The Hot Interconnects conference has issued its Call for Papers. The event takes place August 14-16 in Silicon Valley. "Hot Interconnects is the premier international forum for researchers and developers of state-of-the-art hardware and software architectures and implementations for interconnection networks of all scales, ranging from multi-core on-chip interconnects to those within systems, clusters, datacenters and Clouds. This yearly conference is attended by leaders in industry and academia. The atmosphere provides for a wealth of opportunities to interact with individuals at the forefront of this field."
In this special guest feature from the SC19 Blog, Charity Plata from Brookhaven National Lab catches up with Dr. Lin Gan from Tsinghua University, who's outstanding work in HPC has been recognized with a number of awards including the Gordon Bell Prize. As a highly awarded young researcher who already has been acknowledged for “outstanding, influential, and potentially long-lasting contributions” in HPC, Gan shares his thoughts on future supercomputers and what it means to say, “HPC Is Now."
Today the European PRACE initiative announced that Dr Debora Sijacki from the University of Cambridge will receive the 2019 PRACE Ada Lovelace Award for HPC for her outstanding contributions to and impact on high performance computing in Europe. As a computational cosmologist she has achieved numerous high-impact results in astrophysics based on numerical simulations on state-of-the-art supercomputers.
Rahul Ramachandran from NASA gave this talk at the HPC User Forum. "NASA’s Earth Science Division (ESD) missions help us to understand our planet’s interconnected systems, from a global scale down to minute processes. ESD delivers the technology, expertise and global observations that help us to map the myriad connections between our planet’s vital processes and the effects of ongoing natural and human-caused changes."
Rick Wagner from Globus gave this talk at the Singularity User Group "We package the imSim software inside a Singularity container so that it can be developed independently, packaged to include all dependencies, trivially scaled across thousands of computing nodes, and seamlessly moved between computing systems. To date, the simulation workflow has consumed more than 30M core hours using 4K nodes (256K cores) on Argonne’s Theta supercomputer and 2K nodes (128K cores) on NERSC’s Cori supercomputer."
In this video from the GPU Technology Conference, Dan Olds from OrionX discusses the human impact of AI with Greg Schmidt from HPE. The industry buzz about artificial intelligence and deep learning typically focuses on hardware, software, frameworks, performance, and the lofty business plans that will be enabled by this new technology. What we don’t […]
Young people looking to further their careers in HPC are encouraged to sign up for the ISC STEM Student Day program. As part of the ISC High Performance Conference coming to Frankfurt in June, this program offers undergraduate and graduate students an early insight into the field of high performance computing as well as an opportunity to meet the important players in the sector.
Developers are increasingly besieged by the big data deluge. Intel Distribution for Python uses tried-and-true libraries like the Intel Math Kernel Library (Intel MKL)and the Intel Data Analytics Acceleration Library to make Python code scream right out of the box – no recoding required. Intel highlights some of the benefits dev teams can expect in this sponsored post.
North Carolina State University researchers have developed a technique that reduces training time for deep learning networks by more than 60 percent without sacrificing accuracy, accelerating the development of new artificial intelligence applications. “One of the biggest challenges facing the development of new AI tools is the amount of time and computing power it takes to train deep learning networks to identify and respond to the data patterns that are relevant to their applications. We’ve come up with a way to expedite that process, which we call Adaptive Deep Reuse. We have demonstrated that it can reduce training times by up to 69 percent without accuracy loss.”
Spectra Logic is teaming with Arcitecta for tackling the massive datasets used in life sciences. The two companies will showcase their joint solutions at the BioIT World conference this week in Boston. "Addressing the needs of the life sciences market with reliable data storage lies at the heart of the Spectra and Arcitecta relationship,” said Spectra CTO Matt Starr. “This joint solution enables customers to better manage their data and metadata by optimizing multiple storage targets, retrieving data efficiently and tracking content and resources.”