DOE Argonne Researchers Develop AI Tools to Improve Engine Efficiencies

September 11, 2019

September 11, 2019 — Automotive manufacturers are facing an ever-increasing demand to deliver better engine performance, fuel economy and reduced emissions. Achieving these goals, however, is a daunting task.

Researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory are developing the deep learning framework MaLTESE (Machine Learning Tool for Engine Simulations and Experiments) to meet the challenge.

During the course of our daily commute, our engines take a real licking, given the roller coaster ride of acceleration, deceleration and hard stops. Individual driving habits, along with road and weather conditions, also exact a toll.

Vehicle manufacturers are constantly researching new approaches to optimize engine operation under these diverse conditions. And with over 20 different parameters affecting fuel economy and emissions, determining the right approach can prove slow and expensive.

But what if high-performance computing (HPC) and machine learning tools could sift through innumerable parameter combinations and predict outcomes for the commutes of thousands of drivers in real time?

Utilizing supercomputing resources at the Argonne Leadership Computing Facility (ALCF), a DOE Office of Science User Facility, Argonne researchers Shashi Aithal and Prasanna Balaprakash are developing MaLTESE with autonomous — or self-driving — and cloud-connected vehicles in mind. But first they hope the framework can be used to develop a manufacturer-like onboard system that combines the power of HPC and machine learning for a new class of real-time adaptive learning and controls.

In order to investigate the impact of diverse driving and engine operating conditions on engine performance and emissions, they used MaLTESE to simulate a typical 25-minute drive cycle of 250,000 vehicles, the approximate traffic flow of four major Chicago freeways during rush hour.

Using nearly the full capacity of the ALCF’s Theta system — one of the world’s most powerful supercomputers — the simulations were completed in less than 15 minutes, less than the time it takes to actually make the drive.

Currently, completing a high-fidelity simulation of just one engine cycle requires several days, even on a large supercomputer, as a typical drive cycle, or commute, has thousands of different engine cycles.

It’s a very precise computational fluid dynamics model that takes a lot of computing hours to run and get an output,” says Balaprakash. ​For the given driving conditions and driving behavior, we want to know a multitude of things, like nitrogen oxide and carbon emissions, and efficiency. Simulating that takes a long time.”

But Aithal had previously developed a physics-based real-time engine simulator called pMODES (parallel Multi-fuel Otto Diesel Engine Simulator) that not only runs much faster than traditional engine modeling tools, but can concurrently simulate the performance and emissions of thousands of drive cycles. A high-impact tool for drive simulation on leadership-class machines, pMODES won the HPC Innovation Award in 2015 by IDC Research (now Hyperion research).

MaLTESE was the merging of Aithal’s pMODES with the simulation-driven deep-learning tools being researched by Balaprakash.

The engine simulation outputs from pMODES are used to train a deep neural network to ​learn” how driving conditions and engine/transmission design affects the vehicle’s performance and emissions. The trained neural network can then predict the engine performance and emissions for a set of inputs in microseconds, putting on-board real-time adaptive control within the realm of possibility.

Simulation-driven machine learning is ideally suited for applications with multiple inputs and multiple outputs requiring large HPC resources, such as in drive-cycle analyses” says Balaprakash. ​These tools can be trained with a relatively small subset of the vast parameter space and then be used to make accurate predictions about other scenarios without the need for actually conducting the simulations.”

The team’s simulation on Theta is considered the single largest drive-cycle simulation conducted concurrently on a leadership-class supercomputer in real time and also the first machine learning-based prediction of drive-cycle characteristics of thousands of cars on city roads and freeways during rush hour.

The MaLTESE effort is a great example of how Argonne supercomputing resources enable researchers to combine large-scale simulations with machine learning methods in the development of novel tools for real-world applications, such as engine design and autonomous vehicle technologies,” says ALCF Director Michael Papka.

The research team’s findings were presented at the ISC High Performance conference held in Frankfurt, Germany, in June 2019.

MaLTESE has the potential to be a disruptive technology aimed at simulating and learning critical information about engine performance, emissions and vehicle dynamics in real time”, says Aithal. ​MaLTESE could lead to a rapid paradigm shift in the use of HPC in the design and optimization and real-time control of automotive-features with far-reaching implications for autonomous and connected vehicles.”

Balaprakash’s research was supported in part by DOE’s 2018 Early Career Award funded by the Advanced Scientific Computing Research program within the DOE Office of Science. This project’s use of ALCF computing resources were allocated through the ALCF’s Director’s Discretionary Program.

About Argonne National Laboratory

Argonne National Laboratory seeks solutions to pressing national problems in science and technology. The nation’s first national laboratory, Argonne conducts leading-edge basic and applied scientific research in virtually every scientific discipline. Argonne researchers work closely with researchers from hundreds of companies, universities, and federal, state and municipal agencies to help them solve their specific problems, advance America’s scientific leadership and prepare the nation for a better future. With employees from more than 60 nations, Argonne is managed by UChicago Argonne, LLC for the U.S. Department of Energy’s Office of Science.

About the U.S. Department of Energy’s Office of Science 

The U.S. Department of Energy’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States and is working to address some of the most pressing challenges of our time. For more information, visit https://energy.gov/science


Source: John Spizzirri, Argonne National Laboratory 

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!

When in Rome: AMD Announces New Epyc CPU for HPC, Server and Cloud Wins

September 18, 2019

Where else but Rome could AMD hold the official Europe launch party for its second generation of Epyc microprocessors, codenamed Rome. Today, AMD did just that announcing key server wins, important cloud provider wins Read more…

By John Russell

Dell’s AMD-Powered Server Line Targets High-End Jobs

September 17, 2019

Dell Technologies rolled out five new servers this week based on AMD’s latest Epyc processor that are geared toward data-driven workloads running on increasingly popular multi-cloud platforms as well as in the HPC data Read more…

By George Leopold

Cerebras to Supply DOE with Wafer-Scale AI Supercomputing Technology

September 17, 2019

Cerebras Systems, which debuted its wafer-scale AI silicon at Hot Chips last month, has entered into a multi-year partnership with Argonne National Laboratory and Lawrence Livermore National Laboratory as part of a larger collaboration with the U.S. Department of Energy... Read more…

By Tiffany Trader

AWS Solution Channel

A Guide to Discovering the Best AWS Instances and Configurations for Your HPC Workload

The flexibility and heterogeneity of HPC cloud services provide a welcome contrast to the constraints of on-premises HPC. Every HPC configuration is potentially accessible to any given workload in a well-resourced cloud HPC deployment, with vast scalability to spin up as much compute as that workload demands in any given moment. Read more…

HPE Extreme Performance Solutions

Intel FPGAs: More Than Just an Accelerator Card

FPGA (Field Programmable Gate Array) acceleration cards are not new, as they’ve been commercially available since 1984. Typically, the emphasis around FPGAs has centered on the fact that they’re programmable accelerators, and that they can truly offer workload specific hardware acceleration solutions without requiring custom silicon. Read more…

IBM Accelerated Insights

Rumors of My Death Are Still Exaggerated: The Mainframe

[Connect with Spectrum users and learn new skills in the IBM Spectrum LSF User Community.]

As of 2017, 92 of the world’s top 100 banks used mainframes. Read more…

Better Scientific Software: Turn Your Passion into Cash

September 13, 2019

Do you know your way around scientific software and programming? You think you can contribute to the community by making scientific software better? If so, then the Better Scientific Software (BSSW) organization wants yo Read more…

By Dan Olds

When in Rome: AMD Announces New Epyc CPU for HPC, Server and Cloud Wins

September 18, 2019

Where else but Rome could AMD hold the official Europe launch party for its second generation of Epyc microprocessors, codenamed Rome. Today, AMD did just that Read more…

By John Russell

Cerebras to Supply DOE with Wafer-Scale AI Supercomputing Technology

September 17, 2019

Cerebras Systems, which debuted its wafer-scale AI silicon at Hot Chips last month, has entered into a multi-year partnership with Argonne National Laboratory and Lawrence Livermore National Laboratory as part of a larger collaboration with the U.S. Department of Energy... Read more…

By Tiffany Trader

IDAS: ‘Automagic’ HPC With Training Wheels

September 12, 2019

High-performance computing (HPC) for research is notorious for having steep barriers to entry. For this reason, high-tech disciplines were early adopters, have Read more…

By Elizabeth Leake

Univa Brings Cloud Automation to Slurm Users with Navops Launch 2.0

September 11, 2019

Univa, the company behind Grid Engine, announced today its HPC cloud-automation platform NavOps Launch will support the popular open-source workload scheduler Slurm. With the release of NavOps Launch 2.0, “Slurm users will have access to the same cloud automation capabilities... Read more…

By Tiffany Trader

When Dense Matrix Representations Beat Sparse

September 9, 2019

In our world filled with unintended consequences, it turns out that saving memory space to help deal with GPU limitations, knowing it introduces performance pen Read more…

By James Reinders

Eyes on the Prize: TACC’s Frontera Quickly Ramps up Science Agenda

September 9, 2019

Announced a year ago and officially launched a week ago, the Texas Advanced Computing Center’s Frontera – now the fastest academic supercomputer (~25 petefl Read more…

By John Russell

Quantum Roundup: IBM Goes to School, Delft Tackles Networking, Rigetti Updates

September 5, 2019

IBM today announced a new open source quantum ‘textbook’, a series of quantum education videos, and plans to expand its nascent quantum hackathon program. L Read more…

By John Russell

DARPA Looks to Propel Parallelism

September 4, 2019

As Moore’s law runs out of steam, new programming approaches are being pursued with the goal of greater hardware performance with less coding. The Defense Advanced Projects Research Agency is launching a new programming effort aimed at leveraging the benefits of massive distributed parallelism with less sweat. Read more…

By George Leopold

High Performance (Potato) Chips

May 5, 2006

In this article, we focus on how Procter & Gamble is using high performance computing to create some common, everyday supermarket products. Tom Lange, a 27-year veteran of the company, tells us how P&G models products, processes and production systems for the betterment of consumer package goods. Read more…

By Michael Feldman

Supercomputer-Powered AI Tackles a Key Fusion Energy Challenge

August 7, 2019

Fusion energy is the Holy Grail of the energy world: low-radioactivity, low-waste, zero-carbon, high-output nuclear power that can run on hydrogen or lithium. T Read more…

By Oliver Peckham

AMD Verifies Its Largest 7nm Chip Design in Ten Hours

June 5, 2019

AMD announced last week that its engineers had successfully executed the first physical verification of its largest 7nm chip design – in just ten hours. The AMD Radeon Instinct Vega20 – which boasts 13.2 billion transistors – was tested using a TSMC-certified Calibre nmDRC software platform from Mentor. Read more…

By Oliver Peckham

TSMC and Samsung Moving to 5nm; Whither Moore’s Law?

June 12, 2019

With reports that Taiwan Semiconductor Manufacturing Co. (TMSC) and Samsung are moving quickly to 5nm manufacturing, it’s a good time to again ponder whither goes the venerable Moore’s law. Shrinking feature size has of course been the primary hallmark of achieving Moore’s law... Read more…

By John Russell

DARPA Looks to Propel Parallelism

September 4, 2019

As Moore’s law runs out of steam, new programming approaches are being pursued with the goal of greater hardware performance with less coding. The Defense Advanced Projects Research Agency is launching a new programming effort aimed at leveraging the benefits of massive distributed parallelism with less sweat. Read more…

By George Leopold

Cray Wins NNSA-Livermore ‘El Capitan’ Exascale Contract

August 13, 2019

Cray has won the bid to build the first exascale supercomputer for the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laborator Read more…

By Tiffany Trader

AMD Launches Epyc Rome, First 7nm CPU

August 8, 2019

From a gala event at the Palace of Fine Arts in San Francisco yesterday (Aug. 7), AMD launched its second-generation Epyc Rome x86 chips, based on its 7nm proce Read more…

By Tiffany Trader

Nvidia Embraces Arm, Declares Intent to Accelerate All CPU Architectures

June 17, 2019

As the Top500 list was being announced at ISC in Frankfurt today with an upgraded petascale Arm supercomputer in the top third of the list, Nvidia announced its Read more…

By Tiffany Trader

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour

CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
GOOGLE
GOOGLE
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
VERNE GLOBAL
VERNE GLOBAL

Ayar Labs to Demo Photonics Chiplet in FPGA Package at Hot Chips

August 19, 2019

Silicon startup Ayar Labs continues to gain momentum with its DARPA-backed optical chiplet technology that puts advanced electronics and optics on the same chip Read more…

By Tiffany Trader

Top500 Purely Petaflops; US Maintains Performance Lead

June 17, 2019

With the kick-off of the International Supercomputing Conference (ISC) in Frankfurt this morning, the 53rd Top500 list made its debut, and this one's for petafl Read more…

By Tiffany Trader

A Behind-the-Scenes Look at the Hardware That Powered the Black Hole Image

June 24, 2019

Two months ago, the first-ever image of a black hole took the internet by storm. A team of scientists took years to produce and verify the striking image – an Read more…

By Oliver Peckham

Cray – and the Cray Brand – to Be Positioned at Tip of HPE’s HPC Spear

May 22, 2019

More so than with most acquisitions of this kind, HPE’s purchase of Cray for $1.3 billion, announced last week, seems to have elements of that overused, often Read more…

By Doug Black and Tiffany Trader

Chinese Company Sugon Placed on US ‘Entity List’ After Strong Showing at International Supercomputing Conference

June 26, 2019

After more than a decade of advancing its supercomputing prowess, operating the world’s most powerful supercomputer from June 2013 to June 2018, China is keep Read more…

By Tiffany Trader

Qualcomm Invests in RISC-V Startup SiFive

June 7, 2019

Investors are zeroing in on the open standard RISC-V instruction set architecture and the processor intellectual property being developed by a batch of high-flying chip startups. Last fall, Esperanto Technologies announced a $58 million funding round. Read more…

By George Leopold

Intel Confirms Retreat on Omni-Path

August 1, 2019

Intel Corp.’s plans to make a big splash in the network fabric market for linking HPC and other workloads has apparently belly-flopped. The chipmaker confirmed to us the outlines of an earlier report by the website CRN that it has jettisoned plans for a second-generation version of its Omni-Path interconnect... Read more…

By Staff report

Intel Debuts Pohoiki Beach, Its 8M Neuron Neuromorphic Development System

July 17, 2019

Neuromorphic computing has received less fanfare of late than quantum computing whose mystery has captured public attention and which seems to have generated mo Read more…

By John Russell

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