How the iForge Cluster is Manufacturing Results for Big Industry

By Nicole Hemsoth

February 26, 2014

When one thinks of major manufacturing companies, including Boeing, Proctor and Gamble, John Deere, Caterpillar, Dow, GE and others, from a systems and software perspective, there is little doubt that the competitive edge lies in high performance computing. But for many of these companies, it’s not simply a matter of plugging engineering codes into high core-count, accelerated supercomputers to magically realize better results.

Finite element analysis, computational fluid dynamics and homegrown codes at the largest manufacturing companies have their own unique system needs—but tend to run inside daily workflows where experimentation with new architectures and approaches are pushed down the chain due to competing demands from across the organization. According to Merle Giles, who leads the private sector program and economic development initiatives at the National Center for Supercomputing Applications (NCSA), most of the common engineering applications tend to hum nicely at around 1000 cores. They don’t’ tend to require acceleration but do need major memory to handle decomposition and other critical elements.

So while Giles and his team at NCSA have access to Blue Waters, core counts and scientific application performance are secondary. For the users he’s targeting–those with commercial and mission-critical home-cooked engineering codes–such a massive resource might not have the specific appeal of another far smaller (but far more targeted) option: A pared down, but finely tuned cluster specifically built to address the experimental needs of the “power users” at leading manufacturing companies. Giles’ team has such a hardware resource…and they’re also able to collect the varied expertise across both NCSA and the University of Illinois to bring world class support to bear as well.

To put this difference between system needs in context, consider that memory-tied engineering codes on Blue Waters with its 64 GB of RAM on a single node might do reasonably well, but take a much smaller cluster, in this case, the iForge system that Giles and his team operate in the Digital Manufacturing Lab at NCSA, and these codes can sing through decomposition on 256 GB instead.

The iForge cluster has been benchmarked for common CFD and FEA applications against the mighty Blue Waters for confirmation—which has further bolstered Giles and teams’ mission to keep pushing the edges of what’s useful for the manufacturing companies they’re serving with their private cluster that’s reserved for the experimental “power users” from the big companies listed above. “We want to be complementary to Blue Waters, not redundant,” Giles explained.

If you haven’t heard of iForge, it’s because although it’s been around for the last three years (and churning a profit for Giles to pump directly into the program with more–and more interesting—cores) it’s not part of the more publicized publicly funded efforts one might expect out of a university or national lab/supercomputer center setting. You also haven’t seen it from any LINPACK or other publicized benchmarking runs. Giles says this is because it’s optimized for these users to test and deploy their mission-critical code using some of the newest hardware. For instance, iForge was one of the early recipients of Sandy Bridge when it was available and already sports one of the just-released new Intel Xeon E7 4890 15-core-based nodes–for now.

The goal is simple: let the power users from the high end of digital manufacturing hop on board to take new architectures for a spin, optimize their codes and evaluate them against their existing infrastructure to better understand upgrade/rip and replace ROIs without burdening their own in-house clusters. These users can take valuable lessons about how their code scales and operates, make choices and in turn, Giles and team can turn over valuable feedback to system vendors. Also, they can use these cores for production runs, which the team charges for and that keep the center profitable and support the endless cycle of refreshes and system expansion. And speaking of the system…

iforge_250We were able to receive a number of deep details about the evolution of iForge from Evan Burness, the Program Manager for the private sector and economic development program at NCSA. Evan narrated the journey of cutting-edge hardware for us, including details about their Intel (and for a while, Opteron) environment, which was slung together by Dell with DDN storage and QDR Infinibad. As Burness described:

“We started iForge in Q3 2011 with “Intel’s Westmere” (116 EP nodes, 3 EX nodes) and AMD’s “Magny Cours” (2 nodes) architectures. That system had 1,584 cores total. In 2012 we upgraded to Intel’s “Sandy Bridge” (128 EP nodes) architecture when it was released to market (Q3 2012), and at the same time  increased our AMD node count from 2 to 18, and upgraded the processors to “Interlagos” (Just like the CPU’s on Blue Waters). Through the upgrade, we increased the node count from 121 to 146, and the core count to 2,624.” As a side point, he’s counting 4 Opteron processors in a node as accounting for 32 cores, rather than the 64 AMD might cite since the the “16 core” Opteron chips based on Interlagos and Abu Dhabi only have 8 floating point units, which is what’s really important for their work.

These constant upgrades were part of the master plan for the project—and will continue to be so since the goal is to continue offering new architectures for manufacturing users to test and explore.

Burness says they intended to upgrade again in mid-2013 (this time through Intel’s early access program), but vendor delays pushed that back to January of 2014. At that time, they upgraded to Intel’s “Ivy Bridge” (144 EP nodes) line, and AMD’s “Abu Dhabi’ Line. The Ivy Bridge nodes indeed feature the 10-core variants (Xeon E5 2680 v2), with 96 of the nodes featuring 64 GB of RAM (for CFD) workloads and 48 featuring 256 GB of RAM (for finite element analysis) workloads.

“We also added one (1) Ivy Bridge-EX system directly from Intel, who saw iForge as a particularly good platform at which to throw this new technology given how industry brings real-world development and production problems to this system.” Burness explained. These only were released from Intel in December and January. iForge is now one of the precious few that we can get any details on that features 4 x 15-core Xeon E7 4890 CPUs for a total of 60 cores and 120 threads. Burness and team have also augmented the server with an extra 1.5 terabytes of memory and multiple Infiniband connections.

In addition, he said, they upgraded their network insofar as PCIe gen 3.0 on the Ivy Bridge nodes increased the usable bandwidth of our QDR Infiniband fabric from 25.6 Gb/sec to 32.0 Gb/sec, “all while maintaining the lowest possible latency (even lower than FDR).” Burness says that coupled with all of this, they’re also adding 8 instances of Windows and GUI’d Red Hat Linux in order to provide the “desktop computing” experience for users that need to do so much inside their engineering workflows to support batch processing HPC. “Here, think of the need to run CAD and CAM workloads at one’s computer and then send the files to an HPC cluster. Doing so becomes inherently tougher as the simulated models become more complex and the data sizes grow larger. Having one integrated environment for the entire workflow is a big productivity booster for our industry partners.”

Burness says that, “Throughout all 3 years of operation, iForge has been supported by a GPFS filesystem from IBM running on a DDN SFA-10000 storage system. We pack our storage servers with 192 GB of RAM/server in order to maximize the amount of caching/buffering to RAM, which can really improve performance for I/O intensive applications.” He noted that “A big part of the design focus is on producing a system every year that is as fast or faster than all but a very elite and small number of companies would be able to build and support for themselves (exceptions would General Electric, BP etc.).”

Giles put all of this in real-world terms by referencing a use case with one of the large manufacturers when they first received the early Sandy Bridges. He said that at time, many of their partners weren’t sure how to step up to Sandy Bridge, despite its promise (including AVX capability) for engineering applications. By allowing them to experiment and hit full production runs on the system, Giles says they were able to completely change their workflows, validate the usefulness of the architecture, and push their normal 128-core workflow into 256 core territory. This isn’t something they would have been able to do on their home machines, which are “artificially dumbed down” to support a broader, more policy-based approach to handling daily work.

This work on iForge will be all be overseen by by UI Labs, which is a separate nonprofit organization based out of the university, where it can better leverage academic resources and those found at NCSA as well.  This ties in with the announcement this week of a $70 million “grant” (which Giles defines more of a matching funding arrangement similar to NDEMC) for digital manufacturing. This Department of Defense-led project will drive additional matched funds on the order of around $250 million from a number of manufacturing companies and other institutions.

As Burness concluded, “The government funded model of a system that runs in the same configuration for 3-5 years is not good enough for our power users from industry, as they have an insatiable appetite for speed and performance. In addition, we do a lot in design process to ensure a much higher level of uptime than many other HPC systems. A big part of that is our use of the GPFS filesystem. Though it must be licensed and is not faster than Lustre, it is WAYYY more reliable and easier to administer. It’s a huge part of the reason we’re able to achieve 99% uptime on iForge, which is a reliability level that industry demands.”

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!

What’s New in HPC Research: September (Part 1)

September 18, 2018

In this new bimonthly feature, HPCwire will highlight newly published research in the high-performance computing community and related domains. From exascale to quantum computing, the details are here. Check back every Read more…

By Oliver Peckham

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and development. Among other things it would establish a National Quantu Read more…

By John Russell

Nvidia Accelerates AI Inference in the Datacenter with T4 GPU

September 14, 2018

Nvidia is upping its game for AI inference in the datacenter with a new platform consisting of an inference accelerator chip--the new Turing-based Tesla T4 GPU--and a refresh of its inference server software packaged as Read more…

By George Leopold

HPE Extreme Performance Solutions

Introducing the First Integrated System Management Software for HPC Clusters from HPE

How do you manage your complex, growing cluster environments? Answer that big challenge with the new HPC cluster management solution: HPE Performance Cluster Manager. Read more…

IBM Accelerated Insights

A Crystal Ball for HPC

People are notoriously bad at predicting the future.  This very much includes experts. In the Forbes article “Why Most Predictions Are So Bad” Philip Tetlock discusses the largest and best-known test of the accuracy of expert predictions which show that any experts would do better if they make random guesses. Read more…

NSF Highlights Expanded Efforts for Broadening Participation in Computing

September 13, 2018

Today, the Directorate of Computer and Information Science and Engineering (CISE) of the NSF released a letter highlighting the expansion of its broadening participation in computing efforts. The letter was penned by Jam Read more…

By Staff

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

Nvidia Accelerates AI Inference in the Datacenter with T4 GPU

September 14, 2018

Nvidia is upping its game for AI inference in the datacenter with a new platform consisting of an inference accelerator chip--the new Turing-based Tesla T4 GPU- Read more…

By George Leopold

DeepSense Combines HPC and AI to Bolster Canada’s Ocean Economy

September 13, 2018

We often hear scientists say that we know less than 10 percent of the life of the oceans. This week, IBM and a group of Canadian industry and government partner Read more…

By Tiffany Trader

Rigetti (and Others) Pursuit of Quantum Advantage

September 11, 2018

Remember ‘quantum supremacy’, the much-touted but little-loved idea that the age of quantum computing would be signaled when quantum computers could tackle Read more…

By John Russell

How FPGAs Accelerate Financial Services Workloads

September 11, 2018

While FSI companies are unlikely, for competitive reasons, to disclose their FPGA strategies, James Reinders offers insights into the case for FPGAs as accelerators for FSI by discussing performance, power, size, latency, jitter and inline processing. Read more…

By James Reinders

Update from Gregory Kurtzer on Singularity’s Push into FS and the Enterprise

September 11, 2018

Container technology is hardly new but it has undergone rapid evolution in the HPC space in recent years to accommodate traditional science workloads and HPC systems requirements. While Docker containers continue to dominate in the enterprise, other variants are becoming important and one alternative with distinctly HPC roots – Singularity – is making an enterprise push targeting advanced scale workload inclusive of HPC. Read more…

By John Russell

At HPC on Wall Street: AI-as-a-Service Accelerates AI Journeys

September 10, 2018

AIaaS – artificial intelligence-as-a-service – is the technology discipline that eases enterprise entry into the mysteries of the AI journey while lowering Read more…

By Doug Black

No Go for GloFo at 7nm; and the Fujitsu A64FX post-K CPU

September 5, 2018

It’s been a news worthy couple of weeks in the semiconductor and HPC industry. There were several HPC relevant disclosures at Hot Chips 2018 to whet appetites Read more…

By Dairsie Latimer

TACC Wins Next NSF-funded Major Supercomputer

July 30, 2018

The Texas Advanced Computing Center (TACC) has won the next NSF-funded big supercomputer beating out rivals including the National Center for Supercomputing Ap Read more…

By John Russell

IBM at Hot Chips: What’s Next for Power

August 23, 2018

With processor, memory and networking technologies all racing to fill in for an ailing Moore’s law, the era of the heterogeneous datacenter is well underway, Read more…

By Tiffany Trader

Requiem for a Phi: Knights Landing Discontinued

July 25, 2018

On Monday, Intel made public its end of life strategy for the Knights Landing "KNL" Phi product set. The announcement makes official what has already been wide Read more…

By Tiffany Trader

CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

August 14, 2018

An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learni Read more…

By Rob Farber

ORNL Summit Supercomputer Is Officially Here

June 8, 2018

Oak Ridge National Laboratory (ORNL) together with IBM and Nvidia celebrated the official unveiling of the Department of Energy (DOE) Summit supercomputer toda Read more…

By Tiffany Trader

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

By John Russell

AMD’s EPYC Road to Redemption in Six Slides

June 21, 2018

A year ago AMD returned to the server market with its EPYC processor line. The earth didn’t tremble but folks took notice. People remember the Opteron fondly Read more…

By John Russell

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

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17


AMD @ SC17


ASRock Rack @ SC17

ASRock Rack



DDN Storage @ SC17

DDN Storage

Huawei @ SC17


IBM @ SC17


IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17


Lenovo @ SC17


Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17


Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17


Tyan @ SC17


Univa @ SC17


Pattern Computer – Startup Claims Breakthrough in ‘Pattern Discovery’ Technology

May 23, 2018

If it weren’t for the heavy-hitter technology team behind start-up Pattern Computer, which emerged from stealth today in a live-streamed event from San Franci Read more…

By John Russell

Sandia to Take Delivery of World’s Largest Arm System

June 18, 2018

While the enterprise remains circumspect on prospects for Arm servers in the datacenter, the leadership HPC community is taking a bolder, brighter view of the x86 server CPU alternative. Amongst current and planned Arm HPC installations – i.e., the innovative Mont-Blanc project, led by Bull/Atos, the 'Isambard’ Cray XC50 going into the University of Bristol, and commitments from both Japan and France among others -- HPE is announcing that it will be supply the United States National Nuclear Security Administration (NNSA) with a 2.3 petaflops peak Arm-based system, named Astra. Read more…

By Tiffany Trader

D-Wave Breaks New Ground in Quantum Simulation

July 16, 2018

Last Friday D-Wave scientists and colleagues published work in Science which they say represents the first fulfillment of Richard Feynman’s 1982 notion that Read more…

By John Russell

Intel Pledges First Commercial Nervana Product ‘Spring Crest’ in 2019

May 24, 2018

At its AI developer conference in San Francisco yesterday, Intel embraced a holistic approach to AI and showed off a broad AI portfolio that includes Xeon processors, Movidius technologies, FPGAs and Intel’s Nervana Neural Network Processors (NNPs), based on the technology it acquired in 2016. Read more…

By Tiffany Trader

Intel Announces Cooper Lake, Advances AI Strategy

August 9, 2018

Intel's chief datacenter exec Navin Shenoy kicked off the company's Data-Centric Innovation Summit Wednesday, the day-long program devoted to Intel's datacenter Read more…

By Tiffany Trader

TACC’s ‘Frontera’ Supercomputer Expands Horizon for Extreme-Scale Science

August 29, 2018

The National Science Foundation and the Texas Advanced Computing Center announced today that a new system, called Frontera, will overtake Stampede 2 as the fast Read more…

By Tiffany Trader

GPUs Power Five of World’s Top Seven Supercomputers

June 25, 2018

The top 10 echelon of the newly minted Top500 list boasts three powerful new systems with one common engine: the Nvidia Volta V100 general-purpose graphics proc Read more…

By Tiffany Trader

The Machine Learning Hype Cycle and HPC

June 14, 2018

Like many other HPC professionals I’m following the hype cycle around machine learning/deep learning with interest. I subscribe to the view that we’re probably approaching the ‘peak of inflated expectation’ but not quite yet starting the descent into the ‘trough of disillusionment. This still raises the probability that... Read more…

By Dairsie Latimer

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