HPC Top 5 StoriesWeekly Insights into the World of High Performance Computing

HPC AND AI HAVE PAVED THE WAY FOR GROUNDBREAKING DISCOVERIES IN SCIENCE, MEDICINE, AND OTHER FIELDS…

PROVING THAT AI IS THE FUTURE OF SUPERCOMPUTING…

HERE ARE THE “TOP FIVE” STORIESHIGHLIGHTING WHAT’S HOT IN HPC AND AI

TOP 5

TOP 5

1. Tokyo Tech to Build Japan’s Fastest AI Supercomputer Using NVIDIA’s Accelerated Computing Platform

2. Deep Learning & HPC: New Challenge for Large Scale Computing

3. What is a GPU and Why do I Care? A Businessperson’s Guide

4. Brain Trust: How AI is Helping Surgeons Improve Tumor Diagnosis

5. Accelerating the Forefront of Membrane Transport Research for Drug Design

TOKYO TECH TO BUILD JAPAN'S FASTEST AI SUPERCOMPUTER USING NVIDIA PASCAL GPUS

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Tokyo Institute of Technology today announced plans to create Japan’s fastest AI supercomputer, built on NVIDIA’s accelerated computing platform.

The new system, known as TSUBAME3.0, is expected to deliver more than two times the performance of its predecessor, TSUBAME2.5. It will use Pascal-based Tesla P100 GPUs, which are nearly three times as efficient as their predecessors, to reach an expected 12.2 petaflops of double precision performance. That would rank it among the world’s 10 fastest systems according to the latest TOP500 list, released in November.

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DEEP LEARNING & HPC: NEW CHALLENGES FOR LARGE SCALE COMPUTING

“In recent years, major breakthroughs were achieved in different fields using deep learning. From image segmentation, speech recognition or self-driving cars, deep learning is everywhere. Performance of image classification, segmentation, localization have reached levels not seen before thanks to GPUs and large scale GPU-based deployments, leading deep learning to be a first class HPC workload. In this talk, after a short introduction to Deep Neural Networks on GPUs, we will present NVIDIA’s platform for deep learning and how new advances in hardware and software integrate in large-scale computing environments.”

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WHAT IS A GPU AND WHY DO I CARE? A BUSINESSPERSON’S GUIDE

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Well, GPUs are constructed differently than CPUs. They are not nearly as versatile, but unlike CPUs they actually boast thousands of cores - which as we will find shortly is particularly important when it comes to dealing with large datasets. Since GPUs are single-mindedly designed around maximizing parallelism, the transistors that Moore’s Law grants chipmakers with every process shrink is translated directly into more cores, meaning GPUs are increasing their processing power by at least 40% per year, allowing them to keep pace with the growing deluge of data.

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BRAIN TRUST: HOW AI IS HELPING SURGEONS IMPROVE TUMOR DIAGNOSIS

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Artificial intelligence could help doctors diagnose brain tumors more quickly and more accurately, according to a new study by researchers at the University of Michigan Medical School and Harvard University.

“Our goal is to develop an algorithm that approaches the performance of a neuropathologist at diagnosis during an operation,” said Dr. Daniel Orringer, first author of the study in Nature Biomedical Engineering and an assistant professor of neurosurgery at Michigan Medicine.BLOG

ACCELERATING THE FOREFRONT OF MEMBRANE TRANSPORT RESEARCH FOR DRUG DESIGN

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GROMACS is a popular HPC application for molecular dynamics simulations. The GPU-accelerated version of GROMACS offloads heavy nonbonded force calculations to the GPU while concurrently using the CPU for bonded force calculations and lattice summation (PME). This optimization uses all-new algorithms that have been purpose-built and optimized for SIMD/streaming architectures, as well as support for parallel CPU/GPU calculations. It supports systems with single or multiple GPUs that have the CUDA development libraries installed.

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