Extreme Scale HPC: How Western Digital Corporation leveraged the virtually unlimited HPC capacity on AWS in their quest to speed up innovation and build better products

By Bala Thekkedath - Global HPC Marketing Lead, Amazon Web Services

December 10, 2018

Recently, AWS and Western Digital embarked on a very fun, challenging project of evaluating the impact of running their electro-magnetic simulations on a massive HPC cluster built on AWS using Amazon EC2 Spot Instances.   The lessons we learned and the results we were able to prove are very interesting and I am excited to share a quick overview here.

One of the biggest advantages of moving your HPC workloads to AWS is the ability to achieve extreme scales in terms of capacity and configurations – without a lot of upfront investment and heartache over long term commitments.  If you work for an organization that has moved HPC workloads to the cloud or has at least started the process by bursting to the cloud when demand spikes, you have experienced the agility and flexibility benefits afforded by the cloud.  You either have an individual account to access and request resources in the cloud or you request it via your HPC admin.  In both cases, you start building “your” cluster when you are ready. In most cases the cluster is built automatically by your job scheduler as you submit your jobs, and compute resources are ready within minutes. When the jobs are done, you shut down your cluster and stop paying for it.  When you request your cluster, unlike your on-premises environment, you can specify what type of CPUs (or GPUs, or FPGAs) you would like to run a particular application on.  Ever wonder how much faster your application would run if you had the latest CPU or GPU?  What if you wanted to determine if an I/O bandwidth optimized configuration versus CPU was better for parts of your workflow?   Well, now you can try many different configuration types without going through a cumbersome procurement process.  It becomes incredibly easy to fine tune specific portions of your HPC workflow, given the many different instance types available, and how easy it is to drop them into a workflow.   Then, there is the scale.   It does not matter if you request 1,000 cores for 8-hours or 8,000 cores for 1-hour.  You still pay the same.   So, if your application supports it, why not scale up your resources and get to results faster?

That is exactly what a recent collaborative project between AWS and Western Digital did.  First, a quick overview of the hard disk drive (HDD) market.  The HDD market is an extremely competitive one.  The ever-increasing demand for capacity from enterprises, particularly large hyper-scale data centers (like us) has been keeping Western Digital very busy.  Faced with the need to innovate to meet the growing demand for data storage capacity, the engineering teams at Western Digital are always pushing the limits of physics and engineering.  Enterprise HDDs are still confined to a 3.5 inches form factor (as they have been for years) with no chance to increase the size to accommodate additional capacity and performance requirements.  So, the only solution to meeting the increased capacity demands is to cram more bits into the same space and make sure the drives can handle the increasing demands for performance.  The technical term here is increasing the areal density of the media – meaning, keep on shrinking the geometry that you are allowed to use to capture the ones and zeros on the rotating media.  As you shrink those geometries, there are various aspects of cross talk, noise and atomic behavior that you have to comprehend to get to an ingredient combination that works 24x7x365, and can be manufactured at high volume. It is quite an art and science to get all those things to line up exactly, make it repeatable, make it manufacturable, make it operational, and, oh, by the way, get it to work for years without a failure.

A big focus of the engineering simulations work at Western Digital is to evaluate different combinations of technologies and/or solutions (or ingredients that make up the solutions) that goes into making new HDDs.  The basic design of the hard disk involves a rotating media and a head on a slider arm that moves over the media.  The engineering teams are looking at smaller and smaller geometries of recording channels on the media so they can fit more and more 1’s and 0’s or bits into the same space.  They are looking to achieve faster read and write times from that media.  The simulations thus involve many variable vectors to find the right combination of media, speed of rotation of the media, materials that constitute the media etc. that can provide that higher density and faster read-write times.   The end goal is to determine which combinations work and which don’t – and making sure those combinations that don’t work are avoided in the manufacturing process or in solutions/component recipes for the physical products.

As part of this precedent-setting collaborative work, Western Digital ran around 2.3 million simulation jobs on a Spot-based cluster of a little over one million vCPUs.   If they were to do those same 2.3 million simulations on a standard Spot based cluster of 16,000 vCPUs at a time (as they do today), it would have taken them about 20 days to get the same work done.     The idea of doing 20 days of work in 8 hours is a game changer.  The impacts go beyond the traditional business metrics – it is a great competitive advantage for a business that is driven by innovation.

So, what goes into scaling an application to run on extreme capacity infrastructure?  It is a coordinated effort between the application engineers, the infrastructure engineers, and the team at AWS.    At a 10K ft level, what we are doing here is taking a large statistical simulation, splitting it into jobs that run on a single vCPU, then when the jobs are done, bringing it all back and collating the results.   That requires work on both the application side and the infrastructure side.  The application has to ensure that the individual simulations are all done correctly, the infrastructure has to coordinate jobs across a vast number of servers/cores and bring all the data back to collate. What made this run even more interesting is that we used EC2 Spot instances, so the application had to be resilient for any job preemption or interruption that might happen. During the 8 hours run at the full one million vCPU scale, we experienced less than 1% of interruption. From an infrastructure point of view, we had to evaluate the limits that exists on number of underlying services (compute, storage, API calls) and since this was a cluster that was run all in a single region, but spanned multiple Availability Zones, we combined the features of AWS Spot Fleet with the highly-scalable cluster management and scheduling of Univa NavOps and GridEngine to coordinate cluster management across the wide capacity of our infrastructure and keep the cluster fully utilized even under such very high workload.

A few other points that are worth highlighting here.  First, Western Digital, Univa and AWS were able to fully exploit the configuration flexibility that running HPC workloads on the cloud offers.  Before embarking on this simulation, the engineers from both AWS and Western Digital spent a lot of prep time profiling the various instance types that Amazon EC2 offers. Through profiling this multitude of instance types (over 25 different instances types), we were able to land on the most optimal range of instances offering AVX acceleration for this workload, giving the AWS Spot Fleet the flexibility and freedom to find the cheapest and fastest hardware for the job.   Second, this simulation was also a major achievement in terms of the use of containers to run HPC workloads.  In this run, the entire application was ported onto containers, which is a big shift from having to haul around drivers and dependencies across jobs and VMs.   This run actually might have been one of the largest container fleets running a single application! Third, we used Amazon Simple Storage Service (Amazon S3) as the storage back-end for this simulation.  Being able to support this fast rate of data access at such massive scales required no tuning effort, as S3 bandwidth scaled gracefully and peaked at 7500 PUT/s.  And last, but not the least, this was a great example of how Spot Fleet can simplify cluster management.  In this particular case, we just had three Spot Fleet requests simultaneously and we were able to hit a million cores in the cluster in around 1 hour and 32 minutes!

To learn more, visit https://aws.amazon.com/hpc or reach out to your local AWS representative.

 

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 Budget Approved for $8.3B in 2020, a 2.5% Increase

January 16, 2020

The National Science Foundation (NSF) has been spared a President Trump-proposed budget cut that would have rolled back its funding to 2012 levels. Congress passed legislation last month that sets the budget at $8.3 bill Read more…

By Staff report

NOAA Updates Its Massive, Supercomputer-Generated Climate Dataset

January 15, 2020

As Australia burns, understanding and mitigating the climate crisis is more urgent than ever. Now, by leveraging the computing resources at the National Energy Research Scientific Computing Center (NERSC), the U.S. National Oceanic and Atmospheric Administration (NOAA) has updated its 20th Century Reanalysis Project (20CR) dataset... Read more…

By Oliver Peckham

Atos-AMD System to Quintuple Supercomputing Power at European Centre for Medium-Range Weather Forecasts

January 15, 2020

The United Kingdom-based European Centre for Medium-Range Weather Forecasts (ECMWF), a supercomputer-powered weather forecasting organization backed by most of the countries in Europe, has signed a four-year, $89-million Read more…

By Oliver Peckham

Julia Programming’s Dramatic Rise in HPC and Elsewhere

January 14, 2020

Back in 2012 a paper by four computer scientists including Alan Edelman of MIT introduced Julia, A Fast Dynamic Language for Technical Computing. At the time, the gold standard programming languages for fast performance Read more…

By John Russell

Quantum Computing, ML Drive 2019 Patent Awards

January 14, 2020

The dizzying pace of technology innovation often fueled by the growing availability of computing horsepower is underscored by the race to develop unique designs and application that can be patented. Among the goals of ma Read more…

By George Leopold

AWS Solution Channel

Challenging the barriers to High Performance Computing in the Cloud

Cloud computing helps democratize High Performance Computing by placing powerful computational capabilities in the hands of more researchers, engineers, and organizations who may lack access to sufficient on-premises infrastructure. Read more…

IBM Accelerated Insights

Intelligent HPC – Keeping Hard Work at Bay(es)

Since the dawn of time, humans have looked for ways to make their lives easier. Over the centuries human ingenuity has given us inventions such as the wheel and simple machines – which help greatly with tasks that would otherwise be extremely laborious. Read more…

Andrew Jones Joins Microsoft Azure HPC Team

January 13, 2020

Andrew Jones announced today he is joining Microsoft as part of the Azure HPC engineering & product team in early February. Jones makes the move after nearly 12 years at the UK HPC consultancy Numerical Algorithms Gr Read more…

By Staff report

Atos-AMD System to Quintuple Supercomputing Power at European Centre for Medium-Range Weather Forecasts

January 15, 2020

The United Kingdom-based European Centre for Medium-Range Weather Forecasts (ECMWF), a supercomputer-powered weather forecasting organization backed by most of Read more…

By Oliver Peckham

Julia Programming’s Dramatic Rise in HPC and Elsewhere

January 14, 2020

Back in 2012 a paper by four computer scientists including Alan Edelman of MIT introduced Julia, A Fast Dynamic Language for Technical Computing. At the time, t Read more…

By John Russell

White House AI Regulatory Guidelines: ‘Remove Impediments to Private-sector AI Innovation’

January 9, 2020

When it comes to new technology, it’s been said government initially stays uninvolved – then gets too involved. The White House’s guidelines for federal a Read more…

By Doug Black

IBM Touts Quantum Network Growth, Improving QC Quality, and Battery Research

January 8, 2020

IBM today announced its Q (quantum) Network community had grown to 100-plus – Delta Airlines and Los Alamos National Laboratory are among most recent addition Read more…

By John Russell

HPCwire Awards Highlight Supercomputing Achievements in the Sciences

January 7, 2020

In November at SC19 in Denver, the HPCwire Readers’ and Editors’ Choice awards program celebrated its 16th year of honoring remarkable achievements in high-performance computing. With categories ranging from Best Use of HPC in Energy to Top HPC-Enabled Scientific Achievement, many of the winners contributed to groundbreaking developments in the sciences. This editorial highlights those awards. Read more…

By Oliver Peckham

Blasts from the (Recent) Past and Hopes for the Future

December 23, 2019

What does 2020 look like to you? What did 2019 look like? Lots happened but the main trends were carryovers from 2018 – AI messaging again blanketed everything; the roll-out of new big machines and exascale announcements continued; processor diversity and system disaggregation kicked up a notch; hyperscalers continued flexing their muscles (think AWS and its Graviton2 processor); and the U.S. and China continued their awkward trade war. Read more…

By John Russell

ARPA-E Applies ML to Power Generation Designs

December 19, 2019

The U.S. Energy Department’s research arm is leveraging machine learning technologies to simplify the design process for energy systems ranging from photovolt Read more…

By George Leopold

Focused on ‘Silicon TAM,’ Intel Puts Gary Patton, Former GlobalFoundries CTO, in Charge of Design Enablement

December 12, 2019

Change within Intel’s upper management – and to its company mission – has continued as a published report has disclosed that chip technology heavyweight G Read more…

By Doug Black

Using AI to Solve One of the Most Prevailing Problems in CFD

October 17, 2019

How can artificial intelligence (AI) and high-performance computing (HPC) solve mesh generation, one of the most commonly referenced problems in computational engineering? A new study has set out to answer this question and create an industry-first AI-mesh application... Read more…

By James Sharpe

D-Wave’s Path to 5000 Qubits; Google’s Quantum Supremacy Claim

September 24, 2019

On the heels of IBM’s quantum news last week come two more quantum items. D-Wave Systems today announced the name of its forthcoming 5000-qubit system, Advantage (yes the name choice isn’t serendipity), at its user conference being held this week in Newport, RI. Read more…

By John Russell

SC19: IBM Changes Its HPC-AI Game Plan

November 25, 2019

It’s probably fair to say IBM is known for big bets. Summit supercomputer – a big win. Red Hat acquisition – looking like a big win. OpenPOWER and Power processors – jury’s out? At SC19, long-time IBMer Dave Turek sketched out a different kind of bet for Big Blue – a small ball strategy, if you’ll forgive the baseball analogy... Read more…

By John Russell

Cray, Fujitsu Both Bringing Fujitsu A64FX-based Supercomputers to Market in 2020

November 12, 2019

The number of top-tier HPC systems makers has shrunk due to a steady march of M&A activity, but there is increased diversity and choice of processing compon Read more…

By Tiffany Trader

Crystal Ball Gazing: IBM’s Vision for the Future of Computing

October 14, 2019

Dario Gil, IBM’s relatively new director of research, painted a intriguing portrait of the future of computing along with a rough idea of how IBM thinks we’ Read more…

By John Russell

Julia Programming’s Dramatic Rise in HPC and Elsewhere

January 14, 2020

Back in 2012 a paper by four computer scientists including Alan Edelman of MIT introduced Julia, A Fast Dynamic Language for Technical Computing. At the time, t Read more…

By John Russell

Intel Debuts New GPU – Ponte Vecchio – and Outlines Aspirations for oneAPI

November 17, 2019

Intel today revealed a few more details about its forthcoming Xe line of GPUs – the top SKU is named Ponte Vecchio and will be used in Aurora, the first plann Read more…

By John Russell

Dell Ramps Up HPC Testing of AMD Rome Processors

October 21, 2019

Dell Technologies is wading deeper into the AMD-based systems market with a growing evaluation program for the latest Epyc (Rome) microprocessors from AMD. In a Read more…

By John Russell

Leading Solution Providers

SC 2019 Virtual Booth Video Tour

AMD
AMD
ASROCK RACK
ASROCK RACK
AWS
AWS
CEJN
CJEN
CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
IBM
IBM
MELLANOX
MELLANOX
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
SIX NINES IT
SIX NINES IT
VERNE GLOBAL
VERNE GLOBAL
WEKAIO
WEKAIO

IBM Unveils Latest Achievements in AI Hardware

December 13, 2019

“The increased capabilities of contemporary AI models provide unprecedented recognition accuracy, but often at the expense of larger computational and energet Read more…

By Oliver Peckham

SC19: Welcome to Denver

November 17, 2019

A significant swath of the HPC community has come to Denver for SC19, which began today (Sunday) with a rich technical program. As is customary, the ribbon cutt Read more…

By Tiffany Trader

With the Help of HPC, Astronomers Prepare to Deflect a Real Asteroid

September 26, 2019

For years, NASA has been running simulations of asteroid impacts to understand the risks (and likelihoods) of asteroids colliding with Earth. Now, NASA and the European Space Agency (ESA) are preparing for the next, crucial step in planetary defense against asteroid impacts: physically deflecting a real asteroid. Read more…

By Oliver Peckham

Jensen Huang’s SC19 – Fast Cars, a Strong Arm, and Aiming for the Cloud(s)

November 20, 2019

We’ve come to expect Nvidia CEO Jensen Huang’s annual SC keynote to contain stunning graphics and lively bravado (with plenty of examples) in support of GPU Read more…

By John Russell

Top500: US Maintains Performance Lead; Arm Tops Green500

November 18, 2019

The 54th Top500, revealed today at SC19, is a familiar list: the U.S. Summit (ORNL) and Sierra (LLNL) machines, offering 148.6 and 94.6 petaflops respectively, Read more…

By Tiffany Trader

51,000 Cloud GPUs Converge to Power Neutrino Discovery at the South Pole

November 22, 2019

At the dead center of the South Pole, thousands of sensors spanning a cubic kilometer are buried thousands of meters beneath the ice. The sensors are part of Ic Read more…

By Oliver Peckham

Azure Cloud First with AMD Epyc Rome Processors

November 6, 2019

At Ignite 2019 this week, Microsoft's Azure cloud team and AMD announced an expansion of their partnership that began in 2017 when Azure debuted Epyc-backed instances for storage workloads. The fourth-generation Azure D-series and E-series virtual machines previewed at the Rome launch in August are now generally available. Read more…

By Tiffany Trader

Summit Has Real-Time Analytics: Here’s How It Happened and What’s Next

October 3, 2019

Summit – the world’s fastest publicly-ranked supercomputer – now has real-time streaming analytics. At the 2019 HPC User Forum at Argonne National Laborat Read more…

By Oliver Peckham

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