COSMOS Team Achieves 100x Speedup on Cosmology Code

By Tiffany Trader

August 24, 2015

One of the most popular sessions at the Intel Developer Forum last week in San Francisco, and certainly one of the most exciting from an HPC perspective, brought together two of the world’s foremost experts in parallel programming to discuss current state-of-the-art methods for leveraging parallelism on processors and coprocessors. The speakers, Intel’s Jim Jeffers and James Reinders, are also the co-editors of the just-published “High Performance Parallelism Pearls Volume Two: Multicore and Many-core Programming Approaches.”

You aren’t likely to meet two more engaging and engaged programmers who make learning about this stuff fun, even for this non-coder interloper. In writing the two volumes, the duo saw “example after example get performance and performance portability with ‘just parallel programming.'”

Many of the chapters focus on porting codes to the MIC Phi multicore processor, but in the process, the Xeon processors also accrued significant speedups, often 5x or more. As for why developers did not exploit this parallelism until they had the Phi in hand, Reinders and Jeffers refer to this phenomenon as the “inspiration of 60+ cores.”

High Performance Parallelism Pearls Vol2 coverLike the first volume, High Performance Parallelism Pearls Volume Two (Morgan Kaufmann, 2015) offers a sampling of successful programming efforts, demonstrating how to leverage parallelism from Intel Xeon and Xeon Phi processors across multiple vertical domains in science and industry. The book has been published with the spirit of knowledge sharing and all of the figures and source code are available for download to facilitate further exploration.

The IDF15 session (see slides) was focused on providing the developer audience with useful stories and examples for programming for high performance. While the editors are careful in saying they don’t have favorite chapters, the success story related in chapter 10, titled “Cosmic Microwave Background Analysis: Nested Parallelism in Practice,” stands out for its scientific accomplishment and for its programming prowess.

The chapter, which is featured on the cover of the book, highlights the work of researchers in Stephen Hawking’s group at the University of Cambridge, who achieved over a 100x speedup with optimizations carried out in the process of porting their code to the Intel Xeon Phi coprocessor (Knights Corner). The theoretical physicists at Cambridge use a simulation code called MODAL to probe the Cosmic Background Radiation (CMB), a microwave frequency background radiation left over from the Big Bang. In analyzing this data from the origin of the universe and verifying it against theoretical observations, the team is reconstructing the CMB bispectrum for the first time. What is truly remarkable is that in seeking to understand how the universe emerged out of an intense period of expansion, called inflation, the research team has found evidence of extra dimensions.

A production run using the original Modal code (unoptimized, pure MPI) takes about six hours on 512 Intel Xeon E5-4650L cores of the COSMOS SGI supercomputer. If it can be sped-up then it will greatly enhance the cross-validation process, which requires the code be run many times.

Write the authors:

“The calculation performed by Modal is a prime candidate for Intel Xeon Phi coprocessors — the inner product calculations are computationally very expensive, independent of one another, and require very little memory (with production runs using only O(100) MB of RAM and writing only O(1) MB to disk). However, the code as written does not express this calculation in a way that is conducive to the utilization of modern hardware. Our acceleration of Modal therefore has two components: tuning the code to ensure that it runs efficiently (i.e., optimization); and enabling the code to scale across vectors and many cores (i.e., modernization). Extracting performance from current and future generations of Intel Xeon processors and Intel Xeon Phi coprocessors is impossible without parallelism, and the process of optimization and modernization presented here is imperative for ensuring that COSMOS stay at the forefront of cosmological research.”

The chapter — written by James P. Briggs, James R. Fergusson, Juha Jäykkä, Simon J. Pennycook and Edward P. Shellard — details the 10-step process of optimizations, illustrated below:

Accelerating Cosmic Microwave Background Briggs speedup

Accelerating Cosmic Microwave Background Briggs code versions 1-10

The experiment was carried out using a dual socket Intel Xeon processor E5-4650L and an Intel Xeon Phi coprocessor 5110P with the Intel Composer XE 2015 (v15.0.0.090) compiler.

In addition to showcasing the potentially paradigm-changing science that is being enabled, the chapter, and a related paper from the authors, are salient teaching tools, reflecting the hallmarks of effective parallelism, including one that is sometimes omitted from discussion.

Here Jeffers begins reviewing what he and Reinders have long identified as the three most important vectors of parallelism: “data locality, that is making sure your data is structured properly for the parallelism pipeline; threading or scalability; and then vectorization, taking advantage of the syncing capability.”

“But what did we forget?” Reinders calls out.

“What we forgot,” said Jeffers, “is that you should actually analyze your code and see from an algorithm standpoint what you might be able to do to improve your code.”

“So the biggest leap here was this,” Jeffers continues. “[The developers] were moving forward with parallelism, you see they are getting pretty good gains up through [code version] six. They are moving forward. They have the original code. They did some loop modifications and then at number three, Intel MKL integration routines come in. When they hit step seven, they have been v-tuning their code, looking at the hotspots, and then boom, the MKL integration routine is the hotspot. So they picked the one that best met the inputs and outputs they wanted. It turns out they didn’t need all the power of that, the precision, etc. So they wrote their own. They used the new trapezium rule integrator and bang [performance shoots up] — so, it’s not all about the three vectors.”

“So don’t forget your algorithms,” adds Reinders, emphatically. “Do you really need the algorithm you are using? They went from a 10x to a 60x speedup in that one step, and it was an algorithm change and it affected Xeon and Xeon Phi almost equally.”

“And this is a production code,” Jeffers emphasizes, “extremely important to them, to their analysis, and really to the world in understanding the universe.”

From the COSMOS team: “We find that using a simple trapezium rule integrator combined with hand-selected sampling points (to improve accuracy in areas of interest) provides sufficient numerical accuracy to obtain a physically meaningful result, and the reduced space and time requirements of this simplified method give a speed-up of O(10x).”

A summary of the team’s conclusions appears in a presentation posted to manycore.com:

CMD Intel Cambridge Briggs Conclusions
“The total speed-up relative to the original baseline code is close to 100x on both platforms,” the authors write in chapter 10 of the new Pearls volume. “Further the results shown here use only two processor sockets or one coprocessor–by dividing the complete problem space across nodes using MPI, and then subdividing across the processor and coprocessor present in each node, the calculation can be accelerated even further. These optimizations have thus enabled COSMOS to completely change the way in which the code is used; rather than running on the entire system for hours, after careful selection of cosmological parameters, Modal can now be incorporated as part of a larger Monte Carlo pipeline to quickly evaluate the likelihood of alternative parameters.”

On the IDF15 showroom floor, Intel demonstrated a visualization of the cosmic background radiation rendered with the open-source OSPRay Ray Tracing engine running live on two pre-production Intel Knights Landing cards connected by the Omni-Path pre-production fabric. Being able to observe the Planck data with this tool allows scientists to see correlations predicted by Einstein’s theory of general relativity.

Intel COSMOS CBR visualization IDF15 1200x

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!

New GE Simulations on Summit to Advance Offshore Wind Power

August 6, 2020

The wind energy sector is a frequent user of high-power simulations, with researchers aiming to optimize wind flows and energy production from the massive turbines. Now, researchers at GE are preparing to undertake a lar Read more…

By Oliver Peckham

Research: A Survey of Numerical Methods Utilizing Mixed Precision Arithmetic

August 5, 2020

Within the past years, hardware vendors have started designing low precision special function units in response to the demand of the machine learning community and their demand for high compute power in low precision for Read more…

By Hartwig Anzt and Jack Dongarra

Implement Photonic Tensor Cores for Machine Learning?

August 5, 2020

Researchers from George Washington University have reported an approach for building photonic tensor cores that leverages phase change photonic memory to implement a neural network (NN). Their novel architecture, reporte Read more…

By John Russell

HPE Keeps Cray Brand Promise, Reveals HPE Cray Supercomputing Line

August 4, 2020

The HPC community, ever-affectionate toward Cray and its eponymous founder, can breathe a (virtual) sigh of relief. The Cray brand will live on, encompassing the pinnacle of HPE's HPC portfolio. After announcing its i Read more…

By Tiffany Trader

Machines, Connections, Data, and Especially People: OAC Acting Director Amy Friedlander Charts Office’s Blueprint for Innovation

August 3, 2020

The path to innovation in cyberinfrastructure (CI) will require continued focus on building HPC systems and secure connections between them, in addition to the increasingly important goals of data best practices and work Read more…

By Ken Chiacchia, Pittsburgh Supercomputing Center/XSEDE

AWS Solution Channel

AWS announces the release of AWS ParallelCluster 2.8.0

AWS ParallelCluster is a fully supported and maintained open source cluster management tool that makes it easy for scientists, researchers, and IT administrators to deploy and manage High Performance Computing (HPC) clusters in the AWS cloud. Read more…

Intel® HPC + AI Pavilion

Supercomputing the Pandemic: Scientific Community Tackles COVID-19 from Multiple Perspectives

Since their inception, supercomputers have taken on the biggest, most complex, and most data-intensive computing challenges—from confirming Einstein’s theories about gravitational waves to predicting the impacts of climate change. Read more…

Nvidia Said to Be Close on Arm Deal

August 3, 2020

GPU leader Nvidia Corp. is in talks to buy U.K. chip designer Arm from parent company Softbank, according to several reports over the weekend. If consummated, analysts said the acquisition would cement Nvidia’s stat Read more…

By George Leopold

HPE Keeps Cray Brand Promise, Reveals HPE Cray Supercomputing Line

August 4, 2020

The HPC community, ever-affectionate toward Cray and its eponymous founder, can breathe a (virtual) sigh of relief. The Cray brand will live on, encompassing th Read more…

By Tiffany Trader

Machines, Connections, Data, and Especially People: OAC Acting Director Amy Friedlander Charts Office’s Blueprint for Innovation

August 3, 2020

The path to innovation in cyberinfrastructure (CI) will require continued focus on building HPC systems and secure connections between them, in addition to the Read more…

By Ken Chiacchia, Pittsburgh Supercomputing Center/XSEDE

Nvidia Said to Be Close on Arm Deal

August 3, 2020

GPU leader Nvidia Corp. is in talks to buy U.K. chip designer Arm from parent company Softbank, according to several reports over the weekend. If consummated Read more…

By George Leopold

Intel’s 7nm Slip Raises Questions About Ponte Vecchio GPU, Aurora Supercomputer

July 30, 2020

During its second-quarter earnings call, Intel announced a one-year delay of its 7nm process technology, which it says it will create an approximate six-month shift for its CPU product timing relative to prior expectations. The primary issue is a defect mode in the 7nm process that resulted in yield degradation... Read more…

By Tiffany Trader

PEARC20 Plenary Introduces Five Upcoming NSF-Funded HPC Systems

July 30, 2020

Five new HPC systems—three National Science Foundation-funded “Capacity” systems and two “Innovative Prototype/Testbed” systems—will be coming onlin Read more…

By Ken Chiacchia, Pittsburgh Supercomputing Center/XSEDE

Nvidia Dominates Latest MLPerf Training Benchmark Results

July 29, 2020

MLPerf.org released its third round of training benchmark (v0.7) results today and Nvidia again dominated, claiming 16 new records. Meanwhile, Google provided e Read more…

By John Russell

$39 Billion Worldwide HPC Market Faces 3.7% COVID-related Drop in 2020

July 29, 2020

Global HPC market revenue reached $39 billion in 2019, growing a healthy 8.2 percent over 2018, according to the latest analysis from Intersect360 Research. A 3 Read more…

By Tiffany Trader

Agenting Change: PEARC20 Keynote Encourages Cultural Change to Make Tech Better, More Diverse

July 29, 2020

The tech world will need to become more diverse if it is to thrive and survive, said Cherri Pancake, director of the Northwest Alliance for Computational Resear Read more…

By Ken Chiacchia, Pittsburgh Supercomputing Center/XSEDE

Supercomputer Modeling Tests How COVID-19 Spreads in Grocery Stores

April 8, 2020

In the COVID-19 era, many people are treating simple activities like getting gas or groceries with caution as they try to heed social distancing mandates and protect their own health. Still, significant uncertainty surrounds the relative risk of different activities, and conflicting information is prevalent. A team of Finnish researchers set out to address some of these uncertainties by... Read more…

By Oliver Peckham

Supercomputer-Powered Research Uncovers Signs of ‘Bradykinin Storm’ That May Explain COVID-19 Symptoms

July 28, 2020

Doctors and medical researchers have struggled to pinpoint – let alone explain – the deluge of symptoms induced by COVID-19 infections in patients, and what Read more…

By Oliver Peckham

Intel’s 7nm Slip Raises Questions About Ponte Vecchio GPU, Aurora Supercomputer

July 30, 2020

During its second-quarter earnings call, Intel announced a one-year delay of its 7nm process technology, which it says it will create an approximate six-month shift for its CPU product timing relative to prior expectations. The primary issue is a defect mode in the 7nm process that resulted in yield degradation... Read more…

By Tiffany Trader

Supercomputer Simulations Reveal the Fate of the Neanderthals

May 25, 2020

For hundreds of thousands of years, neanderthals roamed the planet, eventually (almost 50,000 years ago) giving way to homo sapiens, which quickly became the do Read more…

By Oliver Peckham

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

By Doug Black

Nvidia Said to Be Close on Arm Deal

August 3, 2020

GPU leader Nvidia Corp. is in talks to buy U.K. chip designer Arm from parent company Softbank, according to several reports over the weekend. If consummated Read more…

By George Leopold

Neocortex Will Be First-of-Its-Kind 800,000-Core AI Supercomputer

June 9, 2020

Pittsburgh Supercomputing Center (PSC - a joint research organization of Carnegie Mellon University and the University of Pittsburgh) has won a $5 million award Read more…

By Tiffany Trader

Nvidia’s Ampere A100 GPU: Up to 2.5X the HPC, 20X the AI

May 14, 2020

Nvidia's first Ampere-based graphics card, the A100 GPU, packs a whopping 54 billion transistors on 826mm2 of silicon, making it the world's largest seven-nanom Read more…

By Tiffany Trader

Leading Solution Providers

Contributors

Australian Researchers Break All-Time Internet Speed Record

May 26, 2020

If you’ve been stuck at home for the last few months, you’ve probably become more attuned to the quality (or lack thereof) of your internet connection. Even Read more…

By Oliver Peckham

15 Slides on Programming Aurora and Exascale Systems

May 7, 2020

Sometime in 2021, Aurora, the first planned U.S. exascale system, is scheduled to be fired up at Argonne National Laboratory. Cray (now HPE) and Intel are the k Read more…

By John Russell

‘Billion Molecules Against COVID-19’ Challenge to Launch with Massive Supercomputing Support

April 22, 2020

Around the world, supercomputing centers have spun up and opened their doors for COVID-19 research in what may be the most unified supercomputing effort in hist Read more…

By Oliver Peckham

Joliot-Curie Supercomputer Used to Build First Full, High-Fidelity Aircraft Engine Simulation

July 14, 2020

When industrial designers plan the design of a new element of a vehicle’s propulsion or exterior, they typically use fluid dynamics to optimize airflow and in Read more…

By Oliver Peckham

$100B Plan Submitted for Massive Remake and Expansion of NSF

May 27, 2020

Legislation to reshape, expand - and rename - the National Science Foundation has been submitted in both the U.S. House and Senate. The proposal, which seems to Read more…

By John Russell

John Martinis Reportedly Leaves Google Quantum Effort

April 21, 2020

John Martinis, who led Google’s quantum computing effort since establishing its quantum hardware group in 2014, has left Google after being moved into an advi Read more…

By John Russell

Google Cloud Debuts 16-GPU Ampere A100 Instances

July 7, 2020

On the heels of the Nvidia’s Ampere A100 GPU launch in May, Google Cloud is announcing alpha availability of the A100 “Accelerator Optimized” VM A2 instance family on Google Compute Engine. The instances are powered by the HGX A100 16-GPU platform, which combines two HGX A100 8-GPU baseboards using... Read more…

By Tiffany Trader

Japan’s Fugaku Tops Global Supercomputing Rankings

June 22, 2020

A new Top500 champ was unveiled today. Supercomputer Fugaku, the pride of Japan and the namesake of Mount Fuji, vaulted to the top of the 55th edition of the To Read more…

By Tiffany Trader

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