help eliminate system bottlenecks and can significantly improve server performance.”
The third Workshop on Accelerator Programming Using Directives (WACCPD) has posted their meeting agenda. Held in conjunction with SC16, the WACCPD workshop takes place Nov. 14 in Salt Lake City. “To address the rapid pace of hardware evolution, developers continue to explore and add richer features to the various (parallel) programming standards. Domain scientists continue to explore the programming and tools space while preparing themselves for future Exascale systems. This workshop explores innovative language features – their implementations, compilation & runtime scheduling techniques, performance optimization strategies, autotuning tools exploring the optimization space and so on. WACCPD has been one of the major forums for bringing together the users, developers and tools community to share their knowledge and experiences of using directives and similar approaches to program emerging complex systems.”
Adam Buntzman and his colleagues at the University of Arizona recently developed a tool that uses CyVerse supercomputing resources to create the first nearly comprehensive map of the human immunome, all the possible immune receptors our bodies can make. “When people go to a clinic, it’s usually because they’re already sick,” Buntzman said. “If doctors could detect cancerous cells before they grow drastically out of proportion to healthy cells, patients would have much higher odds of successful cancer treatment and survival.”
Today AMD announced that the Alibaba Cloud will use AMD Radeon Pro GPU technology to help expand its cloud computing offerings and accelerate adoption of its cloud-based services. “The partnership between AMD and Alibaba Cloud will bring both of our customers more diversified, cloud-based graphic processing solutions. It is our vision to work together with leading technology firms like AMD to empower businesses in every industry with cutting-edge technologies and computing capabilities,” said Simon Hu, president of Alibaba Cloud.
Jack Dongarra presented this talk at the Argonne Training Program on Extreme-Scale Computing. “ATPESC provides intensive, two weeks of training on the key skills, approaches, and tools to design, implement, and execute computational science and engineering applications on current high-end computing systems and the leadership-class computing systems of the future.”
“IBM has decided to double down on our commitment to open standards and enablement of industry innovation by opening up access to our CAPI technology to the entire industry. With the support of our OpenCAPI co-founders, we have created a new OpenCAPI specification that tremendously improves performance over our prior specification and IBM will be among the first to implement it with our POWER9 products expected in 2017.”
Today Pure Storage announced the availability of petabyte-scale storage for mission-critical cloud IT, anchored by the release of the next-generation of FlashArray//m the company’s flagship all-flash storage array, which now delivers best-in-class performance with the simplicity and agility of public cloud.
European scientists and researchers can now apply for access to PRACE supercomputing resources through the PRACE Call 14.
In this video from the HPC Advisory Council Spain Conference, Martin Hilgeman from Dell Technologies provides a detailed overview of how to approach code optimization through providing more parallelism. “Martin Hilgeman brings perspectives of a system builder to the massively parallel performance discussion – examining the continuous advances in multi-core architectures and its impact on users and computational work.”
In this video, NYU researchers describe their plans to advance deep learning with their new Nvidia DGX-1 AI supercomputer. “The DGX-1 is going to be used in just about every research project we have here,” said Yann LeCun, founding director of the NYU Center for Data Science and a pioneer in the field of AI. “The students here can’t wait to get their hands on it.”