Read updates highlighting what’s hot in high performance computing, with this week's focused on the convergence of HPC and AI.

1. HPC TOP 5 STORIES
Weekly Insights into the World of
High Performance Computing

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

3. PROVING THAT AI IS THE FUTURE OF
SUPERCOMPUTING…

4. HERE ARE THE “TOP FIVE’ STORIES
HIGHLIGHTING WHAT’S HOT IN HPC AND AI
TOP 5

5. TOP 5
1. Scaling Deep Learning on an 18,000 GPU Supercomputer
2. UK to Launch Six Major HPC Centers
3. Deep Learning Driving Up Data Center Power Density
4. 3D Map of Earth’s Interior
5. Video: Computational Fluid Dynamics for Surgical Planning

6. SCALING DEEP LEARNING ON AN 18,000 GPU
SUPERCOMPUTER
It is one thing to scale a neural network on
a single GPU or even a single system with
four or eight GPUs. But it is another thing
entirely to push it across thousands of
nodes. Most centers doing deep learning
have relatively small GPU clusters for
training and certainly nothing on the order
of the Titan supercomputer at Oak Ridge
National Laboratory.
The emphasis on machine learning
scalability has often been focused on node
counts in the past for single-model runs.
This is useful for some applications, but as
neural networks become more integrated
into existing workflows, including those in
HPC, there is another way to consider
scalability.
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7. UK TO LAUNCH SIX MAJOR HPC CENTERS
2
ARTICLE
Six high performance computing centers will be
formally launched in the U.K. later this week
intended to provide wider access to HPC resources
to U.K. industry and academics. This expansion of
HPC resources and access to them is being funded
with £20 million from the Engineering and Physical
Sciences Research Council. The EPSRC plays a
somewhat similar role in the U.K. to the National
Science Foundation role in the U.S.
The centers are located at the universities of
Cambridge, Edinburgh, Exeter, and Oxford,
Loughborough University, and University College
London. According to today’s pre-launch
announcement, some of the centers will be
available free of charge to any EPSRC-supported
researcher, and some will give access to UK
industry. Some of the infrastructure is in place and
has been in use for a while.

8. DEEP LEARNING DRIVING UP DATA CENTER POWER
DENSITY
3
Few people on the planet know more about
building computers for Artificial Intelligence than
Rob Ober. As the top technology exec at NVIDIA’s
Accelerated Computing Group, he’s the chief
platform architect behind Tesla, the most
powerful GPU on the market for Machine
Learning, which is the most widespread type of AI
today.
GPUs, or Graphics Processing Units, take their
name from their original purpose, but their
applications today stretch far beyond that.
Supercomputer designers have found them ideal
for offloading huge chunks of workloads from
CPUs in the systems they build; they’ve also
proven to be super-efficient processors for a
Machine Learning approach called Deep Learning.EXPLORE

9. 3D MAP OF EARTH’S INTERIOR
4
A team of researchers led by Jeroen Tromp at
Princeton University used a GPU-accelerated
supercomputer to create a detailed 3D picture of
Earth’s interior.
“This is the first global seismic model where no
approximations — other than the chosen numerical
method — were used to simulate how seismic
waves travel through the Earth and how they sense
heterogeneities,” said Ebru Bozdag, a coprincipal
investigator of the project and an assistant
professor of geophysics at the University of Nice
Sophia Antipolis. “That’s a milestone for the
seismology community. For the first time, we
showed people the value and feasibility of running
these kinds of tools for global seismic imaging.”LEARN MORE

10. COMPUTATIONAL FLUID DYNAMICS FOR SURGICAL
PLANNING
5
In this video, Todd Raeker, Research Technology
Consultant at the University of Michigan shares how a
group of 50 researchers at University of Michigan are
using GPUs and OpenACC to accelerate the codes for
their data-driven physics simulations.
“The current versions of the codes use MPI and
depend on finer and finer meshes for higher accuracy
which are computationally demanding. To overcome
the demands, the team has gained access to their
state-of-the-art cluster equipped with POWER CPUs
and Tesla P100 GPUs — and turning to OpenACC and
machine learning to accelerate their science. This has
allowed them to spend the least resources on
programming, and effectively utilize available
compute resources.”
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11. HOW CAN HPC IMPACT YOUR BUSINESS?
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