Supernova Factory Employs EC2, Puts Cloud to the Test

By Nicole Hemsoth

July 9, 2010

There is something thrilling about the very term “supernova factory” in that it invokes startling mental images culled from science fiction and our own imaginations. However, the real factory in question here is at the heart of an international research collaboration, although not one in the business of mass-producing supernovas in some kind of cosmic warehouse. It is instead examining the nature of dark energy to understand a “simple” concept — the expanding universe.

The universe is growing rapidly due to what physicists have dubbed as dark energy — a finding that was made possible by comparing the relative brightness of “close” supernovae to the brightness of those much farther in the distance (which culminates in the difference of several billion years). The comparison is not possible without understanding the underlying physics that produced the supernovae that is the nearest, which is where the Nearby Supernova Factory (SNfactory) enters the picture. The project relies on a complicated “pipeline of serial processes that execute various image processing algorithms on approximately 10Tbs of data” to step closer to understanding dark energy and its role in the universe’s constant expansion.

While all of this is interesting enough on its own, the project has a particularly unique HPC and cloud slant due to the efforts of Berkeley researcher Lavanya Ramakrishnan and her team. They have been able to shed light on how a public cloud like EC2 can (and cannot) be used for some scientific computing applications by bringing SNfactory’s pipeline to the cloud. During a recent chat with Ramakrishnan, it became clear that while there are attractive features of clouds, there are some hurdles that relate to just the issues that most concern scientific users, including performance, reliability, as well as ease of use and configuration.

In her research that spans beyond this particular project’s scope, Lavanya Ramakrishnan focuses directly on topics related to finding ways to handle scientific workloads that are reliant on high performance and distributed systems. Accordingly, she has looked extensively at the possibilities of deploying clouds to handle scientiic workloads as well as considering grid technologies and their relevant role in the area.

The SNfactory cloud computing evaluation project in question is important as it provides not only a case study of using HPC in a public cloud, but also because of the specificity of design tests to maximize performance outside of the physical infrastructure. The paper presenting their findings, entitled “Seeking Supernovae in the Clouds: A Performance Study,” won the top honor at the First Workshop on Scientific Cloud Computing this summer. This is not a surprise as the paper provides an in-depth examination of the benefits and drawbacks of public clouds in specific context along with detailed descriptions of the various configurations that produced their conclusions.

Getting Scientific Computing Off the Ground

Until just recently, the Supernova Factory’s complex pipeline was fed into a local cluster. With the oversight and alterations on the part of Berkeley researchers to refine the environment from application-level up, the pipeline was fed into a Amazon’s EC2 after significant experimentation, all of which is discussed at length in the paper. These experimental designs were for the specific purpose of determining what options were available on a design level to suit application data placement and more generally, to provide a distinct view of the performance results in a virtualized cluster environment.

Overall, the authors concluded that “cloud computing offers many features that make it an attractive alternative. The ability to completely control the software environment in a cloud is appealing when dealing with a community-developed science pipeline with many unique library and platform requirements.” While this is a bright statement about the use of the cloud for a project like this, according to Lavanya Ramakrishnan, who spoke with HPC in the Cloud recently about the results of the Berkeley team’s work, the cloud, at least as offered by EC2 is not an out of the box solution for scientific computing users and there were a number of challenges along the way that present some meaty discussion bits for those who debate that the cloud is not ready for HPC.

Ramakrishnan is not the first scientific HPC user to comment on the complexity that is involved when first preparing to send applications into the cloud and setting up the environment. She noted that while it was difficult to determine how long it took them to get started since their purpose was to test multiple designs and models, she advised that it was not a quick or easy process. Before even getting to the point where one would be ready to make the leap, there would have to be exhaustive research about how to best tailor their environment to the specific applications.

In addition to being a complex task to undertake, once the ideal environment is created and the applications and virtual machines have been synched into what might appear to be the best configuration, there are also some troubles with the predictable enemies of HPC and cloud — performance and reliability. The authors of the study encountered a number of failures throughout their experiments with EC2 that would not have been matters of concern with the traditional environment. As Ramakrishnan stated, “A lot of these [scientific] applications have not been designed with these commodity clusters in mind so the reliability issue, which wasn’t a major problem before, is now important.”

The Big Picture for Scientific Computing in the Public Cloud

The full paper provides deep specifics for those looking to design their cloud environment for scientific computing that can be of immense value and save a great deal of time and frustration. It is critical reading for anyone looking to use the cloud for similar (although chances are, on much smaller-scale) workloads.

What is important here in the scientific computing sense bears repeating. There are many questions about the suitability of public clouds for HPC-type applications and while there are many favorable experiences that bode well for the future of this area, some of the barriers and problems need to be addressed in a major way before the clouds will be a paradigm shift for scientific computing.

Ramakrishnan, who as it was noted earlier, spends much of her research time investigating alternatives to traditional HPC, sees how cloud computing is a promising technology in theory for researchers. For instance, as she noted, in physical environments “applications suffer because the people running the machines need to upgrade their packages and software to run in these environments. Sometimes there are compatibility issues and this gets even more complicated when they have collaborations across groups because everyone needs to upgrade to a different version. Software maintenance becomes a big challenge. Cloud has therefore become attractive to a lot of scientific computing users, including the Supernova Factory — cloud lets them maintain this entire stack they need and this alone is very attractive.”

Based on her experiences using a number of different configurations and models for cloud in scientific computing, Ramakrishnan indicated that while there is a class of scientific applications that are well-suited to the cloud, there are indeed many challenges. Furthermore, the important point is that researchers understand that this solution, even if the applications fit well with clouds, cannot be undertaken lightly. A great deal of preparation is required, especially if one is operating on the large scale, before making the leap into the cloud.

Scientific computing and cloud computing are not at odds; they live on the same planet but there is a vast ocean that separates the two at this point — at least if we are talking about public clouds. Performance and reliability — two keys to successfully running applications on bare metal systems — are in question in the public cloud and until ideal configurations can be presented across a wide range of application types more research like that being performed by Ramakrishnan and her colleagues is critical.

Many of the points that Ramakrishnan made about the suitability of the public cloud at large for this kind of workload correspond with what Kathy Yelick discussed in an overview of current progress at the Magellan Testbed, another research endeavor out of Berkeley. The consensus is that there is promise — but only for certain types of applications — at least until more development on the application and cloud levels takes place.

Still, Amazon insists with great ferocity that the future of scientific computing lies in their cloud offering, and this is echoed by Microsoft and others with Azure and EC2-like services. Until the scientific computing community fully experiments with the public cloud to determine how best to configure the enviornment for their applications, we will probably hear a great deal more conflicting information about the suitability of the public clouds for large-scale scientific workloads.

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!

Japan Meteorological Agency Takes Delivery of Pair of Crays

May 21, 2018

Cray has supplied two identical Cray XC50 supercomputers to the Japan Meteorological Agency (JMA) in northwestern Tokyo. Boasting more than 18 petaflops combined peak computing capacity, the new systems will extend the a Read more…

By Tiffany Trader

ASC18: Final Results Revealed & Wrapped Up

May 17, 2018

It was an exciting week at ASC18 in Nanyang, China. The student teams braved extreme heat, extremely difficult applications, and extreme competition in order to cross the cluster competition finish line. The gala awards ceremony took place on Wednesday. The auditorium was packed with student teams, various dignitaries, the media, and other interested parties. So what happened? Read more…

By Dan Olds

ASC18: Tough Applications & Tough Luck

May 17, 2018

The applications at the ASC18 Student Cluster Competition were tough. Tougher than the $3.99 steak special at your local greasy spoon restaurant. The apps are so tough that even Chuck Norris backs away from them slowly. Read more…

By Dan Olds

HPE Extreme Performance Solutions

HPC and AI Convergence is Accelerating New Levels of Intelligence

Data analytics is the most valuable tool in the digital marketplace – so much so that organizations are employing high performance computing (HPC) capabilities to rapidly collect, share, and analyze endless streams of data. Read more…

IBM Accelerated Insights

Mastering the Big Data Challenge in Cognitive Healthcare

Patrick Chain, genomics researcher at Los Alamos National Laboratory, posed a question in a recent blog: What if a nurse could swipe a patient’s saliva and run a quick genetic test to determine if the patient’s sore throat was caused by a cold virus or a bacterial infection? Read more…

Spring Meetings Underscore Quantum Computing’s Rise

May 17, 2018

The month of April 2018 saw four very important and interesting meetings to discuss the state of quantum computing technologies, their potential impacts, and the technology challenges ahead. These discussions happened in Read more…

By Alex R. Larzelere

Japan Meteorological Agency Takes Delivery of Pair of Crays

May 21, 2018

Cray has supplied two identical Cray XC50 supercomputers to the Japan Meteorological Agency (JMA) in northwestern Tokyo. Boasting more than 18 petaflops combine Read more…

By Tiffany Trader

ASC18: Final Results Revealed & Wrapped Up

May 17, 2018

It was an exciting week at ASC18 in Nanyang, China. The student teams braved extreme heat, extremely difficult applications, and extreme competition in order to cross the cluster competition finish line. The gala awards ceremony took place on Wednesday. The auditorium was packed with student teams, various dignitaries, the media, and other interested parties. So what happened? Read more…

By Dan Olds

Spring Meetings Underscore Quantum Computing’s Rise

May 17, 2018

The month of April 2018 saw four very important and interesting meetings to discuss the state of quantum computing technologies, their potential impacts, and th Read more…

By Alex R. Larzelere

Quantum Network Hub Opens in Japan

May 17, 2018

Following on the launch of its Q Commercial quantum network last December with 12 industrial and academic partners, the official Japanese hub at Keio University is now open to facilitate the exploration of quantum applications important to science and business. The news comes a week after IBM announced that North Carolina State University was the first U.S. university to join its Q Network. Read more…

By Tiffany Trader

Democratizing HPC: OSC Releases Version 1.3 of OnDemand

May 16, 2018

Making HPC resources readily available and easier to use for scientists who may have less HPC expertise is an ongoing challenge. Open OnDemand is a project by t Read more…

By John Russell

PRACE 2017 Annual Report: Exascale Aspirations; Industry Collaboration; HPC Training

May 15, 2018

The Partnership for Advanced Computing in Europe (PRACE) today released its annual report showcasing 2017 activities and providing a glimpse into thinking about Read more…

By John Russell

US Forms AI Brain Trust

May 11, 2018

Amid calls for a U.S. strategy for promoting AI development, the Trump administration is forming a senior-level panel to help coordinate government and industry research efforts. The Select Committee on Artificial Intelligence was announced Thursday (May 10) during a White House summit organized by the Office of Science and Technology Policy (OSTP). Read more…

By George Leopold

Emerging Advanced Scale Tech Trends Focus of Annual Tabor Conference

May 9, 2018

At Tabor Communications' annual Advanced Scale Forum (ASF) held this week in Austin, the focus was on enterprise adoption of HPC-class technologies and high performance data analytics (HPDA). It’s a confab that brings together end users (CIOs, IT planners, department heads) and vendors and encourages... Read more…

By the Editorial Team

MLPerf – Will New Machine Learning Benchmark Help Propel AI Forward?

May 2, 2018

Let the AI benchmarking wars begin. Today, a diverse group from academia and industry – Google, Baidu, Intel, AMD, Harvard, and Stanford among them – releas Read more…

By John Russell

How the Cloud Is Falling Short for HPC

March 15, 2018

The last couple of years have seen cloud computing gradually build some legitimacy within the HPC world, but still the HPC industry lies far behind enterprise I Read more…

By Chris Downing

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

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

Deep Learning at 15 PFlops Enables Training for Extreme Weather Identification at Scale

March 19, 2018

Petaflop per second deep learning training performance on the NERSC (National Energy Research Scientific Computing Center) Cori supercomputer has given climate Read more…

By Rob Farber

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

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

US Plans $1.8 Billion Spend on DOE Exascale Supercomputing

April 11, 2018

On Monday, the United States Department of Energy announced its intention to procure up to three exascale supercomputers at a cost of up to $1.8 billion with th Read more…

By Tiffany Trader

Leading Solution Providers

Lenovo Unveils Warm Water Cooled ThinkSystem SD650 in Rampup to LRZ Install

February 22, 2018

This week Lenovo took the wraps off the ThinkSystem SD650 high-density server with third-generation direct water cooling technology developed in tandem with par Read more…

By Tiffany Trader

HPC and AI – Two Communities Same Future

January 25, 2018

According to Al Gara (Intel Fellow, Data Center Group), high performance computing and artificial intelligence will increasingly intertwine as we transition to Read more…

By Rob Farber

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

Google Chases Quantum Supremacy with 72-Qubit Processor

March 7, 2018

Google pulled ahead of the pack this week in the race toward "quantum supremacy," with the introduction of a new 72-qubit quantum processor called Bristlecone. Read more…

By Tiffany Trader

HPE Wins $57 Million DoD Supercomputing Contract

February 20, 2018

Hewlett Packard Enterprise (HPE) today revealed details of its massive $57 million HPC contract with the U.S. Department of Defense (DoD). The deal calls for HP Read more…

By Tiffany Trader

CFO Steps down in Executive Shuffle at Supermicro

January 31, 2018

Supermicro yesterday announced senior management shuffling including prominent departures, the completion of an audit linked to its delayed Nasdaq filings, and Read more…

By John Russell

Deep Learning Portends ‘Sea Change’ for Oil and Gas Sector

February 1, 2018

The billowing compute and data demands that spurred the oil and gas industry to be the largest commercial users of high-performance computing are now propelling Read more…

By Tiffany Trader

Nvidia Ups Hardware Game with 16-GPU DGX-2 Server and 18-Port NVSwitch

March 27, 2018

Nvidia unveiled a raft of new products from its annual technology conference in San Jose today, and despite not offering up a new chip architecture, there were still a few surprises in store for HPC hardware aficionados. Read more…

By Tiffany Trader

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