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Video: Reliving the First Moon Landing with NVIDIA RTX real-time Ray Tracing

In this video, Apollo 11 astronaut Buzz Aldrin looks back at the first moon landing with help from a reenactment powered by NVIDIA RTX GPUs with real-time ray tracing technology. “The result: a beautiful, near-cinematic depiction of one of history’s great moments. That’s thanks to NVIDIA RTX GPUs, which allowed our demo team to create an interactive visualization that incorporates light in the way it actually works, giving the scene uncanny realism.”

NSF Funds $10 Million for ‘Expanse’ Supercomputer at SDSC

SDSC has been awarded a five-year grant from the NSF valued at $10 million to deploy Expanse, a new supercomputer designed to advance research that is increasingly dependent upon heterogeneous and distributed resources. “As a standalone system, Expanse represents a substantial increase in the performance and throughput compared to our highly successful, NSF-funded Comet supercomputer. But with innovations in cloud integration and composable systems, as well as continued support for science gateways and distributed computing via the Open Science Grid, Expanse will allow researchers to push the boundaries of computing and answer questions previously not possible.”

Brent Gorda from Arm looks back at ISC 2019

In this special guest feature, Brent Gorda from Arm shares his impressions of ISC 2019 in Frankfurt. “From the perspective of Arm in HPC, it was an excellent event with several high-profile announcements that caught everyone’s attention. The Arm ecosystem was well represented with our partners visible on the show floor and around town.”

ISC 2019 Student Cluster Competition: Day-by-Day Drama, Winners Revealed!

In this special guest feature, Dan Olds from OrionX continues his first-hand coverage of the Student Cluster Competition at the recent ISC 2019 conference. “The ISC19 Student Cluster Competition in Frankfurt, Germany had one of the closest and most exciting finishes in cluster competition history. The overall winner was decided by just over two percentage points and the margin between third and fourth place was less than a single percentage point.”

NVIDIA DGX-Ready Program Goes Global

Deploying AI at scale can be an extreme challenge for data centers. To ease the process, NVIDIA has expanded its DGX-Ready Data Center Program to 19 validated partners around the world. “DGX-Ready Data Center partners help companies access modern data center facilities for their AI infrastructure. They offer world-class facilities to host DGX AI compute infrastructure, giving more organizations access to AI-ready data center facilities while saving on capital expenditures and keeping operational costs low.”

Video: Verne Global joins NVIDIA DGX-Ready Program as HPC & AI Colocation Partner

In this video, Bob Fletcher from Verne Global describes advantages the HPC cloud provider offers through the NVIDIA DGX Ready Data Center program. “Enterprises and research organizations seeking to leverage the NVIDIA DGX-2 System – the world’s most powerful AI system – now have the option to deploy their AI infrastructure using a cost-effective Op-Ex solution in Verne Global’s HPC-optimized campus in Iceland, which utilizes 100 percent renewable energy and relies on one of the world’s most reliable and affordable power grids.”

Google Cloud and NVIDIA Set New Training Records on MLPerf v0.6 Benchmark

Today the MLPerf effort released results for MLPerf Training v0.6, the second round of results from their machine learning training performance benchmark suite. MLPerf is a consortium of over 40 companies and researchers from leading universities, and the MLPerf benchmark suites are rapidly becoming the industry standard for measuring machine learning performance. “We are creating a common yardstick for training and inference performance,” said Peter Mattson, MLPerf General Chair.

The Challenges of Updating Scientific Codes for New HPC Architectures

In this video from PASC19 in Zurich, Benedikt Riedel from the University of Wisconsin describes the challenges researchers face when it comes to updating their scientific codes for new HPC architectures. After that he describes his work on the IceCube Neutrino Observatory.

Video: Data-Centric Parallel Programming

In this slidecast, Torsten Hoefler from ETH Zurich presents: Data-Centric Parallel Programming. “To maintain performance portability in the future, it is imperative to decouple architecture-specific programming paradigms from the underlying scientific computations. We present the Stateful DataFlow multiGraph (SDFG), a data-centric intermediate representation that enables separating code definition from its optimization.”

ISC19 Student Cluster Competition: LINs Packed & Conjugates Gradient-ed

In this special guest feature, Dan Olds from OrionX shares first-hand coverage of the Student Cluster Competition at the recent ISC 2019 conference. “The benchmark results from the recently concluded ISC19 Student Cluster Competition have been compiled, sliced, diced, and analyzed senseless. As you cluster comp fanatics know, this year the student teams are required to run LINPACK, HPCG, and HPCC as part of the ISC19 competition.”