F1 Team Finds Successful Formula in HPC

By Tiffany Trader

October 18, 2013

Formula1 racing is all about saving time. The team that competes the specified number of laps with the best time goes home with the trophy. Nowadays, winning on the racetrack begins in the datacenter.

To build the ultimate race car, every single part must be optimized for performance. Improvements in design may translate into tenths of a second being shaved from lap times, but those incremental gains add up. As a science, racing is all about manipulating aerodynamics to reduce drag. Back when supercomputers were the sole purview of government labs, this design work was done using physical prototypes and wind tunnel testing. It was a time-consuming and expensive endeavor. Now a great percentage of this work is done using high-performance computer clusters – it’s a faster and more precise discipline.

The Caterham F1 Team relies on a Dell HPC cluster to design its race cars. Thanks to recent enhancements, the cluster at the Leafield Technology Centre in Oxfordshire, England, can perform 10 billion calculations in about 12 hours, according to William Morrison, the Caterham IT infrastructure manager. The average home computer would take four to five months to do a similar amount of math.

The common practice today is for F1 teams to pursue computational fluid dynamics (CFD) in tandem with wind tunnel work. CFD relies on a technique called meshing, which breaks up the car’s surface area into a grid of smaller spaces – creating a virtual model of the car. The computer’s “wind tunnel” simulator will provide engineers with detailed information, including temperature, pressure, turbulence and velocity, for each unit in the mesh.

The computerized testing process is a tremendous time-saver, allowing the team’s engineers to try out hundreds or thousands of virtual parts without having to physically build a thing. Only the best candidates will be manufactured into actual parts.

The Caterham F1 engineering team recently figured out how to decrease the time of a typical job from about 17 hours to 12 hours using some enhancements to the model and the solving approach. Shaving those five hours took a few months of work of stripping down the model and rebuilding it. “We have a little group of about three people dedicated to improving this all the time,” notes Morrison.

Each job generates about 800 million pieces of individual data, which through further processing are transformed into a dataset that includes approximately eight videos, several graphs and a couple hundred pictures.

While there was originally some skepticism against virtual prototyping, the results of HPC won over converts. The digital design process is now central to F1 racing, and that’s definitely the case with the Caterham F1 Team operation. Without their Dell HPC cluster, design and development would come to a halt. The team’s engineers run their HPC cluster 24 hours a day, 365 days a year, and there’s always 10 and 20 jobs awaiting processing.

There are safety mechanisms and power backups in place to prevent downtime. The HPC system is monitored twice a day and individual nodes can be taken offline without affecting other jobs.

For the Caterham F1 team, their HPC system is too important to let something happen to it. “It’s not allowed any time off,” jokes Morrison.

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!

NSF Project Sets Up First Machine Learning Cyberinfrastructure – CHASE-CI

July 25, 2017

Earlier this month, the National Science Foundation issued a $1 million grant to Larry Smarr, director of Calit2, and a group of his colleagues to create a community infrastructure in support of machine learning research Read more…

By John Russell

DARPA Continues Investment in Post-Moore’s Technologies

July 24, 2017

The U.S. military long ago ceded dominance in electronics innovation to Silicon Valley, the DoD-backed powerhouse that has driven microelectronic generation for decades. With Moore's Law clearly running out of steam, the Read more…

By George Leopold

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in 2017 with scale-up production for enterprise datacenters and Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

HPE Servers Deliver High Performance Remote Visualization

Whether generating seismic simulations, locating new productive oil reservoirs, or constructing complex models of the earth’s subsurface, energy, oil, and gas (EO&G) is a highly data-driven industry. Read more…

Trinity Supercomputer’s Haswell and KNL Partitions Are Merged

July 19, 2017

Trinity supercomputer’s two partitions – one based on Intel Xeon Haswell processors and the other on Xeon Phi Knights Landing – have been fully integrated are now available for use on classified work in the Nationa Read more…

By HPCwire Staff

NSF Project Sets Up First Machine Learning Cyberinfrastructure – CHASE-CI

July 25, 2017

Earlier this month, the National Science Foundation issued a $1 million grant to Larry Smarr, director of Calit2, and a group of his colleagues to create a comm Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's out Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the com Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee Read more…

By Alex R. Larzelere

Women in HPC Luncheon Shines Light on Female-Friendly Hiring Practices

July 13, 2017

The second annual Women in HPC luncheon was held on June 20, 2017, during the International Supercomputing Conference in Frankfurt, Germany. The luncheon provid Read more…

By Tiffany Trader

Satellite Advances, NSF Computation Power Rapid Mapping of Earth’s Surface

July 13, 2017

New satellite technologies have completely changed the game in mapping and geographical data gathering, reducing costs and placing a new emphasis on time series Read more…

By Ken Chiacchia and Tiffany Jolley

Intel Skylake: Xeon Goes from Chip to Platform

July 13, 2017

With yesterday’s New York unveiling of the new “Skylake” Xeon Scalable processors, Intel made multiple runs at multiple competitive threats and strategic Read more…

By Doug Black

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

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

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

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

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

CPU-based Visualization Positions for Exascale Supercomputing

March 16, 2017

In this contributed perspective piece, Intel’s Jim Jeffers makes the case that CPU-based visualization is now widely adopted and as such is no longer a contrarian view, but is rather an exascale requirement. Read more…

By Jim Jeffers, Principal Engineer and Engineering Leader, Intel

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

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 the successor to Caffe, the deep learning framework developed by Berkeley AI Research and community contributors. Read more…

By Tiffany Trader

Leading Solution Providers

How ‘Knights Mill’ Gets Its Deep Learning Flops

June 22, 2017

Intel, the subject of much speculation regarding the delayed, rewritten or potentially canceled “Aurora” contract (the Argonne Lab part of the CORAL “ Read more…

By Tiffany Trader

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

Russian Researchers Claim First Quantum-Safe Blockchain

May 25, 2017

The Russian Quantum Center today announced it has overcome the threat of quantum cryptography by creating the first quantum-safe blockchain, securing cryptocurrencies like Bitcoin, along with classified government communications and other sensitive digital transfers. Read more…

By Doug Black

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 Engine (GCE) job. Sutherland ran the massive mathematics workload on 220,000 GCE cores using preemptible virtual machine instances. Read more…

By Tiffany Trader

Google Debuts TPU v2 and will Add to Google Cloud

May 25, 2017

Not long after stirring attention in the deep learning/AI community by revealing the details of its Tensor Processing Unit (TPU), Google last week announced the Read more…

By John Russell

Groq This: New AI Chips to Give GPUs a Run for Deep Learning Money

April 24, 2017

CPUs and GPUs, move over. Thanks to recent revelations surrounding Google’s new Tensor Processing Unit (TPU), the computing world appears to be on the cusp of Read more…

By Alex Woodie

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

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