Europe’s Fastest Supercomputer to Get Pascal GPU Upgrade

By Tiffany Trader and John Russell

April 6, 2016

Already Europe’s fastest supercomputer at 7.8 petaflops, the Piz Daint (hybrid CPU/GPU Cray XC30) at the Swiss National Computing Center (CSCS) will double its performance with a massive upgrade that involves switching to NVIDIA’s newest Pascal GPU architecture and merging with Piz Dora (Cray XC40), a smaller CPU-based machine. The announcement was made at GTC16 yesterday. Last November Piz Daint placed seventh on the TOP500 list.

Plans call for 5,200 NVIDIA K20xs to be replaced by 4,500 Pascal GPUs – which version hasn’t been decided. Also, the Intel processors will be upgraded from Sandy Bridge to Haswell architecture. When completed, the new combined system, all on a single fabric, will keep the Piz Daint name and provide users with two types of compute nodes: hybrid CPU-GPU and CPU-only nodes. Although slightly reduced in physical size, Piz Daint will be more powerful and flexible allowing simulations or data analyses to be scaled to a few nodes or thousands of nodes.

“We are taking advantage of NVIDIA GPUs to significantly accelerate simulations in such diverse areas as cosmology, materials science, seismology and climatology,” said Thomas Schulthess, professor of computational physics at ETH Zurich and director of CSCS. “Tesla accelerators represent a leap forward in computing, allowing our researchers to solve larger, more complex problems that are currently out of reach in a host of fields.”

Pascal GPUs feature a number of breakthrough technologies, including second-generation High Bandwidth Memory (HBM2) that delivers three times higher bandwidth than the previous generation architecture, and 16nm FinFET technology for unprecedented energy efficiency.

NVIDIA Tesla P100 frontPiz Daint will also incorporate Cray’s DataWarp technology. DataWarp’s so-called Burst Buffer mode quadruples the effective bandwidth for long-term storage; in other words, data is input to and output from storage far more quickly. It paves the way for analyzing millions of small, unstructured files. Consequently, Piz Daint will be able to transfer initial results to a specialized area of the supercomputer for analysis while calculations are still under way.

The upgraded machine will help CSCS carry out its mission of tackling grand challenge science as well as critical applied research. Piz Daint will be used to analyze data from the Large Hadron Collider at CERN, to accelerate research on the Human Brain Project’s High Performance Analytics and Computing Platform, and to continue its work in meteorology and climatology among other domain areas, including deep learning — which was of course a highlight of the NVIDIA event.

“Today a lot of the machine learning work [at ETH Zurich] is happening on workstations and I think the researchers are only now starting to realize that they can actually do this at much bigger scale on our supercomputers,” said Schulthess.

Schulthess bulleted out what he thought were the three were the most important advantages of upgrading to the Pascal architecture and combining the two systems:

  1. Memory Bandwidth. He expects a substantial memory performance increase. “Exactly how big a boost, we will have to find out — probably NVIDIA doesn’t even know yet, but we do expect a big boost on the memory bandwidth. That’s really important because many applications on the GPU are memory bandwidth bound.”
  1. Pascal-Haswell Duo. “The combination of Pascal and Haswell versus K20x and Sandy Bridge is important [now] that we have PCIe Gen3. Imagine you have a job distributed over the GPU memory — a weather code or a climate code, [for example] over the GPU memory of many nodes. Now there is no bottleneck. The GPUs talk to each other with a similar bandwidth. Before the piece between the CPU and the GPU was slow and now the bottleneck is gone.”
  1. Overall Performance. “Pascal is higher performance. I expect that this combination of much better memory bandwidth and faster performance will increase the throughput of the system. And we will open the system to new applications with all these new cool developments that we have today, all these libraries that are coming out of the deep neural network side. Pascal will enable a lot of this.”

All netted out, Schulthess is confident Piz Daint will double performance for both compute and memory bound applications. “We’re not talking about FLOPS; we’re talking about application performance,” he said.

TOP500 the list graphicNot surprisingly, CSCS will again run the LINPACK benchmark on Piz Daint, according to Schulthess, in part for the high profile all supercomputer centers desire but equally because, “LINPACK is very, very good at finding out if there are any hardware problems. It was good last time and I’m sure it will be good for that this time.”

It’s not yet clear how energy efficient the new system will be, but Schulthess thinks it won’t be worse and may be better.

“This whole FLOPS per watt and FLOPS per second is very narrow view of looking at the performance of a system. You have to look at time-to-solution of applications and you have to look at energy-to-solution of applications. In a sense what you’ve want – and I’ve written this in a number of papers already – is for the time-to-solution to be good enough,” he said.

A good example, he noted, are weather forecasts, which need to be completed as quickly as practical so as to make them most useful. “At some point when the time-to-solution is good enough, then you want to really minimize energy to solution (not FLOPS-per-watt),” he agreed.

CSCS is exploring the use of Intel’s forthcoming Xeon Phi, but isn’t ready to comment as the work with Intel is ongoing. Software development is another a major investment area, said Schulthess, “much more important than the hardware. We will actually double up in the future with our investments.” Predictably, CSCS is “looking at everything, also ARM – but that is a whole separate conversation.” Indeed.

Notably, the merging of Piz Dora into Piz Daint opens up tremendous flexibility and is in keeping with the growing trend to create unified platforms able to handle big data analytics as well as traditional modeling and simulation.

For example, one can pre-process data and then scale the simulation up while the data is always on the same system.

“If we need GPU-acceleration for simulations but the CPUs for pre-processing, we move the data from the pre-processing side to the GPU-accelerated side. So you move data between partitions, but you’re doing this per node, at 10 gigabytes-per-second, which is much higher than I/O bandwidth if you go through the disks. We’ll have very high performance for the whole workflow and make things more convenient for the scientists,” said Schulthess.

What’s more, the incorporation of big data analytics tools and practices can help science adopt new approaches. “It’s one thing to bring the data analytics on the systems, but to me there is another very important benefit to the HPC community. The data analytics community is used to a different type of software environment — they like to use Python and SPARK, and in real-time not batches. If we’re able to get supercomputers to run Python and even SPARK, we make them much more usable also to the traditional scientific computing community.”

He cited CSCS work on climate and meteorology as an example, “There’s no reason you wouldn’t want climate scientists to write their models in Python rather than Fortran in the future. Their productivity could go up [significantly] on model development. On an old-style supercomputer, you don’t want to talk about those things. But thanks to the whole data science pressure, we’re creating a software environment that’s much more usable for computational scientists. To me, that’s almost as interesting as the deep learning stuff – enhancing productivity of scientists.”

Turning to the rise of container technology in high-end HPC, perhaps best illustrated by the Docker-Shifter effort at NERSC, Schulthess said CSCS was working with NVIDIA to expose the GPUs in Docker.

Schulthess predicts the revamped Piz Daint will be up and fully running in a year or so, “Our requirements are very high and we are not going to cut corners, but once that is done, moving applications from today’s Piz Daint to the new system, they will just fly — I don’t expect any issues there.” A key reason is Pascal GPUs are backwards compatible. In the words of NVIDIA, “It’s all CUDA; you can use the same application you had five years ago and it just scales up.”

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industy updates delivered to you every week!

San Diego Supercomputer Center to Welcome ‘Expanse’ Supercomputer in 2020

July 18, 2019

With a $10 million dollar award from the National Science Foundation, San Diego Supercomputer Center (SDSC) at the University of California San Diego is procuring a new supercomputer, called Expanse, to be deployed next Read more…

By Staff report

Informing Designs of Safer, More Efficient Aircraft with Exascale Computing

July 18, 2019

During the process of designing an aircraft, aeronautical engineers must perform predictive simulations to understand how airflow around the plane impacts flight characteristics. However, modeling the complexities and su Read more…

By Rob Johnson

How Fast is Your Rubik Solver; This One’s Probably Faster

July 18, 2019

In the race to solve Rubik’s Cube, the time-to-finish keeps shrinking. This year Philipp Weyer from Germany won the 10th World Cube Association (WCA) Championship held in Melbourne, Australia, with a 6.74-second perfo Read more…

By John Russell

HPE Extreme Performance Solutions

Bring the Combined Power of HPC and AI to Your Business Transformation

A growing number of commercial businesses are implementing HPC solutions to derive actionable business insights, to run higher performance applications and to gain a competitive advantage. Read more…

IBM Accelerated Insights

Smarter Technology Revs Up Red Bull Racing

In 21st century business, companies that effectively leverage their information resources – thrive. As it turns out, the same is true in Formula One racing. Read more…

Intel Debuts Pohoiki Beach, Its 8M Neuron Neuromorphic Development System

July 17, 2019

Neuromorphic computing has received less fanfare of late than quantum computing whose mystery has captured public attention and which seems to have generated more efforts (academic, government, and commercial) but whose Read more…

By John Russell

Informing Designs of Safer, More Efficient Aircraft with Exascale Computing

July 18, 2019

During the process of designing an aircraft, aeronautical engineers must perform predictive simulations to understand how airflow around the plane impacts fligh Read more…

By Rob Johnson

Intel Debuts Pohoiki Beach, Its 8M Neuron Neuromorphic Development System

July 17, 2019

Neuromorphic computing has received less fanfare of late than quantum computing whose mystery has captured public attention and which seems to have generated mo Read more…

By John Russell

Goonhilly Unveils New Immersion-Cooled Platform, Doubles Down on Sustainability Mission

July 16, 2019

Goonhilly Earth Station has opened its new datacenter – an enhancement to its existing tier 3 facility – in Cornwall, England, touting an ambitious commitme Read more…

By Oliver Peckham

ISC19 Cluster Competition: Application Results, Finally!

July 15, 2019

Our exhaustive coverage of the ISC19 Student Cluster Competition continues as we discuss the application scores below. While the scores were typically high, som Read more…

By Dan Olds

Nvidia Expands DGX-Ready AI Program to 19 Countries

July 11, 2019

Nvidia’s DGX-Ready Data Center Program, announced in January and designed to provide colo and public cloud-like options to access the company’s GPU-powered Read more…

By Doug Black

Argonne Team Makes Record Globus File Transfer

July 10, 2019

A team of scientists at Argonne National Laboratory has broken a data transfer record by moving a staggering 2.9 petabytes of data for a research project.  The data – from three large cosmological simulations – was generated and stored on the Summit supercomputer at the Oak Ridge Leadership Computing Facility (OLCF)... Read more…

By Oliver Peckham

Nvidia, Google Tie in Second MLPerf Training ‘At-Scale’ Round

July 10, 2019

Results for the second round of the AI benchmarking suite known as MLPerf were published today with Google Cloud and Nvidia each picking up three wins in the at Read more…

By Tiffany Trader

Applied Materials Embedding New Memory Technologies in Chips

July 9, 2019

Applied Materials, the $17 billion Santa Clara-based materials engineering company for the semiconductor industry, today announced manufacturing systems enablin Read more…

By Doug Black

High Performance (Potato) Chips

May 5, 2006

In this article, we focus on how Procter & Gamble is using high performance computing to create some common, everyday supermarket products. Tom Lange, a 27-year veteran of the company, tells us how P&G models products, processes and production systems for the betterment of consumer package goods. Read more…

By Michael Feldman

Cray, AMD to Extend DOE’s Exascale Frontier

May 7, 2019

Cray and AMD are coming back to Oak Ridge National Laboratory to partner on the world’s largest and most expensive supercomputer. The Department of Energy’s Read more…

By Tiffany Trader

Graphene Surprises Again, This Time for Quantum Computing

May 8, 2019

Graphene is fascinating stuff with promise for use in a seeming endless number of applications. This month researchers from the University of Vienna and Institu Read more…

By John Russell

AMD Verifies Its Largest 7nm Chip Design in Ten Hours

June 5, 2019

AMD announced last week that its engineers had successfully executed the first physical verification of its largest 7nm chip design – in just ten hours. The AMD Radeon Instinct Vega20 – which boasts 13.2 billion transistors – was tested using a TSMC-certified Calibre nmDRC software platform from Mentor. Read more…

By Oliver Peckham

TSMC and Samsung Moving to 5nm; Whither Moore’s Law?

June 12, 2019

With reports that Taiwan Semiconductor Manufacturing Co. (TMSC) and Samsung are moving quickly to 5nm manufacturing, it’s a good time to again ponder whither goes the venerable Moore’s law. Shrinking feature size has of course been the primary hallmark of achieving Moore’s law... Read more…

By John Russell

Deep Learning Competitors Stalk Nvidia

May 14, 2019

There is no shortage of processing architectures emerging to accelerate deep learning workloads, with two more options emerging this week to challenge GPU leader Nvidia. First, Intel researchers claimed a new deep learning record for image classification on the ResNet-50 convolutional neural network. Separately, Israeli AI chip startup Hailo.ai... Read more…

By George Leopold

Nvidia Embraces Arm, Declares Intent to Accelerate All CPU Architectures

June 17, 2019

As the Top500 list was being announced at ISC in Frankfurt today with an upgraded petascale Arm supercomputer in the top third of the list, Nvidia announced its Read more…

By Tiffany Trader

Top500 Purely Petaflops; US Maintains Performance Lead

June 17, 2019

With the kick-off of the International Supercomputing Conference (ISC) in Frankfurt this morning, the 53rd Top500 list made its debut, and this one's for petafl Read more…

By Tiffany Trader

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour

CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
GOOGLE
GOOGLE
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
VERNE GLOBAL
VERNE GLOBAL

Intel Launches Cascade Lake Xeons with Up to 56 Cores

April 2, 2019

At Intel's Data-Centric Innovation Day in San Francisco (April 2), the company unveiled its second-generation Xeon Scalable (Cascade Lake) family and debuted it Read more…

By Tiffany Trader

Cray – and the Cray Brand – to Be Positioned at Tip of HPE’s HPC Spear

May 22, 2019

More so than with most acquisitions of this kind, HPE’s purchase of Cray for $1.3 billion, announced last week, seems to have elements of that overused, often Read more…

By Doug Black and Tiffany Trader

A Behind-the-Scenes Look at the Hardware That Powered the Black Hole Image

June 24, 2019

Two months ago, the first-ever image of a black hole took the internet by storm. A team of scientists took years to produce and verify the striking image – an Read more…

By Oliver Peckham

Announcing four new HPC capabilities in Google Cloud Platform

April 15, 2019

When you’re running compute-bound or memory-bound applications for high performance computing or large, data-dependent machine learning training workloads on Read more…

By Wyatt Gorman, HPC Specialist, Google Cloud; Brad Calder, VP of Engineering, Google Cloud; Bart Sano, VP of Platforms, Google Cloud

Chinese Company Sugon Placed on US ‘Entity List’ After Strong Showing at International Supercomputing Conference

June 26, 2019

After more than a decade of advancing its supercomputing prowess, operating the world’s most powerful supercomputer from June 2013 to June 2018, China is keep Read more…

By Tiffany Trader

Why Nvidia Bought Mellanox: ‘Future Datacenters Will Be…Like High Performance Computers’

March 14, 2019

“Future datacenters of all kinds will be built like high performance computers,” said Nvidia CEO Jensen Huang during a phone briefing on Monday after Nvidia revealed scooping up the high performance networking company Mellanox for $6.9 billion. Read more…

By Tiffany Trader

It’s Official: Aurora on Track to Be First US Exascale Computer in 2021

March 18, 2019

The U.S. Department of Energy along with Intel and Cray confirmed today that an Intel/Cray supercomputer, "Aurora," capable of sustained performance of one exaf Read more…

By Tiffany Trader

In Wake of Nvidia-Mellanox: Xilinx to Acquire Solarflare

April 25, 2019

With echoes of Nvidia’s recent acquisition of Mellanox, FPGA maker Xilinx has announced a definitive agreement to acquire Solarflare Communications, provider Read more…

By Doug Black

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This