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Abstractions and Directives for Adapting Wavefront Algorithms to Future Architectures

Robert Searles from the University of Delaware gave this talk at PASC18. “Architectures are rapidly evolving, and exascale machines are expected to offer billion-way concurrency. We need to rethink algorithms, languages and programming models among other components in order to migrate large scale applications and explore parallelism on these machines. Although directive-based programming models allow programmers to worry less about programming and more about science, expressing complex parallel patterns in these models can be a daunting task especially when the goal is to match the performance that the hardware platforms can offer.”

Porting HPC Codes with Directives and OpenACC

In this video from ISC 2018, Michael Wolfe from describes how scientists can port their code to accelerated computing. “OpenACC is a user-driven directive-based performance-portable parallel programming model designed for scientists and engineers interested in porting their codes to a wide-variety of heterogeneous HPC hardware platforms and architectures with significantly less programming effort than required with a low-level model.”

Penguin Computing to Deploy Supercomputer at ICHEC in Ireland

Today Penguin Computing (a subsidiary of SMART Global Holdings) announced that it will deliver the new national supercomputer to the Irish Centre for High-End Computing (ICHEC) at the National University of Ireland (NUI) Galway. “With 11 supercomputers in the Top500 list and a bare-metal HPC Cloud service since 2009, we knew we could rely on Penguin Computing’s HPC expertise to address our needs in an innovative way.”

OpenACC Helps Scientists Port their code at the Center for Application Readiness (CARR)

In this video, Jack Wells from the Oak Ridge Leadership Computing Facility and Duncan Poole from NVIDIA describe how OpenACC enabled them to port their codes to the new Summit supercomputer. “In preparation for next-generation supercomputer Summit, the Oak Ridge Leadership Computing Facility (OLCF) selected 13 partnership projects into its Center for Accelerated Application Readiness (CAAR) program. A collaborative effort of application development teams and staff from the OLCF Scientific Computing group, CAAR is focused on redesigning, porting, and optimizing application codes for Summit’s hybrid CPU–GPU architecture.”

Podcast: Deep Learning for Scientific Data Analysis

In this NERSC News Podcast, Debbie Bard from NERSC describes how Deep Learning can help scientists accelerate their research. “Deep learning is enjoying unprecedented success in a variety of commercial applications, but it is also beginning to find its footing in science. Just a decade ago, few practitioners could have predicted that deep learning-powered systems would surpass human-level performance in computer vision and speech recognition tasks.”

ISC 2018: NVIDIA DGX-2 — The World’s Most Powerful AI System on Display

In this video, Satinder Nijjar from NVIDIA describes the new DGX-2 GPU supercomputer. “Experience new levels of AI speed and scale with NVIDIA DGX-2, the first 2 petaFLOPS system that combines 16 fully interconnected GPUs for 10X the deep learning performance. It’s powered by NVIDIA DGX software and a scalable architecture built on NVIDIA NVSwitch, so you can take on the world’s most complex AI challenges.”

NVIDIA Offers Framework to Solve AI System Challenges

At the recent NVIDIA GPU Technology Conference (GTC) 2018, Jensen Huang, NVIDIA President and CEO, during his presentation focused on a new framework designed to contextualize the key challenges using AI systems and delivering deep learning-based solutions. A new white paper sponsored by NVIDIA outlines these requirements — coined PLASTER.

Podcast: Evolving MPI for Exascale Applications

In this episode of Let’s Talk Exascale, Pavan Balaji and Ken Raffenetti describe their efforts to help MPI, the de facto programming model for parallel computing, run as efficiently as possible on exascale systems. “We need to look at a lot of key technical challenges, like performance and scalability, when we go up to this scale of machines. Performance is one of the biggest things that people look at. Aspects with respect to heterogeneity become important.”

HPE Teams with WekaIO for HPC and Machine Learning

In this video from the HPE booth at ISC 2018, Barbara Murphy from WekaIO describes how the company’s fast parallel file system for NVMe devices speeds HPC and Machine Learning workloads. “You invested in the best infrastructure to run your AI and data intensive applications, so don’t let data accessibility be the bottleneck to your productivity gains. To maximize your investments and resolve the GPU and CPU starvation problem, you need a shared file system that ensures data is available to the applications. WekaIO delivers all the bandwidth you need, so your applications never have to wait for data.”

One Stop Systems Showcases Composable Infrastructure for GPU Workloads at ISC 2018

In this video from ISC 2018, Jaan Mannik from One Stop Systems describes the company’s HPC systems and new composable infrastructure solutions. OneStop also showcased a wide array of its high-density NVIDIA GPU-based appliances, as well as showcase a live remote connection to one of its machine learning and HPC platforms. “OSS leads the market in external systems that increase a server’s performance in HPC applications, reducing cost and impact on data center infrastructure. These technology-hungry applications include AI (artificial intelligence), deep learning, seismic exploration, financial modeling, media and entertainment, security and defense.”