Parameter Encoding on FPGAs Boosts Neural Network Efficiency

The key to creating more efficient neural network models is rooted in trimming and refining the many parameters in deep learning models without losing accuracy. Much of this work is happening on the software side, but devices like FPGAs that can be tuned for trimmed parameters are offering promising early results for implementation.

A team from UC San Diego has created a reconfigurable clustering approach to deep neural networks that encodes the parameters the network according the accuracy requirements and limitations of the platform—which are often bound by memory access bandwidth. Encoding the trimmed parameters in an FPGA resulted in …

Parameter Encoding on FPGAs Boosts Neural Network Efficiency was written by Nicole Hemsoth at The Next Platform.

A High Performance Hiatus

The Next Platform will be on summer holiday for the coming week.

We will return to our normal publishing schedule on Monday, July 10^th.

For our U.S. readership, we hope you have an excellent Independence Day holiday week and for our many readers outside the states, here’s hoping you find time to relax and enjoy great weather.

Thanks as always for reading, and for our sponsors, we appreciate your support.

Cheers,

Timothy Prickett Morgan, Nicole Hemsoth

Co-Founders, Co-Editors, The Next Platform …

A High Performance Hiatus was written by Nicole Hemsoth at The Next Platform.

Momentum is Building for ARM in HPC

2011 marked ARM’s first step into the world of HPC with the European Mont-Blanc project. The premise was simple: leverage the energy efficiency of ARM-based mobile designs for high performance computing applications.

Unfortunately, making the leap from the mobile market to HPC was not an easy feat. Long time players in this space, such as Intel and IBM, hold home field advantage: that of legacy software. HPC-optimized libraries, compilers and applications were already present for these platforms. This was not, however, the case for ARM. Early adopters had to start, largely from scratch, porting and building an ecosystem with a …

Momentum is Building for ARM in HPC was written by Nicole Hemsoth at The Next Platform.

A Deep Learning Performance Lens for Low Precision Inference

Few companies have provided better insight into how they think about new hardware for large-scale deep learning than Chinese search giant, Baidu.

As we have detailed in the past, the company’s Silicon Valley Research Lab (SVAIL) in particular has been at the cutting edge of model development and hardware experimentation, some of which is evidenced in their publicly available (and open source) DeepBench deep learning benchmarking effort, which allowed users to test different kernels across various hardware devices for training.

Today, Baidu SVAIL extended DeepBench to include support for inference as well as expanded training kernels. Also of …

A Deep Learning Performance Lens for Low Precision Inference was written by Nicole Hemsoth at The Next Platform.

U.S. Military Sees Future in Neuromorphic Computing

The novel architectures story is still shaping out for 2017 when it comes machine learning, hyperscale, supercomputing and other areas.

From custom ASICs at Google, new uses for quantum machines, FPGAs finding new routes into wider application sets, advanced GPUs primed for deep learning, hybrid combinations of all of the above, it is clear there is serious exploration of non-CMOS devices. When the Department of Energy in the U.S. announced its mission to explore novel architectures, one of the clear candidates for investment appeared to be neuromorphic chips—efficient pattern matching devices that are in development at Stanford (NeuroGrid), The …

U.S. Military Sees Future in Neuromorphic Computing was written by Nicole Hemsoth at The Next Platform.

Machine Learning and the Language of the Brain

For years, researchers have been trying to figure out how the human brain organizes language – what happens in the brain when a person is presented with a word or an image. The work has academic rewards of its own, given the ongoing push by researchers to better understand the myriad ways in which the human brain works.

At the same time, ongoing studies can help doctors and scientists learn how to better treat people with aphasia or other brain disorders caused by strokes, tumors or trauma that impair a person’s ability to communicate – to speak, read, write and …

Machine Learning and the Language of the Brain was written by Nicole Hemsoth at The Next Platform.

Exascale on the Far Horizon for Cash-Strapped Oil and Gas

All the compute power in the world is useless against code that cannot scale. And neither compute or code can be useful if growing data for simulations cannot be collected and managed.

But ultimately, none of this is useful at all if the industry that needs these HPC resources is having more trouble than ever acquiring them. It comes as no surprise that the national labs and major research centers will be the first to get exaflop-capable systems, but in a normal market (like the one oil and gas knew not long ago) these machines would be relatively quickly followed …

Exascale on the Far Horizon for Cash-Strapped Oil and Gas was written by Nicole Hemsoth at The Next Platform.

The Biggest Shift in Supercomputing Since GPU Acceleration

For years, the pace of change in large-scale supercomputing neatly tracked with the curve of Moore’s Law. As that swell flattens, and as the competitive pressure ticks up to build productive exascale supercomputers in the next few years, HPC has been scrambling to find the silver bullet architecture to reach sustained exascale performance. And as it turns out, there isn’t one.

But there is something else—something few saw coming three years ago, has less to do with hardware than it does a shift in how we approach massive-scale simulations, and is happening so fast that too-far-ahead-of-time procurements are …

The Biggest Shift in Supercomputing Since GPU Acceleration was written by Nicole Hemsoth at The Next Platform.

Knights Landing Can Stand Alone—But Often Won’t

It is a time of interesting architectural shifts in the world of supercomputing but one would be hard-pressed to prove that using the mid-year list of the top 500 HPC systems in the world. We are still very much in an X86 dominated world with the relatively stable number of accelerated systems to spice the numbers, but there are big changes afoot—as we described in depth when the rankings were released this morning.

This year, the list began to lose one of its designees in the list of “accelerator/offload” architectures as the Xeon Phi moves from offload model to host …

Knights Landing Can Stand Alone—But Often Won’t was written by Nicole Hemsoth at The Next Platform.

Is HPE’s “Machine” the Novel Architecture to Fit Exascale Bill?

The exascale effort in the U.S. got a fresh injection with R&D funding set to course through six HPC vendors to develop scalable, reliable, and efficient architectures and components for new systems in the post-2020 timeframe.

However, this investment, coming rather late in the game for machines that need hit sustained exaflop performance in a 20-30 megawatt envelope in less than five years, raises a few questions about potential shifts in what the Department of Energy (DoE) is looking for in next-generation architectures. From changes in the exascale timeline and new focal points on “novel architectures” to solve exascale challenges, …

Is HPE’s “Machine” the Novel Architecture to Fit Exascale Bill? was written by Nicole Hemsoth at The Next Platform.

Tackling Computational Fluid Dynamics in the Cloud

Cloud computing isn’t just for running office productivity software or realising your startup idea. It can support high-performance computing (HPC) applications that crunch through large amounts of data to produce actionable results.

Using elastic cloud resources to process data in this way can have a real business impact. What might one of these applications look like, and how could the cloud support it?

Let’s take buildings as an example. London’s ‘Walkie Talkie’ skyscraper has suffered from a bad rap of late. First it gave the term ‘hot wheels’ a whole new meaning, melting cars by inadvertently focusing the sun’s rays …

Tackling Computational Fluid Dynamics in the Cloud was written by Nicole Hemsoth at The Next Platform.

American HPC Vendors Get Government Boost for Exascale R&D

The US Department of Energy – and the hardware vendors it partners with – are set to enliven the exascale effort with nearly a half billion dollars in research, development, and deployment investments.  The push is led by the DoE’s Exascale Computing Project and its extended PathForward program, which was announced today.

The future of exascale computing in the United States has been subjected to several changes—some public, some still in question (although we received a bit more clarification and we will get to in a moment). The timeline for delivering an exascale capability system has also shifted, with most …

American HPC Vendors Get Government Boost for Exascale R&D was written by Nicole Hemsoth at The Next Platform.

Stretching the Business of Tape Storage to Extreme Scale

IPOs and major investments in storage startups are one thing, but when it comes to a safe tech company investment, all bets are still on tape.

The rumors of tape’s death are greatly exaggerated, but there have been some changes to the market. While the number of installed sites might be shrinking for long-time tape storage maker, SpectraLogic, the installation sizes of its remaining customers keeps growing, which produces a nice uptick in revenue for the company, according to its CTO, Matt Starr.

This makes sense since the relatively smaller backups and archives make better performance sense on disk—and many …

Stretching the Business of Tape Storage to Extreme Scale was written by Nicole Hemsoth at The Next Platform.

FPGAs, OpenHMC Push SKA HPC Processing Capabilities

Astronomy is the oldest research arena, but the technologies required to process the massive amount of data created from radio telescope arrays represents some of the most bleeding-edge research in modern computer science.

With an exabyte of data expected to stream off the Square Kilometer Array (SKA), teams from both the front and back ends of the project have major challenges ahead. One “small” part of that larger picture of seeing farther into the universe than ever before is moving the data from the various distributed telescopes into a single unified platform and data format. This means transferring data from …

FPGAs, OpenHMC Push SKA HPC Processing Capabilities was written by Nicole Hemsoth at The Next Platform.

Knights Landing System Development Targets Dark Matter Study

Despite the best efforts of leading cosmologists, the nature of dark energy and dark matter – which comprise approximately 95% of the total mass-energy content of the universe – is still a mystery.

Dark matter remains undetected even with all the different methods that have been employed so far to directly find it.  The origin of dark energy is one of the greatest puzzles in physics. Cosmologist Katrin Heitmann, PI of an Aurora Early Science Program effort at the Argonne Leadership Computing Facility (ALCF) and her team are conducting research to shed some light on the dark universe.

“The reach …

Knights Landing System Development Targets Dark Matter Study was written by Nicole Hemsoth at The Next Platform.

Early Benchmarks on Argonne’s New Knights Landing Supercomputer

We are heading into International Supercomputing Conference week (ISC) and as such, there are several new items of interest from the HPC side of the house.

As far as supercomputer architectures go for mid-2017, we can expect to see a lot of new machines with Intel’s Knights Landing architecture, perhaps a scattered few finally adding Nvidia K80 GPUs as an upgrade from older generation accelerators (for those who are not holding out for Volta with NVlink ala the Summit supercomputer), and of course, it all remains to be seen what happens with the Tianhe-2 and Sunway machines in China in …

Early Benchmarks on Argonne’s New Knights Landing Supercomputer was written by Nicole Hemsoth at The Next Platform.

Python Coils Around FPGAs for Broader Accelerator Reach

Over the last couple of years, much work has been shifted into making FPGAs more usable and accessible. From building around OpenCL for a higher-level interface to having reconfigurable devices available on AWS, there is momentum—but FPGAs are still far from the grip of everyday scientific and technical application developers.

In an effort to bridge the gap between FPGA acceleration and everyday domain scientists who are well-versed in using the common scripting language, a team from the University of Southern California has created a new platform for Python-based development that abstracts the complexity of using low-level approaches (HDL, Verilog). “Rather …

Python Coils Around FPGAs for Broader Accelerator Reach was written by Nicole Hemsoth at The Next Platform.

Machine Learning on Stampede2 Supercomputer to Bolster Brain Research

In our ongoing quest to understand the human mind and banish abnormalities that interfere with life we’ve always drawn upon the most advanced science available. During the last century, neuroimaging – most recently, the Magnetic Resonance Imaging scan (MRI) – has held the promise of showing the connection between brain structure and brain function.

Just last year, cognitive neuroscientist David Schnyer and colleagues Peter Clasen, Christopher Gonzalez, and Christopher Beevers published a compelling new proof of concept in Psychiatry Research: Neuroimaging. It suggests that machine learning algorithms running on high-performance computers to classify neuroimaging data may deliver the most …

Machine Learning on Stampede2 Supercomputer to Bolster Brain Research was written by Nicole Hemsoth at The Next Platform.

HPC Center NERSC Eases Path to Optimization at Scale

The National Energy Research Scientific Computing Center (NERSC) application performance team knows that for many users, “optimization is hard.” They’ve thought a lot about how to distill the application optimization process for users in a way that would resonate with them.

One of the analogies they use is the “Ant Farm.” Optimizing code is like continually “running a lawnmower over a lawn to find and cut-down the next tallest blade of grass,” where the blade of grass is analogous to a code bottleneck that consumes the greatest amount of runtime. One of the challenges is that each bottleneck …

HPC Center NERSC Eases Path to Optimization at Scale was written by Nicole Hemsoth at The Next Platform.

One Programming Model To Support Them All

Many hands make light work, or so they say. So do many cores, many threads and many data points when addressed by a single computing instruction. Parallel programming – writing code that breaks down computing problems into small parts that run in unison – has always been a challenge. Since 2011, OpenACC has been gradually making it easier.  OpenACC is a de facto standard set of parallel extensions to Fortran, C and C++ designed to enable portable parallel programming across a variety of computing platforms.

Compilers, which are used to translate higher-level programming languages into binary executables, first appeared in …

One Programming Model To Support Them All was written by Nicole Hemsoth at The Next Platform.