4. HERE ARE THE “TOP FIVE’ STORIES
HIGHLIGHTING WHAT’S HOT IN HPC AND AI
TOP 5
5. TOP 5
1. Why UIUC Built HPC Application Containers for NVIDIA GPU Cloud
2. Fujitsu Boosts RIKEN AI Supercomputer to 54 PetaFLOPS
3. More Power, Less Tower: AI May Make Aircraft Control Towers Obsolete
4. The Buck Stops – And Starts- Here for GPU Compute
5. Boston University Researchers use AI to Detect Kidney Disease
6. WHY UIUC BUILT HPC APPLICATION CONTAINERS FOR
NVIDIA GPU CLOUD
“Containers are a way of packaging up an application and
all of its dependencies in such a way that you can install
them collectively on a cloud instance or a workstation or a
compute node. And it doesn’t require the typical amount
of system administration skills and involvement to put one
of these containers on a machine. And within the container
image in a manner that’s roughly similar to what you have
in a virtual machine, the user can change anything they
want. So you have an entire sort of operating system
snapshot is what it looks like on the inside. So you can
customize the layout of the file system and do all kinds of
other things that would otherwise involve getting a lot of
permission and cooperation, particularly in large
computing installations.”
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VIDEO ARTICLE
7. FUJITSU BOOSTS RIKEN AI SUPERCOMPUTER TO 54
PETAFLOPS
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Fujitsu has performed a massive upgrade to RIKEN’s RAIDEN
supercomputer using NVIDIA DGX-1 servers outfitted with the
latest V100 Tesla GPUs.
RAIDEN was originally deployed in 2017 using 24 of NVIDIA’s
first-generation DGX-1 servers, each of which were powered
by eight P100 GPUs. Together, set of servers delivered four
half-precision petaflops for deep learning applications. With
the upgrade, those original servers were replaced with 54
DGX-1 boxes, using the newest V100 GPUs. Since the V100
has the special Tensor Core circuitry specifically designed for
neural network processing (125 teraflops of mixed precision
floating point operations per device), the upgraded system
will offer a whopping 54 petaflops of deep learning
performance.
ARTICLE
8. MORE POWER, LESS TOWER:
AI MAY MAKE AIRCRAFT CONTROL TOWERS OBSOLETE
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Airport control towers are an emblem of the
aviation industry. A Canadian company wants to
use its technology to make them a relic of the
past.
Airport buffs may mourn the change. But
Ontario-based Searidge Technologies believes its
reasoning is, um, well-grounded.
It believes AI-powered video systems can better
watch runways, taxiways and gate areas. By
“seeing” airport operations through as many as
200 cameras, there’s no need for the sightline
towers give air traffic controllers.
9. THE BUCK STOPS – AND STARTS – HERE FOR GPU
COMPUTE
We have done surveys of the HPC codes, and about 70 percent of
the processing cycles of the HPC centers is dominated by 15
different applications. This small number of applications
dominate compute time. We have been focused on accelerating
those applications first as well as making them run well. There
are hundreds of accelerated applications, but some of them are
just moving to GPUs and they are going to take a while. You do
have to know your workloads, and at every HPC center, all that
we ask is that they look at their applications and first of all
make sure they are on the most recent versions of the code,
many of which have been accelerated by GPUs. On average, if
you compare a server with four Volta GPUs against a best-in-class
server with two “Skylake” Xeon SP processors, the average speed
up across a basket of HPC applications is 20X. - Ian Buck
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ARTICLE
10. BOSTON UNIVERSITY RESEARCHERS USE AI TO DETECT
KIDNEY DISEASE
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Researchers at Boston University developed a deep
learning algorithm that can assess kidney disease
with better accuracy than trained pathologists.
Detecting kidney damage is of great importance, and
unlike many other diseases, symptoms often don’t
appear until the disease is very advanced. Getting
this diagnosis wrong can lead to a series of life-
threatening conditions.
“This rapid, scalable method can be deployable in
the form of software at the point of care, and holds
the potential for substantial clinical impact,
including augmenting clinical decision making for
nephrologists,” the team wrote in their research
paper.
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