Next-generation aerospace modeling and simulation: benchmarking Amazon Web Services High Performance Computing services

By Amazon Web Services

September 16, 2020

The aerospace industry has been using Computational Fluid Dynamics (CFD) for decades to create and optimize designs digitally, from the largest passenger planes and fighter jets to gliders and drones. CFD allows them to get to market faster and at a lower development cost, reducing, for instance, expensive wind tunnel testing.

But performance and cost-effectiveness need to get even tighter. By 2050, commercial aircraft will face even more stringent environmental legislation, which necessitates continuously improving aircraft performance. As such, engineers are increasingly using more complex and higher fidelity CFD simulations as well as digital twinning to reduce design times.

Running these simulations requires a large computing power and as the simulation complexity increases so does the demand of High-Performance Computing (HPC) systems. This trend is set to continue, and aerospace companies are exploring the next generation of CFD tools and the HPC systems to run them.

In the last few years, the advances in cloud computing infrastructure has meant that more and more workloads that previously required on-premises HPC can now run on the cloud. However, there is still the perception that large scale workloads require an on-premises HPC resource. In this article we explore this and test various AWS HPC performance options for a large scale industrial CFD test case.

This article is a summary of the study based on the tests carried out as part of the Aerospace Cloud Services project, funded by Innovate UK and the Aerospace Technology Institute.

Authors of the original white paper: Mike Turner, CTO at Zenotech, Neil Ashton, Principal Solution Architect CFD and AWS, and Gilles Tourpe, Senior Go-to-Market Specialist at AWS.

The CFD challenge

To test the AWS infrastructure, we used the zCFD solver from Zenotech. Zenotech is a computational engineering company based in Bristol, UK, that has extensive experience working in the aerospace industry and offers on-demand cloud HPC via their EPIC product.

XRF1 Simulation Challenge supplied by Airbus was used as a test case. XRF1 is a generic non-production aircraft design but represents the kind of simulations that Airbus performs to produce a real aircraft. Airbus has extensive wind tunnel result data for XRF1 and has released the model to partners to support the verification and validation of CFD codes.

The combination of zCFD and XRF1 allowed us to run the benchmarks in a way that replicates runs that are typically used in an aerospace production design cycle.

To quantify the performance of AWS infrastructure we compared it with an on-premises Cray CS400 cluster, configured specifically for HPC tasks. It is one of several types of HPC clusters that large organizations have on-premise.

AWS HPC Configuration

To create an HPC cluster in AWS the following services were used:

The AWS infrastructure was set up by Zenotech and managed via Zenotec’s EPIC platform, which provides access to a variety of HPC systems, both cloud-based and a range of specialist supercomputing providers.

Scaling Performance

We ran the benchmarks on 3,600 CPU cores using a 149 million cell aircraft mesh and test results demonstrated that the AWS based infrastructure is capable of running a large aircraft CFD simulation at scale delivering performance that exceeds an on-premises HPC cluster.

The results below show how the runtime of the CFD solver scales with the number of CPU cores used. The “ideal” metric is where the performance scales linearly to the number of CPUs used, while at higher core counts this “ideal” scenario becomes more difficult as the communication between partitions starts to dominate the calculation time. The speed and bandwidth of the network interconnect also have a considerable impact on strong scaling.

The tests run with zCFD in three modes:

  • MPI: The code was run in pure MPI mode, one MPI process per CPU core and one thread per MPI process. This mode is the most network intensive as all processes can potentially communicate.
  • Hybrid: The code was run in hybrid MPI/OpenMP mode. In this case one MPI process is run per CPU socket and then one OpenMP thread per CPU core on that socket. So, for example a compute node with two 12 core CPUs would run two MPI processes each with 12 OpenMP threads. This mode is more efficient on the network as it reduces the number of components communicating.
  • GPU: Zenotech’s zCFD is capable of offloading the solve to GPUs via CUDA . To do this one MPI process is run per GPU on the system and the code detects the available GPUs and binds one MPI process to each GPU.

The solver was also compiled for arm64 to benchmark the Graviton2 arm64-based CPUs.

How did the AWS cluster do?

The chart below illustrates the strong scaling results for the Amazon EC2 c5n.18xlarge instance type. It shows a comparison of the scaling with and without the use of EFA for communications, running zCFD in Hybrid mode with two MPI processes on each node and 18 OpenMP threads per MPI process.

As shown above, the scaling without ETA is still very strong, with around 75% efficiency at 100 nodes/3600 cores. This is over the standard ENA based ethernet interfaces on those nodes using the libfabric TCP provider. Introduction of EFA improves metrics even further, with near linear scaling up to around 75 nodes and an efficiency of 87% at 100 nodes/3600 cores.

Some applications, legacy CFD codes in particular, are not capable of running in a hybrid mode and so we also ran our tests in full MPI mode; with 36 MPI processes per node and no OpenMP threads. As demonstrated in the chart below, the scaling for the MPI run drops off faster than the Hybrid run. This was expected due to the increased number of communication processes in the MPI run putting more load on the network. These results mirror those seen on the on-premises cluster.

How does it compare to the On-Premises Cluster?

The results from the AWS cluster look very promising. The chart below shows a comparison of a zCFD hybrid running on c5n.18xlarge with EFA enabled and the Infiniband connected on-premises cluster.

As demonstrated in the above chart, scaling on the AWS cluster is closer to “ideal” than the on-premises cluster. Even at 100 nodes we see 78% parallel efficiency, when compared to a single node, for the on-premises cluster versus 87% on the AWS cluster.

It is also useful to make a direct performance comparison. If we look at cycle time per compute node/instance, the AWS cluster is around 1.5x faster than the on-premises cluster. If we run the job until the solver converges (in this case around 15,000 cycles) we can calculate a time to solution. The graph below shows this time to solution at different node counts, where a lower time to solution is better.

The above chart demonstrates that AWS instances are giving a quicker time to solution for the same node counts as the on-premises cluster. This is to be expected as the AWS compute nodes have 36 Skylake cores versus the 24 Broadwell cores on the on-premises cluster compute nodes. However, the scaling performance demonstrates that this advantage is still present at the higher node counts although one might expect that the impact of the interconnect network would give the on-premises cluster an advantage.

What was the impact of FSx for Lustre?

To assess the impact of Amazon FSx for Lustre we also ran the tests using an NVMe exported via NFS based solution and compared the overall elapsed time for the run (to 20 cycles). The chart below shows the comparison between the on-premises cluster with IBM Spectrum Scale storage, Amazon FSx for Lustre and the NFS solution.

The above chart shows that Amazon FSx for Lustre scales well with the increased node count and at the higher node counts actually outperforms the Spectrum Scale solution.

Our additional tests demonstrated:

  • Use of GPU instances like Amazon EC2 P3 Instances and Amazon EC2 instances can significantly accelerate your workloads
  • Use of Graviton2 instances (performance tests were repeated on the c6g.16xlarge instance type) demonstrated better performance

Price Performance

The number of CFD runs that need to be performed as part of the design cycle is enormous and so price/performance for CFD on HPC becomes critical. AWS offers several pricing models. For the purposes of this study, we considered standard On-demand pricing, Reserved Instances (RI) and Spot instances. For on-premises cluster, we used a price of £0.05 per core/hour, which from our experience is a fair representation of the cost of using an on-demand specialist HPC system.

The relative price performance shown on the chart below is the cycle time of the run divided by the resource cost, normalized relative to the on-premises system. The value above 1 represents better price/performance than the on-premises cluster.

On-demand pricing places the AWS solution at a lower price/performance than the on-premises cluster. However, when we apply Reserved Instances or Spot, the AWS solution is more cost effective than the on-premises cluster.   Overall, mixing On-demand, Reserved Instances and Spot pricing models will often provide an organization with the best mix of flexibility and cost savings.

Below is the same price/performance metric for the GPU and Graviton2 instances demonstrating that increased performance of the GPU options balances out the higher instances prices and brings the price performance in line with on-premises cluster even at on-demand pricing, in fact the G4 instances are providing significantly better price performance.

Graviton2 price performance makes it an interesting option for those codes that cannot easily take advantage of GPUs but may be able to target the arm64 architecture.

Conclusion

One of the biggest changes that comes with using cloud HPC is the ability to be flexible with the size of the infrastructure. Cloud allows you to do things that are not easy with an in-house cluster such as ‘Design of experiments’ and increase model accuracy or fidelity.

If turnaround time is a priority, you can scale your HPC cluster size to meet your demand, meaning users no longer have to queue. HPC clusters can be spun up in a matter of minutes and then used for a single job, a specific project or even dedicated to a single user. For example, Zenotech was able to spin up all the infrastructure required to run the 100 node benchmarks in less than 10 minutes, and then when the runs completed they post-processed the data, stored the results on S3, and terminated all of the infrastructure – with no on-going costs associated with the HPC cluster.

The study conducted by Zenotech and AWS demonstrated that the AWS based infrastructure is capable of running a large aircraft CFD simulation at scale at a level of performance that exceeds an on-premises HPC cluster. This coupled with the on-demand Lustre file system offered by FSx for Lustre gives organizations that require HPC a flexible cloud-based option to complement, or replace on-premises HPC.

We also demonstrated that running CFD on GPUs gives the industry the ability to vastly speed up CFD simulations, a trend that will continue as next generation of GPUs gets deployed. The advent of arm64 processors is a very interesting development and we have demonstrated that they can be used for an HPC workload and offer a price/performance advantage over the x86 equivalent. Cloud HPC offers the flexibility to use this heterogeneous mix of hardware without expensive reconfiguration or capital purchases.

Learn more about CFD simulations on AWS here.

Notices

Customers are responsible for making their own independent assessment of the information in this article. This document: (a) is for informational purposes only, (b) represents current AWS product offerings and practices, which are subject to change without notice, and (c) does not create any commitments or assurances from AWS and its affiliates, suppliers or licensors. AWS products or services are provided “as is” without warranties, representations, or conditions of any kind, whether express or implied. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers.

Return to Solution Channel Homepage

AWS Resources

Follow @awscloud

AWS on Facebook

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!

European Commission Declares €8 Billion Investment in Supercomputing

September 18, 2020

Just under two years ago, the European Commission formalized the EuroHPC Joint Undertaking (JU): a concerted HPC effort (comprising 32 participating states at current count) across the European Union and supplanting HPC Read more…

By Oliver Peckham

Google Hires Longtime Intel Exec Bill Magro to Lead HPC Strategy

September 18, 2020

In a sign of the times, another prominent HPCer has made a move to a hyperscaler. Longtime Intel executive Bill Magro joined Google as chief technologist for high-performance computing, a newly created position that is a Read more…

By Tiffany Trader

Swiss Supercomputer Enables Ultra-Precise Climate Simulations

September 17, 2020

As smoke from the record-breaking West Coast wildfires pours across the globe and tropical storms continue to form at unprecedented rates, the state of the global climate is once again looming in the public eye. Owing to Read more…

By Oliver Peckham

Future of Fintech on Display at HPC + AI Wall Street

September 17, 2020

Those who tuned in for Tuesday's HPC + AI Wall Street event got a peak at the future of fintech and lively discussion of topics like blockchain, AI for risk management, and high-frequency trading, as told by a group of l Read more…

By Alex Woodie,Tiffany Trader and Todd R. Weiss

Legacy HPC System Seeds Supercomputing Excellence at UT Dallas

September 16, 2020

What happens to supercomputers after their productive life at an academic research center ends? The question often arises when people hear that the average age of a top supercomputer at retirement is about five years. Rest assured — systems aren’t simply scrapped. Instead, they’re donated to organizations and institutions that can make... Read more…

By Aaron Dubrow

AWS Solution Channel

Next-generation aerospace modeling and simulation: benchmarking Amazon Web Services High Performance Computing services

The aerospace industry has been using Computational Fluid Dynamics (CFD) for decades to create and optimize designs digitally, from the largest passenger planes and fighter jets to gliders and drones. Read more…

Intel® HPC + AI Pavilion

Berlin Institute of Health: Putting HPC to Work for the World

Researchers from the Center for Digital Health at the Berlin Institute of Health (BIH) are using science to understand the pathophysiology of COVID-19, which can help to inform the development of targeted treatments. Read more…

IBM’s Quantum Race to One Million Qubits

September 15, 2020

IBM today outlined its ambitious quantum computing technology roadmap at its virtual Quantum Summit. The eye-popping million qubit number is still far out, agrees IBM, but perhaps not that far out. Just as eye-popping is IBM’s nearer-term plan for a 1,000-plus qubit system named Condor... Read more…

By John Russell

European Commission Declares €8 Billion Investment in Supercomputing

September 18, 2020

Just under two years ago, the European Commission formalized the EuroHPC Joint Undertaking (JU): a concerted HPC effort (comprising 32 participating states at c Read more…

By Oliver Peckham

Google Hires Longtime Intel Exec Bill Magro to Lead HPC Strategy

September 18, 2020

In a sign of the times, another prominent HPCer has made a move to a hyperscaler. Longtime Intel executive Bill Magro joined Google as chief technologist for hi Read more…

By Tiffany Trader

Future of Fintech on Display at HPC + AI Wall Street

September 17, 2020

Those who tuned in for Tuesday's HPC + AI Wall Street event got a peak at the future of fintech and lively discussion of topics like blockchain, AI for risk man Read more…

By Alex Woodie,Tiffany Trader and Todd R. Weiss

IBM’s Quantum Race to One Million Qubits

September 15, 2020

IBM today outlined its ambitious quantum computing technology roadmap at its virtual Quantum Summit. The eye-popping million qubit number is still far out, agrees IBM, but perhaps not that far out. Just as eye-popping is IBM’s nearer-term plan for a 1,000-plus qubit system named Condor... Read more…

By John Russell

Nvidia Commits to Buy Arm for $40B

September 14, 2020

Nvidia is acquiring semiconductor design company Arm Ltd. for $40 billion from SoftBank in a blockbuster deal that catapults the GPU chipmaker to a dominant position in the datacenter while helping troubled SoftBank reverse its financial woes. The deal, which has been rumored for... Read more…

By Todd R. Weiss and George Leopold

AMD’s Massive COVID-19 HPC Fund Adds 18 Institutions, 5 Petaflops of Power

September 14, 2020

Almost exactly five months ago, AMD announced its COVID-19 HPC Fund, an ongoing flow of resources and equipment to research institutions studying COVID-19 that began with an initial donation of $15 million. In June, AMD announced major equipment donations to several major institutions. Now, AMD is making its third major COVID-19 HPC Fund... Read more…

By Oliver Peckham

HPC Strategist Dave Turek Joins DNA Storage (and Computing) Company Catalog

September 11, 2020

You've heard the saying "flash is the new disk and disk is the new tape," which traces its origins back to Jim Gray*. But what if DNA-based data storage could o Read more…

By Tiffany Trader

Google’s Quantum Chemistry Simulation Suggests Promising Path Forward

September 9, 2020

A much-anticipated prize in quantum computing is the ability to more accurately model chemical bonding behavior. Doing so should lead to better chemical synthes Read more…

By John Russell

Supercomputer-Powered Research Uncovers Signs of ‘Bradykinin Storm’ That May Explain COVID-19 Symptoms

July 28, 2020

Doctors and medical researchers have struggled to pinpoint – let alone explain – the deluge of symptoms induced by COVID-19 infections in patients, and what Read more…

By Oliver Peckham

Nvidia Said to Be Close on Arm Deal

August 3, 2020

GPU leader Nvidia Corp. is in talks to buy U.K. chip designer Arm from parent company Softbank, according to several reports over the weekend. If consummated Read more…

By George Leopold

10nm, 7nm, 5nm…. Should the Chip Nanometer Metric Be Replaced?

June 1, 2020

The biggest cool factor in server chips is the nanometer. AMD beating Intel to a CPU built on a 7nm process node* – with 5nm and 3nm on the way – has been i Read more…

By Doug Black

Intel’s 7nm Slip Raises Questions About Ponte Vecchio GPU, Aurora Supercomputer

July 30, 2020

During its second-quarter earnings call, Intel announced a one-year delay of its 7nm process technology, which it says it will create an approximate six-month shift for its CPU product timing relative to prior expectations. The primary issue is a defect mode in the 7nm process that resulted in yield degradation... Read more…

By Tiffany Trader

HPE Keeps Cray Brand Promise, Reveals HPE Cray Supercomputing Line

August 4, 2020

The HPC community, ever-affectionate toward Cray and its eponymous founder, can breathe a (virtual) sigh of relief. The Cray brand will live on, encompassing th Read more…

By Tiffany Trader

Supercomputer Simulations Reveal the Fate of the Neanderthals

May 25, 2020

For hundreds of thousands of years, neanderthals roamed the planet, eventually (almost 50,000 years ago) giving way to homo sapiens, which quickly became the do Read more…

By Oliver Peckham

Neocortex Will Be First-of-Its-Kind 800,000-Core AI Supercomputer

June 9, 2020

Pittsburgh Supercomputing Center (PSC - a joint research organization of Carnegie Mellon University and the University of Pittsburgh) has won a $5 million award Read more…

By Tiffany Trader

Supercomputer Modeling Tests How COVID-19 Spreads in Grocery Stores

April 8, 2020

In the COVID-19 era, many people are treating simple activities like getting gas or groceries with caution as they try to heed social distancing mandates and protect their own health. Still, significant uncertainty surrounds the relative risk of different activities, and conflicting information is prevalent. A team of Finnish researchers set out to address some of these uncertainties by... Read more…

By Oliver Peckham

Leading Solution Providers

Contributors

Australian Researchers Break All-Time Internet Speed Record

May 26, 2020

If you’ve been stuck at home for the last few months, you’ve probably become more attuned to the quality (or lack thereof) of your internet connection. Even Read more…

By Oliver Peckham

Oracle Cloud Infrastructure Powers Fugaku’s Storage, Scores IO500 Win

August 28, 2020

In June, RIKEN shook the supercomputing world with its Arm-based, Fujitsu-built juggernaut: Fugaku. The system, which weighs in at 415.5 Linpack petaflops, topp Read more…

By Oliver Peckham

Google Cloud Debuts 16-GPU Ampere A100 Instances

July 7, 2020

On the heels of the Nvidia’s Ampere A100 GPU launch in May, Google Cloud is announcing alpha availability of the A100 “Accelerator Optimized” VM A2 instance family on Google Compute Engine. The instances are powered by the HGX A100 16-GPU platform, which combines two HGX A100 8-GPU baseboards using... Read more…

By Tiffany Trader

DOD Orders Two AI-Focused Supercomputers from Liqid

August 24, 2020

The U.S. Department of Defense is making a big investment in data analytics and AI computing with the procurement of two HPC systems that will provide the High Read more…

By Tiffany Trader

Joliot-Curie Supercomputer Used to Build First Full, High-Fidelity Aircraft Engine Simulation

July 14, 2020

When industrial designers plan the design of a new element of a vehicle’s propulsion or exterior, they typically use fluid dynamics to optimize airflow and in Read more…

By Oliver Peckham

Japan’s Fugaku Tops Global Supercomputing Rankings

June 22, 2020

A new Top500 champ was unveiled today. Supercomputer Fugaku, the pride of Japan and the namesake of Mount Fuji, vaulted to the top of the 55th edition of the To Read more…

By Tiffany Trader

Microsoft Azure Adds A100 GPU Instances for ‘Supercomputer-Class AI’ in the Cloud

August 19, 2020

Microsoft Azure continues to infuse its cloud platform with HPC- and AI-directed technologies. Today the cloud services purveyor announced a new virtual machine Read more…

By Tiffany Trader

$100B Plan Submitted for Massive Remake and Expansion of NSF

May 27, 2020

Legislation to reshape, expand - and rename - the National Science Foundation has been submitted in both the U.S. House and Senate. The proposal, which seems to 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