Exterminating at Extreme Scale

By Nicole Hemsoth

May 7, 2013

Since the first bug was eradicated from a Mark II system at Harvard in 1940s (an actual moth wedged in a relay, which drove the machine to a standstill) system exterminators have faced a constant spray of challenges. Nodes continue to reproduce, architectures alter, and application demands climb ever-higher walls.  

This all means it’s getting tougher for code exterminators to reproduce and track down the bugs across many thousands of cores. Further, many pre-petascale debuggers weren’t able to efficiently relay information about the health of the entire application, allowing a small portal to see one process at a time, despite the fact that hundreds were being debugged alongside.

Throw  coprocessors and accelerators into the mix and it seems there’s a perfect storm brewing for a total rethink in more efficient, scalable bug-zapping—especially with the spectre of exascale in the distance.

According to David Lecomber, co-founder and COO of HPC debugging company, Allinea, the scale and complexity of systems it’s been working with, including Titan and Blue Waters, required new approaches to tackle larger node counts. More pressing and complex, however, is the increased heterogeneity. For top-tier machines like these, he says, scale and core diversity are critical–but at the heart of all of their work is improving debugging speed. The company has targeted all of these areas as it’s worked alongside Oak Ridge National Lab, NCSA, and others aiming for extreme scale computing targets, refining its ability to show thousands of processes in one, full view for more effective bug stomping.

In the “moth-plucking” days of debugging, before visually-oriented, multi-process, scalable approaches, every single node in a cluster had to directly connect to where the user was sitting. Naturally, as node counts climbed, the workstations were quickly overloaded, meaning users could only handle at most several hundred or a thousand cores. Debugging was a necessary, clunky of evil—one that wouldn’t hold up to the demands of core counts in the hundreds of thousands, and even if it could keep up, it would slow to a crawl.

Lecomber touts his company’s role in reshaping that long-standing trend via Allinea’s DDT, which offered a UI that could paint the whole landscape of an application, letting users “visualize and compare 200,000 processes as simply as two.” Their work at massive scale recently started in earnest with Jaguar via their work with Oak Ridge, before wading into Blue Waters or battling the Titan. He claims that despite the scale, the speed was emphasized—to the point that Allinea could handle even higher node counts in anything we’re set to see soon. He said that the time to debug using the old node-connected approach was in the minutes, but they’ve been able to trim this process down to seconds.

During the company’s early work with Jaguar, and later Titan, Oak Ridge had a couple of problems, including limitations with the traditional printfs debugging approach to find bugs, followed by adding GPUs into the mix. Oak Ridge’s Tools Project Technical Officer, Joshua Ladd said that the ability to see every process in a parallel job allowed the lab to remove the debugging hassles and speed time to result.

And on the GPU front, the lab wanted researchers to take advantage of Titan’s accelerators but they needed more powerful tools that could attack those more complicated bugs. Further, Oak Ridge was able to harness DDT on Jaguar to debug an open source implementation of MPI at a half-million lines of code across a maximum of 225,000 cores.

Scale aside, as noted, the true challenges relate to the increasing heterogeneity of ever-larger systems. Lecomber said that a lot of work went on behind the scenes to get DDT primed for GPUs and coprocessors, and he expects such challenges are going to persist during the exascale climb. They’ve already done a great deal of work on accelerators and recently looked to address challenges on Xeon Phi, as detailed below.

Beyond new architectures, Allinea is focusing on combining advanced debugging and performance tools so users will be able to better visualize the performance of their applications. In other words, having a petascale machine isn’t incredibly useful if you can’t take advantage of that power—just as computing the fastest wrong answer won’t work either.

When it comes to exascale, and even petascale at this point, “the real gaps are in the tools area, the people writing applications for these large machines need to be able to do performance profiling in a similar way as they handle debugging—visually and with emphasis on speed,” he said. Their MPI profiler, called MAP, highlights lines of code that executed the slowest to demo what happened during the run in a format that will be familiar to those who already use DDT.

While we generally hear about HPC debuggers in the context of national labs, petascale systems are proliferating in the commercial spaces as well, necessitating enterprise-grade, extreme-scale extermination. Lecomber says that companies they work with, several of which are in the oil and gas and engineering arenas, are adopting similarly-sized systems that present mission-critical challenges. Simulating the performance and safety of an engine, for instance, can have devastating results if not done correctly or at best, can result in expensive runtime waste.

Aside from their academic affiliations and work in oil and gas and other key commercial areas, Allinea is working closely with the European Collaborative Research into Exascale Systemware, Tools and Applications (CRESTA) to identify what these future systems will look like and how tool vendors and application artists will need to rework their approaches. Lecomber says this also involves collaboration with system designers, processor-makers and other vendors to make sure the exascale research food chain is aligned.

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

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

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

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