High Performance (Potato) Chips

By Michael Feldman

May 5, 2006

“I’m going to be talking about things that are very familiar to people,” said Tom Lange, Director of Modeling and Simulation at Procter & Gamble (P&G).

Not the kind of introduction you normally think of when someone speaks about high performance computing applications. But this is exactly what Tom Lange talked about at the High Performance Computing and Communications (HPCC) Conference in Newport, Rhode Island a few weeks ago. His presentation was titled “The Aerodynamics of Pringles.”

Tom Lange has spent over 27 years at Procter & Gamble, modeling products, processes and production systems — everything from how the aerodynamics of potato chips optimizes production to how baby size affects diaper leakage. Although P&G has really only used high performance computing for the last 10 years or so, its origins go back to the late 70s.

“When I joined Procter & Gamble in 1978, we had high-end IBM 360/370 kinds of computers that we used to solve statistics problems,” said Lange. “Our first finite element analysis kind of problem — something that would look more familiar to a supercomputing person today — we solved using a Boeing computer in the middle of the 1980s. So our exploration of the use of simulations to improve our ability to innovate for the consumer is a legacy that is not just a few years old, but in fact more like 15 years old.”

Today, P&G has a fairly typical setup for commercial users of high performance computing. Lange said they have a heterogeneous computing environment — a shared memory SGI Altix system and a multi-hundred-node cluster. Choosing which system to use depends on their suitability for the specific type of modeling/simulation application.

As far as software goes, P&G gets its codes from a variety of sources. They use software packages from ISVs like Abacus, Fluent and LS-Dyna. Most of P&G’s proprietary code is implemented with user-defined functions within these packages. Lange calls this his “commercial-plus” strategy. At P&G, they have not attempted to maintain internal codes.

P&G also uses some national laboratory codes from both LANL and Sandia National Labs. “The same weapons code used at Los Alamos for more sophisticated purposes is used for combustion code in automotive applications and at P&G for paper products manufacturing,” said Lange.

Procter & Gamble tells its story

Unlike its competitors, P&G’s been publicizing how it uses high performance computing technology for a few years now. Other companies have been much more reticent to share their HPC story with the masses. Even Lange admits this story would not have told at P&G in the 1980s. But the nature of product manufacturing has changed.

“We’re in a global competition for ideas,” said Lange. “There’s no illusion at Procter and Gamble that it’s the only place where smart things happen. Since that illusion is not there, our willingness to say what we do know gives us the hope we’ll learn from others. If we’re just sitting in the back hiding, not saying anything, that doesn’t improve our innovation.”

Procter & Gamble does appear to have a more strategic focus on using HPC technology than its competitors. Lange’s position — the director of modeling and simulation — may be hard to find at other companies that produce package goods. Although modeling may have been used to help with product and package design at P&G ten or fifteen years ago, it wasn’t seen as a critical asset. But today, Lange believes there is an increasing awareness to use this technology to develop and improve products. This mirrors what has happened in other sectors — defense, electronics, automotive, aerospace, oil & gas — in the last decade or so.

Lange believes his willingness to speak at conferences like HPCC helps him connect with others in government and industry that deal with similar types of problems. He is hoping to develop some good relationships at the conference, leading to possible future collaborations. Lange uses events such as these to get to know his counterparts in other organizations.

“I know my counterparts at Chrysler, I know my counterparts at Dreamworks, I know my counterparts at Morgan-Stanley,” said Lange. “I would have never met those individuals if I hadn’t been involved in things like [HPCC]. In a lot of ways they all have similar jobs to mine. They’re trying to bring computing to their innovation process.”

Lange believes that collaboration between the defense, automotive industry, and package goods industry is quite possible. For example, P&G models many of the properties of skin to develop the interaction of its lotion products. Those models could be relevant for a crash test simulation at Ford Motor Company or a battlefield armor protection simulation for the Army.

“In my world I’m worried about wrinkles and freckles,” said Lange. “I’m just trying to make everyone’s life just a little better. But the science and engineering of making everyone’s life a little better has an amazing similarity to what are some of the more complex problems in safety and defense.”

High Performance Pringles

In general, Procter and Gamble use high performance computing modeling to design consumer package goods for a variety of its products: Ivory, Pringles, Charmin, Downy, Tide, Crest, Mr. Clean, Pampers, and a whole range of Hugo Boss products. A fairly recent success story is the Folgers Coffee plastic canister, which features the so-called “Aroma Seal.”

“There’s a lot of complex science and engineering associated with that particular container,” said Lange.

He explains that structural integrity is especially important for hermetically sealed packages. This type of container must be able to withstand pressure changes in elevation when they’re being transported — for example, during shipping, when the product is being driven over 11,000-foot mountain passes. Metal containers are very resistant pressure changes. But metal has drawbacks in maintaining the flavor profiles of foods, such as coffee, whose aroma is a result of its volatile oils. Metal does not react well with those volatile oils, so the coffee flavor tends to degrade over time.

Plastic, on the other hand, is better at preserving the coffee flavor profile. However plastic is not as good at maintaining its structural integrity when undergoing pressure changes during transport. Lange said this can be overcome if you just make the plastic really thick, but this is not very practical from a consumer acceptance and environmental point of view. So the challenge was to design a plastic container that would be both strong and practical for the consumer. For this, Procter and Gamble had to resort to sophisticated computer-aided engineering.

“That plastic coffee canister — the Aroma Seal package — would not exist without modeling,” said Lange. “Packaging, in general, is where this [modeling] gets applied — whether you’re talking about a Tide bottle or any of our liquid products.”

At P&G, product modeling is used to design a range of properties associated with a package, including its manufacturability, its strength and it resistance to leakage. In some cases, modeling is used to create more efficient packaging, so that fewer raw materials are used. This benefits both the manufacturer, because it is less expensive to produce, and the consumer, because its lighter, more compact and friendlier to the environment.

According to Lange, their paper products, including disposable diapers, toilet paper and paper towels is another area where a lot of modeling takes place. Also, substrate-based products such as Swiffer, Bounce, Thermocare have also benefited from high performance computing, employing chemoinformatics and molecular mesoscale modeling to predict the behavior of liquid solutions. Lange said that none of these products would be on the store shelves without modeling.

And then there’s Pringles. One of the reasons the aerodynamics of Pringles is so important is because the chips are being produced so quickly that they are practically flying down the production line.

“We make them very, very, very fast,” said Lange. “We make them fast enough so that in their transport, the aerodynamics are relevant. If we make them too fast, they fly where we don’t want them to, which is normally into a big pile somewhere. And that’s bad.”

Lange notes that the aerodynamics of chips is also important for food processing reasons. In this case, the aerodynamic properties combine with the food engineering issues, such as fluid flow interactions with the steam and oil as the chips are being cooked and seasoned.

Future Applications

Lange thinks that he will be able to use more advanced codes, such as human biomechanical modeling, on next-generation computers. At P&G, he would like to apply biomechanical modeling to design more user-friendly packaging. To the degree Procter and Gamble’s products interface better with the full range of humanity, the more likely he’s going to able to deliver a preferred product in the marketplace.

Lange describes one possible application of this from his own experience. He said he noticed that his mother-in-law, who has arthritis, leaves tops ajar or the caps off on a variety of containers around her home, because it’s too painful for her to continually open and close them.

“It’s a classic engineering dilemma, said Lange. “How do I make something that never leaks but opens easily? Introducing the human into this, in a full biomechanical way, is a complicated problem. It puts a huge demand on computing.”

Lange said that if they had more computing power, they could also perform much finer-grained molecular modeling. For example, they could simulate the nanoscale behavior of liquids. With this capability they would be able to predict the stability and opacity properties of different liquid solutions. Today he can only address those problems with very simple mesoscale representations.

Lange thinks it’s a shame when he occasionally hears his counterparts in the aerospace and automotive sectors say their systems are fast enough today — that no more computing power is really needed. He believes there are problems in all engineering domains that have yet to be addressed because of a lack of computing capability.

“My appetite for computing is insatiable,” admitted Lange. “For every factor of ten that Moore’s Law gives me, I can make use of every bit of it!”

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!

Hedge Funds (with Supercomputing help) Rank First Among Investors

May 22, 2017

In case you didn’t know, The Quants Run Wall Street Now, or so says a headline in today’s Wall Street Journal. Quant-run hedge funds now control the largest Read more…

By John Russell

IBM, D-Wave Report Quantum Computing Advances

May 18, 2017

IBM said this week it has built and tested a pair of quantum computing processors, including a prototype of a commercial version. That progress follows an an Read more…

By George Leopold

PRACEdays 2017 Wraps Up in Barcelona

May 18, 2017

Barcelona has been absolutely lovely; the weather, the food, the people. I am, sadly, finishing my last day at PRACEdays 2017 with two sessions: an in-depth loo Read more…

By Kim McMahon

US, Europe, Japan Deepen Research Computing Partnership

May 18, 2017

On May 17, 2017, a ceremony was held during the PRACEdays 2017 conference in Barcelona to announce the memorandum of understanding (MOU) between PRACE in Europe Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Exploring the Three Models of Remote Visualization

The explosion of data and advancement of digital technologies are dramatically changing the way many companies do business. With the help of high performance computing (HPC) solutions and data analytics platforms, manufacturers are developing products faster, healthcare providers are improving patient care, and energy companies are improving planning, exploration, and production. Read more…

NSF, IARPA, and SRC Push into “Semiconductor Synthetic Biology” Computing

May 18, 2017

Research into how biological systems might be fashioned into computational technology has a long history with various DNA-based computing approaches explored. N Read more…

By John Russell

DOE’s HPC4Mfg Leads to Paper Manufacturing Improvement

May 17, 2017

Papermaking ranks third behind only petroleum refining and chemical production in terms of energy consumption. Recently, simulations made possible by the U.S. D Read more…

By John Russell

PRACEdays 2017: The start of a beautiful week in Barcelona

May 17, 2017

Touching down in Barcelona on Saturday afternoon, it was warm, sunny, and oh so Spanish. I was greeted at my hotel with a glass of Cava to sip and treated to a Read more…

By Kim McMahon

NSF Issues $60M RFP for “Towards a Leadership-Class” System

May 16, 2017

In case you missed it, the National Science Foundation issued the request for proposals (RFP) for the next ‘Towards a Leadership-Class Computing Facility – Read more…

By John Russell

Cray Offers Supercomputing as a Service, Targets Biotechs First

May 16, 2017

Leading supercomputer vendor Cray and datacenter/cloud provider the Markley Group today announced plans to jointly deliver supercomputing as a service. The init Read more…

By John Russell

HPE’s Memory-centric The Machine Coming into View, Opens ARMs to 3rd-party Developers

May 16, 2017

Announced three years ago, HPE’s The Machine is said to be the largest R&D program in the venerable company’s history, one that could be progressing tow Read more…

By Doug Black

What’s Up with Hyperion as It Transitions From IDC?

May 15, 2017

If you’re wondering what’s happening with Hyperion Research – formerly the IDC HPC group – apparently you are not alone, says Steve Conway, now senior V Read more…

By John Russell

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

HPE Launches Servers, Services, and Collaboration at GTC

May 10, 2017

Hewlett Packard Enterprise (HPE) today launched a new liquid cooled GPU-driven Apollo platform based on SGI ICE architecture, a new collaboration with NVIDIA, a Read more…

By John Russell

IBM PowerAI Tools Aim to Ease Deep Learning Data Prep, Shorten Training 

May 10, 2017

A new set of GPU-powered AI software announced by IBM today brings automation to many of the tedious, time consuming and complex aspects of AI project on-rampin Read more…

By Doug Black

Bright Computing 8.0 Adds Azure, Expands Machine Learning Support

May 9, 2017

Bright Computing, long a prominent provider of cluster management tools for HPC, today released version 8.0 of Bright Cluster Manager and Bright OpenStack. The Read more…

By John Russell

Microsoft Azure Will Debut Pascal GPU Instances This Year

May 8, 2017

As Nvidia's GPU Technology Conference gets underway in San Jose, Calif., Microsoft today revealed plans to add Pascal-generation GPU horsepower to its Azure clo Read more…

By Tiffany Trader

Quantum Bits: D-Wave and VW; Google Quantum Lab; IBM Expands Access

March 21, 2017

For a technology that’s usually characterized as far off and in a distant galaxy, quantum computing has been steadily picking up steam. Just how close real-wo Read more…

By John Russell

Trump Budget Targets NIH, DOE, and EPA; No Mention of NSF

March 16, 2017

President Trump’s proposed U.S. fiscal 2018 budget issued today sharply cuts science spending while bolstering military spending as he promised during the cam Read more…

By John Russell

Google Pulls Back the Covers on Its First Machine Learning Chip

April 6, 2017

This week Google released a report detailing the design and performance characteristics of the Tensor Processing Unit (TPU), its custom ASIC for the inference Read more…

By Tiffany Trader

HPC Compiler Company PathScale Seeks Life Raft

March 23, 2017

HPCwire has learned that HPC compiler company PathScale has fallen on difficult times and is asking the community for help or actively seeking a buyer for its a Read more…

By Tiffany Trader

Nvidia Responds to Google TPU Benchmarking

April 10, 2017

Last week, Google reported that its custom ASIC Tensor Processing Unit (TPU) was 15-30x faster for inferencing workloads than Nvidia's K80 GPU (see our coverage Read more…

By Tiffany Trader

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

Since our first formal product releases of OSPRay and OpenSWR libraries in 2016, CPU-based Software Defined Visualization (SDVis) has achieved wide-spread adopt Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a ne Read more…

By Tiffany Trader

Facebook Open Sources Caffe2; Nvidia, Intel Rush to Optimize

April 18, 2017

From its F8 developer conference in San Jose, Calif., today, Facebook announced Caffe2, a new open-source, cross-platform framework for deep learning. Caffe2 is Read more…

By Tiffany Trader

Leading Solution Providers

Nvidia’s Mammoth Volta GPU Aims High for AI, HPC

May 10, 2017

At Nvidia's GPU Technology Conference (GTC17) in San Jose, Calif., this morning, CEO Jensen Huang announced the company's much-anticipated Volta architecture a Read more…

By Tiffany Trader

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which w Read more…

By Tiffany Trader

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling Read more…

By Steve Campbell

MIT Mathematician Spins Up 220,000-Core Google Compute Cluster

April 21, 2017

On Thursday, Google announced that MIT math professor and computational number theorist Andrew V. Sutherland had set a record for the largest Google Compute Eng Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular Read more…

By John Russell

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu's Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural networ Read more…

By Tiffany Trader

US Supercomputing Leaders Tackle the China Question

March 15, 2017

As China continues to prove its supercomputing mettle via the Top500 list and the forward march of its ambitious plans to stand up an exascale machine by 2020, Read more…

By Tiffany Trader

DOE Supercomputer Achieves Record 45-Qubit Quantum Simulation

April 13, 2017

In order to simulate larger and larger quantum systems and usher in an age of "quantum supremacy," researchers are stretching the limits of today's most advance Read more…

By Tiffany Trader

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