Simplifying Cluster Management…

By Nicole Hemsoth

April 22, 2013

Atipa

THE PROBLEM:
Managing clusters can be a daunting task

Higher education and research institutes around the globe are investing in HPC clusters, yet there is an all-too-common oversight during the product acquisition process… they’re not investing in the additional, dedicated man-power it takes to maintain, monitor, and  update their clusters. To the grad students and post-docs  who need the clusters for their research – and also end up being the ones in charge of maintaining and fixing them – clusters are just big, black boxes. The thought of updating the OFED drivers or troubleshooting MCE errors can too often become their impossible task.

THE SOLUTION:
Learn to leverage the deep technical insight of qualified cluster vendors willing to work with you
Damien Tourret, PhD, is a postdoctoral fellow for the Center for Interdisciplinary Research on Complex Systems at Northeastern University’s Boston campus. Recently, he was asked how their cluster has been operating and how his team, led by Distinguished Professor Alain Karma, PhD, has managed to keep the cluster running despite the lack of a cluster administrator. Following an interview with a server technology specialist here is what Damian said:

Interviewer-Tell me about yourself and how you use the cluster

Tourret: Yes, I’m a user of this cluster.  But Ari Adland, I and other grad students are basically also in charge of it. We installed it, and thanks to the interaction we’ve had with our cluster vendor we just basically plugged it in. We’re not computer scientists, we are not HPC experts, we know how to utilize HPC but we’re not that knowledgeable about managing the cluster. Those in charge of cluster maintenance are just grad students and postdocs with backgrounds in physics, material sciences, and biomedical research. We want to spend our time on the cluster doing research, not cluster management.

Our cluster vendor relationship and interaction has allowed us to do our own clustering here while focusing on our research. Basically, we just plugged our cluster in and exchanged a few emails here and there with the vendor to solve problems. Whether it’s GPUs or CPUs, what matters to us is the speedup that we can achieve to solving the problems, more than considerations about the architecture. To most users in here, clusters are big, black boxes.

Interviewer-Do you have any specific cluster problems?

Tourret: A few problems. One was related to memory slots failure, and we had to have the motherboard replaced on one of the nodes at some point.  Two DIMM slots were just not being seen by the motherboard and couldn’t run the jobs properly. That’s a problem we could not diagnose ourselves.

When we reached that level of problem our cluster provider quickly responded to our needs. When we can’t diagnose it ourselves, like a big problem with the motherboard or even a small update to the software, we’re not able to fix them like they can. We simply email Bart, one of our vendor’s HPC engineers, and our problem gets diagnosed and fixed within the day. That’s what we appreciate most.

Interviewer: Have you worked with other system integrators, and how was their support?

Tourret: I have not. That was the first time I’ve personally been in charge of a cluster. I’ve used them before, but they were managed by the IT people. Honestly, when I first arrived here, I was told “Ok you’re going to install this and that” and I asked myself, can I do that? That’s where our cluster vendor has helped a lot because I could not have done it on my own.

At one point we had a performance problem we could not understand at all. We explained the problem to our provider. They felt our code needed more memory channels for better performance and suggested a new configuration along with more memory modules which they took care of. That fixed our problem, and improved the memory access and speed of our MPI jobs.

Over the past year and a half the questions we had were like, “Hey, how do I fix this,” and the answer was “Try running this command line.” Or a response equally as simple.  And even if I don’t know what that command means, it solved the problem quickly and easily most of the time. What more do you need.

Interviewer: Who is your cluster vendor, and is there anything more you would like to say about them?

Tourret:  Atipa Technologies is our vendor. I appreciate the collaboration with them so far. Something that I really appreciated was being able to benchmark our programs with them before buying. For instance, when we wanted to try a new GPU or CPU we could just SSH in and test our real codes before making the purchase. When it’s possible, trying before you buy helps guide you to making the best purchase decisions.

A word from Atipa Technologies…

Damien Tourret is not the only one. Thousands of cluster end-users are struggling to keep clusters running on their own. Tourret is, however, one of the lucky ones. With the hindsight to purchase from a vendor who can provide priceless support and advice, as opposed to purchasing from an OEM with multiple support levels that would take days or even weeks to return a solution, his cluster has been running efficiently and reliably since the day it was delivered. In the end, what matters to researchers most is how quickly their simulations can be solved, even if the machines doing the work are mysterious, big, black boxes.

 

To find out more about Atipa Technologies solutions go to: www.atipa.com

For questions, or to request a quote contact: Dan Mantyla/ dmantyla@atipa.com

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!

Musk’s Latest Startup Eyes Brain-Computer Links

April 21, 2017

Elon Musk, the auto and space entrepreneur and severe critic of artificial intelligence, is forming a new venture that reportedly will seek to develop an interface between the human brain and computers. Read more…

By George Leopold

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

Nvidia P100 Shows 1.3-2.3x Speedup Over K80 GPU on Financial Apps

April 20, 2017

When it comes to the true performance of the latest silicon, every end user knows that the best processor is the one that works best for their application. Read more…

By Tiffany Trader

Quantum Adds Global Smarts to StorNext File System

April 20, 2017

Companies that use Quantum’s StorNext platform to store massive amounts of data this week got a glimpse of new storage capabilities that should make it easier to access their data horde from anywhere in the world. Read more…

By Alex Woodie

HPE Extreme Performance Solutions

HPC-Driven Weather Simulations Improving Forecasting Capabilities

In September of 1938, a massive hurricane traversed the Atlantic Ocean and made landfall in New England. Due to inadequate and incorrect forecasting, the storm struck farther north and with greater intensity than had been predicted, leaving residents and authorities with virtually no warning or time to properly prepare. Read more…

Scaling an HPC Career in Nepal Can Be a Steep Climb

April 20, 2017

Umesh Upadhyaya works as an IT Associate at the International Centre for Integrated Mountain Development (ICIMOD) in Nepal, which supports the country’s one and only HPC facility. He is directly involved in an initiative that focuses on climate change and atmosphere modeling Read more…

By Nages Sieslack

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). Read more…

By John Russell

Intel Open Sources All Lustre Work, Brent Gorda Exits

April 19, 2017

In a letter to the Lustre community posted on the Intel website, Vice President of Intel's Data Center Group Trish Damkroger writes that effective immediately the company will be contributing all Lustre development to the open source community. Damkroger also announced that Brent Gorda, General Manager, High Performance Data Division at Intel is leaving the company. 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

Hyperion (IDC) Paints a Bullish Picture of HPC Future

April 20, 2017

Hyperion Research – formerly IDC’s HPC group – yesterday painted a fascinating and complicated portrait of the HPC community’s health and prospects at the HPC User Forum held in Albuquerque, NM. HPC sales are up and growing ($22 billion, all HPC segments, 2016). 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

CERN openlab Explores New CPU/FPGA Processing Solutions

April 14, 2017

Through a CERN openlab project known as the ‘High-Throughput Computing Collaboration,’ researchers are investigating the use of various Intel technologies in data filtering and data acquisition systems. Read more…

By Linda Barney

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

Penguin Takes a Run at the Big Cloud Providers

April 12, 2017

HPC specialist Penguin Computing recently re-ran benchmarks from a study of its larger brethren and says the results show its ‘public cloud’ – Penguin on Demand (POD) – is among the leaders in cost and performance. Read more…

By John Russell

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

HPC and the Colocation Datacenter – a Bridge Too Far?

April 7, 2017

A more standardised HPC platform approach is making the running of HPC projects within increasing financial reach. Read more…

By Clive Longbottom, Quocirca

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 phase of neural networks (NN). 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 phase of neural networks (NN). 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. 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 campaign. 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 assets. 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

For IBM/OpenPOWER: Success in 2017 = (Volume) Sales

January 11, 2017

To a large degree IBM and the OpenPOWER Foundation have done what they said they would – assembling a substantial and growing ecosystem and bringing Power-based products to market, all in about three years. 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

TSUBAME3.0 Points to Future HPE Pascal-NVLink-OPA Server

February 17, 2017

Since our initial coverage of the TSUBAME3.0 supercomputer yesterday, more details have come to light on this innovative project. Of particular interest is a new board design for NVLink-equipped Pascal P100 GPUs that will create another entrant to the space currently occupied by Nvidia's DGX-1 system, IBM's "Minsky" platform and the Supermicro SuperServer (1028GQ-TXR). Read more…

By Tiffany Trader

Leading Solution Providers

Tokyo Tech’s TSUBAME3.0 Will Be First HPE-SGI Super

February 16, 2017

In a press event Friday afternoon local time in Japan, Tokyo Institute of Technology (Tokyo Tech) announced its plans for the TSUBAME3.0 supercomputer, which will be Japan’s “fastest AI supercomputer,” Read more…

By Tiffany Trader

IBM Wants to be “Red Hat” of Deep Learning

January 26, 2017

IBM today announced the addition of TensorFlow and Chainer deep learning frameworks to its PowerAI suite of deep learning tools, which already includes popular offerings such as Caffe, Theano, and Torch. Read more…

By John Russell

Is Liquid Cooling Ready to Go Mainstream?

February 13, 2017

Lost in the frenzy of SC16 was a substantial rise in the number of vendors showing server oriented liquid cooling technologies. Three decades ago liquid cooling was pretty much the exclusive realm of the Cray-2 and IBM mainframe class products. That’s changing. We are now seeing an emergence of x86 class server products with exotic plumbing technology ranging from Direct-to-Chip to servers and storage completely immersed in a dielectric fluid. Read more…

By Steve Campbell

BioTeam’s Berman Charts 2017 HPC Trends in Life Sciences

January 4, 2017

Twenty years ago high performance computing was nearly absent from life sciences. Today it’s used throughout life sciences and biomedical research. Genomics and the data deluge from modern lab instruments are the main drivers, but so is the longer-term desire to perform predictive simulation in support of Precision Medicine (PM). There’s even a specialized life sciences supercomputer, ‘Anton’ from D.E. Shaw Research, and the Pittsburgh Supercomputing Center is standing up its second Anton 2 and actively soliciting project proposals. There’s a lot going on. Read more…

By John Russell

HPC Startup Advances Auto-Parallelization’s Promise

January 23, 2017

The shift from single core to multicore hardware has made finding parallelism in codes more important than ever, but that hasn’t made the task of parallel programming any easier. Read more…

By Tiffany Trader

HPC Technique Propels Deep Learning at Scale

February 21, 2017

Researchers from Baidu’s Silicon Valley AI Lab (SVAIL) have adapted a well-known HPC communication technique to boost the speed and scale of their neural network training and now they are sharing their implementation with the larger deep learning community. Read more…

By Tiffany Trader

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

IDG to Be Bought by Chinese Investors; IDC to Spin Out HPC Group

January 19, 2017

US-based publishing and investment firm International Data Group, Inc. (IDG) will be acquired by a pair of Chinese investors, China Oceanwide Holdings Group Co., Ltd. Read more…

By Tiffany Trader

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