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Video: NCSA’s Ed Seidel Testifies on the Networking and Information Technology Research and Development Program


In the video, Ed Seidel from NSCA testifies at a House hearing on the Networking and Information Technology Research and Development (NITRD) Program. NITRD provides a framework in which many Federal agencies come together to coordinate their networking and information technology (IT) research and development (R&D) efforts.

Video: How the SPARC M7 Builds Security into Silicon


“The SPARC M7 incorporates silicon-embedded advancements primarily in two areas: security and performance. First, the SPARC M7 accelerates data encryption through “cryptographic units” integrated in each of its 32 cores. And by incorporating very high-performance encryption in the chip, Fowler says, the M7 is able to not only secure data quickly but also devote substantial processor resources to additional projects, resources that otherwise would be occupied encrypting data at the software layer.”

Interview: Baidu Speeds Deep Learning with GPU Clusters

Chris Fougner, Baidu Research

“Deep neural networks are increasingly important for powering AI-based applications like speech recognition. Baidu’s research shows that adding GPUs to the data center makes deploying big deep neural networks practical at scale. Deep learning based technologies benefit from batching user requests in the data center, which requires a different software architecture than traditional web applications.”

Video: Debugging and Profiling Your HPC Applications


David Lecomber from Allinea Software presented this talk at the Argonne Training Program on Extreme-Scale Computing. “From climate modeling to astrophysics, from financial modeling to engine design, the power of clusters and supercomputers advances the frontiers of knowledge and delivers results for industry. Writing and deploying software that exploits that computing power is a demanding challenge – it needs to run fast, and run right. That’s where Allinea comes in.”

Panel Discussion: Extreme-Scale Numerical Algorithms and Software


“The FASTMathSciDAC Institute develops and deploys scalable mathematical algorithms and software tools for reliable simulation of complex physical phenomena and collaborates with application scientists to ensure the usefulness and applicability of FASTMath technologies. Our current research efforts are focused on developing a full range of technologies to improve the reliability, accuracy, and robustness of application simulation codes.”

Video: Introduction to the Yellowstone Supercomputer


In this video, Patrick Nichols from the Computational and Informational Systems Laboratory presents: Introduction to the Yellowstone Supercomputer. Yellowstone is NCAR’s 1.5-petaflops high-performance IBM iDataPlex cluster, which features 72,576 Intel Sandy Bridge processors and 144.6 TB of memory.

Video: Python for High Performance Computing


In this video from the recent Argonne Training Program on Extreme-Scale Computing, William Scullin from Argonne National Labs presents: Python for High Performance Computing.

Video: Supercomputing for Nuclear Fusion

Santiago Badia

In this video from the World Economic Forum, Santiago Badia from the Universitat Politècnica de Catalunya in Barcelona introduces some of the challenges of working to make safe, efficient nuclear fusion a reality by 2040.

Video: Cognitive Computing – Past and Present


“The Cognitive Era is the next step in the application of science to understand nature and improve the human condition. In that sense, it is a new chapter of a familiar story, and the controversy surrounding Artificial Intelligence is merely the latest example of the age-old debate between those who believe in progress and those who fear it. Within the scientific community —as opposed to the media and popular entertainment —the verdict is in. There is broad agreement on the importance of pursuing a cognitive future, along with recognition of the need to develop the technology responsibly.”

Bill Gropp Presents: MPI and Hybrid Programming Models

Bill Gropp

Bill Gropp presented this talk at the Argonne Training Program on Extreme-Scale Computing. “Where it is used as an alternative to MPI, OpenMP often has difficulty achieving the performance of MPI (MPI’s much-criticized requirement that the user directly manage data motion ensures that the programmer does in fact manage that memory motion, leading to improved performance). This suggests that other programming models can be productively combined with MPI as long as they complement, rather than replace, MPI.”