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Rock Stars of HPC: James Phillips

Recipient of a Gordon Bell Award in 2002, James Phillips has been a full-time research programmer for almost 20 years. Since 1998, he has been the lead developer of NAMD, a parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems that scales beyond 200,000 cores, and is undoubtedly a Rock Star of HPC.

Echelon Code on Minksy Servers Sets Record for Oil & Gas Simulation

IBM and Stone Ridge Technology have announced a new performance milestone in reservoir simulation that will improve efficiency and lower the cost of production. Working with Nvidia, the companies reported that they had beat previous results using one-tenth the power and 1/100th of the space by employing GPUs alongside a GPU optimized code from Stone Ridge Technology called ECHELON.

Mellanox InfiniBand Delivers up to 250 Percent Higher ROI for HPC

Today Mellanox announced that EDR 100Gb/s InfiniBand solutions have demonstrated from 30 to 250 percent higher HPC applications performance versus Omni-Path. These performance tests were conducted at end-user installations and Mellanox benchmarking and research center, and covered a variety of HPC application segments including automotive, climate research, chemistry, bioscience, genomics and more.

Introduction to Parallel Programming with OpenACC

“This is the first in a series of short videos to introduce you to parallel programming with OpenACC and the PGI compilers, using C++ or Fortran. You will learn by example how to build a simple example program, how to add OpenACC directives, and to rebuild the program for parallel execution on a multicore system. To get the most out of this video, you should download the example programs and follow along on your workstation.”

HPC Workflows Using Containers

“In this talk we will discuss a workflow for building and testing Docker containers and their deployment on an HPC system using Shifter. Docker is widely used by developers as a powerful tool for standardizing the packaging of applications across multiple environments, which greatly eases the porting efforts. On the other hand, Shifter provides a container runtime that has been specifically built to fit the needs of HPC. We will briefly introduce these tools while discussing the advantages of using these technologies to fulfill the needs of specific workflows for HPC, e.g., security, high-performance, portability and parallel scalability.”

Rock Stars of HPC: John Stone

This Rock Stars of HPC series is about the men and women who are changing the way the HPC community develops, deploys, and operates the supercomputers and social and economic impact of their discoveries. “As the lead developer of the VMD molecular visualization and analysis tool, John Stone’s code is used by more than 100,000 researchers around the world. He’s also a CUDA Fellow, helping to bring HPC to the masses with accelerated computing. In this way and many others, John Stone is certainly one of the Rock Stars of HPC.”

Baidu Deep Learning Service adds Latest NVIDIA Pascal GPUs

“Baidu and NVIDIA are long-time partners in advancing the state of the art in AI,” said Ian Buck, general manager of Accelerated Computing at NVIDIA. “Baidu understands that enterprises need GPU computing to process the massive volumes of data needed for deep learning. Through Baidu Cloud, companies can quickly convert data into insights that lead to breakthrough products and services.”

Podcast: How AI Can Improve the Diagnosis and Treatment of Diseases

In this AI Podcast, Mark Michalski from the Massachusetts General Hospital Center for Clinical Data Science discusses how AI is being used to advance medicine. “Medicine — particularly radiology and pathology — have become more data-driven. The Massachusetts General Hospital Center for Clinical Data Science — led by Mark Michalski — promises to accelerate that, using AI technologies to spot patterns that can improve the detection, diagnosis and treatment of diseases.”

Deep Learning on the SaturnV Cluster

“The basic idea of deep learning is to automatically learn to represent data in multiple layers of increasing abstraction, thus helping to discover intricate structure in large datasets. NVIDIA has invested in SaturnV, a large GPU-accelerated cluster, (#28 on the November 2016 Top500 list) to support internal machine learning projects. After an introduction to deep learning on GPUs, we will address a selection of open questions programmers and users may face when using deep learning for their work on these clusters.”

A PCIe Congestion-Aware Performance Model for Densely Populated Accelerator Servers

“MeteoSwiss, the Swiss national weather forecast institute, has selected densely populated accelerator servers as their primary system to compute weather forecast simulation. Servers with multiple accelerator devices that are primarily connected by a PCI-Express (PCIe) network achieve a significantly higher energy efficiency. Memory transfers between accelerators in such a system are subjected to PCIe arbitration policies. In this paper, we study the impact of PCIe topology and develop a congestion-aware performance model for PCIe communication. We present an algorithm for computing congestion factors of every communication in a congestion graph that characterizes the dynamic usage of network resources by an application.”