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!

Fluid HPC: How Extreme-Scale Computing Should Respond to Meltdown and Spectre

February 15, 2018

The Meltdown and Spectre vulnerabilities are proving difficult to fix, and initial experiments suggest security patches will cause significant performance penalties to HPC applications. Even as these patches are rolled o Read more…

By Pete Beckman

Intel Touts Silicon Spin Qubits for Quantum Computing

February 14, 2018

Debate around what makes a good qubit and how best to manufacture them is a sprawling topic. There are many insistent voices favoring one or another approach. Referencing a paper published today in Nature, Intel has offe Read more…

By John Russell

Brookhaven Ramps Up Computing for National Security Effort

February 14, 2018

Last week, Dan Coats, the director of Director of National Intelligence for the U.S., warned the Senate Intelligence Committee that Russia was likely to meddle in the 2018 mid-term U.S. elections, much as it stands accused of doing in the 2016 Presidential election. Read more…

By John Russell

HPE Extreme Performance Solutions

Safeguard Your HPC Environment with the World’s Most Secure Industry Standard Servers

Today’s organizations operate in an environment with ever-evolving threats, and in order to protect themselves they must continuously bolster their security strategy. Hewlett Packard Enterprise (HPE) and Intel® are addressing modern security challenges with the world’s most secure industry standard servers powered by the latest generation of Intel® Xeon® Scalable processors. Read more…

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended to make it easier, faster and cheaper to train and run machi Read more…

By Doug Black

Fluid HPC: How Extreme-Scale Computing Should Respond to Meltdown and Spectre

February 15, 2018

The Meltdown and Spectre vulnerabilities are proving difficult to fix, and initial experiments suggest security patches will cause significant performance penal Read more…

By Pete Beckman

Brookhaven Ramps Up Computing for National Security Effort

February 14, 2018

Last week, Dan Coats, the director of Director of National Intelligence for the U.S., warned the Senate Intelligence Committee that Russia was likely to meddle in the 2018 mid-term U.S. elections, much as it stands accused of doing in the 2016 Presidential election. Read more…

By John Russell

AI Cloud Competition Heats Up: Google’s TPUs, Amazon Building AI Chip

February 12, 2018

Competition in the white hot AI (and public cloud) market pits Google against Amazon this week, with Google offering AI hardware on its cloud platform intended Read more…

By Doug Black

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

The Food Industry’s Next Journey — from Mars to Exascale

February 12, 2018

Global food producer and one of the world's leading chocolate companies Mars Inc. has a unique perspective on the impact that exascale computing will have on the food industry. Read more…

By Scott Gibson, Oak Ridge National Laboratory

Singularity HPC Container Start-Up – Sylabs – Emerges from Stealth

February 8, 2018

The driving force behind Singularity, the popular HPC container technology, is bringing the open source platform to the enterprise with the launch of a new vent Read more…

By George Leopold

Dell EMC Debuts PowerEdge Servers with AMD EPYC Chips

February 6, 2018

AMD notched another EPYC processor win today with Dell EMC’s introduction of three PowerEdge servers (R6415, R7415, and R7425) based on the EPYC 7000-series p Read more…

By John Russell

‘Next Generation’ Universe Simulation Is Most Advanced Yet

February 5, 2018

The research group that gave us the most detailed time-lapse simulation of the universe’s evolution in 2014, spanning 13.8 billion years of cosmic evolution, is back in the spotlight with an even more advanced cosmological model that is providing new insights into how black holes influence the distribution of dark matter, how heavy elements are produced and distributed, and where magnetic fields originate. Read more…

By Tiffany Trader

Inventor Claims to Have Solved Floating Point Error Problem

January 17, 2018

"The decades-old floating point error problem has been solved," proclaims a press release from inventor Alan Jorgensen. The computer scientist has filed for and Read more…

By Tiffany Trader

Japan Unveils Quantum Neural Network

November 22, 2017

The U.S. and China are leading the race toward productive quantum computing, but it's early enough that ultimate leadership is still something of an open questi Read more…

By Tiffany Trader

AMD Showcases Growing Portfolio of EPYC and Radeon-based Systems at SC17

November 13, 2017

AMD’s charge back into HPC and the datacenter is on full display at SC17. Having launched the EPYC processor line in June along with its MI25 GPU the focus he Read more…

By John Russell

Researchers Measure Impact of ‘Meltdown’ and ‘Spectre’ Patches on HPC Workloads

January 17, 2018

Computer scientists from the Center for Computational Research, State University of New York (SUNY), University at Buffalo have examined the effect of Meltdown Read more…

By Tiffany Trader

IBM Begins Power9 Rollout with Backing from DOE, Google

December 6, 2017

After over a year of buildup, IBM is unveiling its first Power9 system based on the same architecture as the Department of Energy CORAL supercomputers, Summit a Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Nvidia highlights strengths of its newest GPU silicon in response to Google's report on the performance and energy advantages of its custom tensor processor. Read more…

By Tiffany Trader

Fast Forward: Five HPC Predictions for 2018

December 21, 2017

What’s on your list of high (and low) lights for 2017? Volta 100’s arrival on the heels of the P100? Appearance, albeit late in the year, of IBM’s Power9? Read more…

By John Russell

Russian Nuclear Engineers Caught Cryptomining on Lab Supercomputer

February 12, 2018

Nuclear scientists working at the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF) have been arrested for using lab supercomputing resources to mine crypto-currency, according to a report in Russia’s Interfax News Agency. Read more…

By Tiffany Trader

Leading Solution Providers

Chip Flaws ‘Meltdown’ and ‘Spectre’ Loom Large

January 4, 2018

The HPC and wider tech community have been abuzz this week over the discovery of critical design flaws that impact virtually all contemporary microprocessors. T Read more…

By Tiffany Trader

Perspective: What Really Happened at SC17?

November 22, 2017

SC is over. Now comes the myriad of follow-ups. Inboxes are filled with templated emails from vendors and other exhibitors hoping to win a place in the post-SC thinking of booth visitors. Attendees of tutorials, workshops and other technical sessions will be inundated with requests for feedback. Read more…

By Andrew Jones

How Meltdown and Spectre Patches Will Affect HPC Workloads

January 10, 2018

There have been claims that the fixes for the Meltdown and Spectre security vulnerabilities, named the KPTI (aka KAISER) patches, are going to affect applicatio Read more…

By Rosemary Francis

GlobalFoundries, Ayar Labs Team Up to Commercialize Optical I/O

December 4, 2017

GlobalFoundries (GF) and Ayar Labs, a startup focused on using light, instead of electricity, to transfer data between chips, today announced they've entered in Read more…

By Tiffany Trader

Tensors Come of Age: Why the AI Revolution Will Help HPC

November 13, 2017

Thirty years ago, parallel computing was coming of age. A bitter battle began between stalwart vector computing supporters and advocates of various approaches to parallel computing. IBM skeptic Alan Karp, reacting to announcements of nCUBE’s 1024-microprocessor system and Thinking Machines’ 65,536-element array, made a public $100 wager that no one could get a parallel speedup of over 200 on real HPC workloads. Read more…

By John Gustafson & Lenore Mullin

Flipping the Flops and Reading the Top500 Tea Leaves

November 13, 2017

The 50th edition of the Top500 list, the biannual publication of the world’s fastest supercomputers based on public Linpack benchmarking results, was released Read more…

By Tiffany Trader

V100 Good but not Great on Select Deep Learning Aps, Says Xcelerit

November 27, 2017

Wringing optimum performance from hardware to accelerate deep learning applications is a challenge that often depends on the specific application in use. A benc Read more…

By John Russell

SC17: Singularity Preps Version 3.0, Nears 1M Containers Served Daily

November 1, 2017

Just a few months ago about half a million jobs were being run daily using Singularity containers, the LBNL-founded container platform intended for HPC. That wa Read more…

By John Russell

  • arrow
  • Click Here for More Headlines
  • arrow
Share This