Wanted: Good Use for Supercomputer

By Nicole Hemsoth

September 15, 2011

It’s a bit unorthodox for us to bring you news from something happening on a social news site, but there’s been a great deal of buzz generated on Slashdot following a recent post in which a user wrote the following:

In about 2 weeks time I will be receiving everything necessary to build the largest x86_64-based supercomputer on the east coast of the U.S. (at least until someone takes the title away from us). It’s spec’ed to start with 1200 dual-socket six-core servers. We primarily do life-science/health/biology related tasks on our existing (fairly small) HPC. We intend to continue this usage, but to also open it up for new uses (energy comes to mind). Additionally, we’d like to lease access to recoup some of our costs. So, what’s the best Linux distro for something of this size and scale? Any that include a chargeback option/module? Additionally, due to cost contracts, we have to choose either InfiniBand or 10Gb Ethernet for the backend: which would Slashdot readers go with if they had to choose? Either way, all nodes will have four 1Gbps Ethernet ports. Finally, all nodes include only a basic onboard GPU. We intend to put powerful GPUs into the PCI-e slot and open up the new HPC for GPU related crunching. Any suggestions on the most powerful Linux friendly PCI-e GPU available?

Chances are, some, if not much, of this sounds rather unlikely to you (including, of course, the whole “largest supercomputer on the east coast” claim).

However, what’s most interesting here is not necessarily the question itself, but the extended conversation that this generated from members of the HPC user community. Many respondents (often prefacing their responses with a “this is an unlikely scenario but I’ll answer anyway” disclaimer) went far beyond merely poking holes in the soon-to-be supercomputer owner’s story (although there was plenty of hole poking) — and shed some light on real, practical opinions from HPC shops.

In the process of answering some of the user’s questions about which Linux distribution is best, whether InfiniBand or 10GbE was the proper choice, and what kind of performance benefits can be had with GPUs for a range of applications, and what cluster management solutions were the best, the HPC community inadvertently produced a compendium of first-hand insights about their own experience making purchase and use decisions at their centers or companies.

As you might imagine, comments like the following were not uncommon:

1) Something with 10gb really isn’t a “supercomputer” it is a cluster. Fine, but call it what it is. I really wouldn’t call a cluster with Infiniband a supercomputer either.

2) You really should maybe get someone who knows more about your project and someone who knows more about clusters/supercomputers. The questions you are asking are not ones I would want to see form the guy making the choices on a multimillion dollar project.

But many others provided some excellent real-world examples (or so we assume, this is the Internet) of their use of similarly-sized clusters. For instance, one user wrote:

Similar size setup in bio-informatics in Europe. We run redhat 6.1, was centos 5 and LSF. single 1gbit to each server (blades). No need for 10gb or IB unless huge mpi which no one uses. 32GB to 2TB per node – some people like enormous R datasets. All works well for our ~500 users.

Others weighed in with more specific answers about specific elements, including GPUs:

As for GPUs…be aware that the claimed performance for GPUs, especially in clusters, is virtually unattainable. You have to write code in their nasty domain-specific languages (CUDA or OpenCL for Nvidia, just OpenCL for AMD) and there isn’t really any concept of IPC baked in to the tools to allow for distributed operations. Furthermore, GPUs are also generally extroridnarly memory and memory bandwidth starved (remember, the speed comes from there being hundreds of processing elements on the card, all sharing the same memory and interface), so simply keeping them fed with data is challenging. GPGPU is also an unstable area in both relevant senses: the GPGPU software itself has a nasty tendency to hang the host when something goes wrong (which is extra fun in clusters without BMCs), and the platforms are changing at an alarming clip. AMD is somewhat worse in the “moving target” regard – they recently deprecated all 4000 series cards from being supported by GPGPU tools, and have abandoned their CTM, CAL, and Brook+ environments before settling on OpenCL, and only OpenCL.

The original author did decide to answer back with more details about why he was in such a predicament in the first place. The story that came forth was one of woe and struggle, indeed.

His response to the critics initiated some rather confident guesses about exactly what institution he was from — and who the “generous benefactor” might be.

…here’s the quick backstory behind my question(s): Our organization received a grant to pay for this from a private philanthropist that has a medical issue that is currently being researched by one of our labs (this happens to us not to infrequently). We have an existing HPC of roughly 300 nodes and 1200 cores that’s all 1Gbps connected and running Rocks 5.1. The grant money came in in two different payments. We used the first payment to buy the nodes (which are in route to arrive in 2 weeks or so). The second payment was going to pay for the GPU’s and the extra infrastructure (storage is one thing we currently have plenty of… both SAN and NAS). Unfortunately, we hit two issues: 1) one of our more seasoned enterprise admins took a new job at Apple’s new NC datacenter and 2) our cluster admin passed away from a heart attack about a week after the purchase was made. This put us into a bit of a holding pattern. We’re in the process of replacing both of them, but in the meantime we A) have the equipment arriving soon and B) have the second round of the grant money in hand now.

We’re smart enough to know that we lost two very valuable resources and we decided to step back, pause, and re-evaluate. The servers are already bought. The infrastructure, interconnects, and GPU’s are not. The old admin knew which GPU’s he wanted; unfortunately we haven’t found his research anywhere to know what and why. He had also planned to go with the latest release of Rocks, but only because he was very familiar with it. We know there are other options out there and we’ve no idea how well Rocks can scale. Additionally, I don’t see an option for chargeback with Rocks (at least not from a Google search), plus we’ve heard they recently lost a core developer. Thus, we went to the Slashdot community for advice. So I’ve already seen some good info on the IB versus 10GbE question and its much appreciated. We’re still looking for info on which Linux distro and which GPU to go for. We want to make the best decision we can and use the money as wisely as possible. But we also realize that we know what we don’t know and thought the Slashdot community could provide some experience to help us make the right decisions.

For anyone with the time and patience to read through almost 400 comments, well over half of which provide at least a useful morsel of information for someone trying to learn about what works and doesn’t for clusters around the world — it’s definitely worth a glance.

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!

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 “pre-exascale” award), parsed out additional information ab Read more…

By Tiffany Trader

Tsinghua Crowned Eight-Time Student Cluster Champions at ISC

June 22, 2017

Always a hard-fought competition, the Student Cluster Competition awards were announced Wednesday, June 21, at the ISC High Performance Conference 2017. Amid whoops and hollers from the crowd, Thomas Sterling presented t Read more…

By Kim McMahon

GPUs, Power9, Figure Prominently in IBM’s Bet on Weather Forecasting

June 22, 2017

IBM jumped into the weather forecasting business roughly a year and a half ago by purchasing The Weather Company. This week at ISC 2017, Big Blue rolled out plans to push deeper into climate science and develop more gran Read more…

By John Russell

Intersect 360 at ISC: HPC Industry at $44B by 2021

June 22, 2017

The care, feeding and sustained growth of the HPC industry increasingly is in the hands of the commercial market sector – in particular, it’s the hyperscale companies and their embrace of AI and deep learning – tha Read more…

By Doug Black

HPE Extreme Performance Solutions

Creating a Roadmap for HPC Innovation at ISC 2017

In an era where technological advancements are driving innovation to every sector, and powering major economic and scientific breakthroughs, high performance computing (HPC) is crucial to tackle the challenges of today and tomorrow. Read more…

At ISC – Goh on Go: Humans Can’t Scale, the Data-Centric Learning Machine Can

June 22, 2017

I've seen the future this week at ISC, it’s on display in prototype or Powerpoint form, and it’s going to dumbfound you. The future is an AI neural network designed to emulate and compete with the human brain. In thi Read more…

By Doug Black

Cray Brings AI and HPC Together on Flagship Supers

June 20, 2017

Cray took one more step toward the convergence of big data and high performance computing (HPC) today when it announced that it’s adding a full suite of big data and artificial intelligence software to its top-of-the-l Read more…

By Alex Woodie

AMD Charges Back into the Datacenter and HPC Workflows with EPYC Processor

June 20, 2017

AMD is charging back into the enterprise datacenter and select HPC workflows with its new EPYC 7000 processor line, code-named Naples, announced today at a “global” launch event in Austin TX. In many ways it was a fu Read more…

By John Russell

Hyperion: Deep Learning, AI Helping Drive Healthy HPC Industry Growth

June 20, 2017

To be at the ISC conference in Frankfurt this week is to experience deep immersion in deep learning. Users want to learn about it, vendors want to talk about it, analysts and journalists want to report on it. Deep learni Read more…

By Doug Black

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

Tsinghua Crowned Eight-Time Student Cluster Champions at ISC

June 22, 2017

Always a hard-fought competition, the Student Cluster Competition awards were announced Wednesday, June 21, at the ISC High Performance Conference 2017. Amid wh Read more…

By Kim McMahon

GPUs, Power9, Figure Prominently in IBM’s Bet on Weather Forecasting

June 22, 2017

IBM jumped into the weather forecasting business roughly a year and a half ago by purchasing The Weather Company. This week at ISC 2017, Big Blue rolled out pla Read more…

By John Russell

Intersect 360 at ISC: HPC Industry at $44B by 2021

June 22, 2017

The care, feeding and sustained growth of the HPC industry increasingly is in the hands of the commercial market sector – in particular, it’s the hyperscale Read more…

By Doug Black

At ISC – Goh on Go: Humans Can’t Scale, the Data-Centric Learning Machine Can

June 22, 2017

I've seen the future this week at ISC, it’s on display in prototype or Powerpoint form, and it’s going to dumbfound you. The future is an AI neural network Read more…

By Doug Black

Cray Brings AI and HPC Together on Flagship Supers

June 20, 2017

Cray took one more step toward the convergence of big data and high performance computing (HPC) today when it announced that it’s adding a full suite of big d Read more…

By Alex Woodie

AMD Charges Back into the Datacenter and HPC Workflows with EPYC Processor

June 20, 2017

AMD is charging back into the enterprise datacenter and select HPC workflows with its new EPYC 7000 processor line, code-named Naples, announced today at a “g Read more…

By John Russell

Hyperion: Deep Learning, AI Helping Drive Healthy HPC Industry Growth

June 20, 2017

To be at the ISC conference in Frankfurt this week is to experience deep immersion in deep learning. Users want to learn about it, vendors want to talk about it Read more…

By Doug Black

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

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

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

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 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

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

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

US Supercomputing Leaders Tackle the China Question

March 15, 2017

Joint DOE-NSA report responds to the increased global pressures impacting the competitiveness of U.S. supercomputing. Read more…

By Tiffany Trader

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

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

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 advanced supercomputers. Read more…

By Tiffany Trader

Messina Update: The US Path to Exascale in 16 Slides

April 26, 2017

Paul Messina, director of the U.S. Exascale Computing Project, provided a wide-ranging review of ECP’s evolving plans last week at the HPC User Forum. Read more…

By John Russell

Knights Landing Processor with Omni-Path Makes Cloud Debut

April 18, 2017

HPC cloud specialist Rescale is partnering with Intel and HPC resource provider R Systems to offer first-ever cloud access to Xeon Phi "Knights Landing" processors. The infrastructure is based on the 68-core Intel Knights Landing processor with integrated Omni-Path fabric (the 7250F Xeon Phi). Read more…

By Tiffany Trader

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