Cray XT5m Midrange Supercomputer Builds Market Momentum

By Nicole Hemsoth

September 28, 2009

In March 2009, Cray announced the Cray XT5m system, a compatible midrange extension of the high-end Cray XT5 product line that was first to break the sustained petaflop performance barrier on real-world applications. HPCwire asked Barry Bolding, Cray’s vice president of scalable systems, for an update on the midrange product.

Cray XT5HPCwire: How is the Cray XT5m midrange supercomputer doing in the market place?

Bolding: We disclosed one customer name with the March announcement, the High Performance Computing Center Stuttgart, where it’s being used for automotive, academic and public sector work. We have also publically announced a second customer, the Finnish Meteorological Institute (FMI) in the production weather forecasting segment. The Cray XT5m has been meeting our sales goals since then. Granted, our expectations for the first six months were fairly modest because the midrange is a new space for us and we viewed this as a learning period. The good news is that we have validated that the XT5m can be a leader in the mid-range. We have won customers in several of our key target segments and our pricing is very competitive in this price sensitive space so we expect higher volumes going forward. Today we have a large number of bids outstanding in academia, automotive, aerospace, pharma and weather forecasting, as well as in government and R&D labs.

HPCwire: Why did Cray decide to develop this product?

Bolding: There were several reasons. We were consistently running into procurements that were in the midrange and needed a more price-competitive system for that space, which we view as a growth area for us. According to IDC, Cray is the current global market share leader for HPC systems priced at $3 million and up, but we have a very small presence in the midrange segment. Many of the characteristics of our largest machines are applicable in the midrange, but to succeed in this space we needed to develop a price-competitive product, turn around procurements faster, and provide a wider range of ISV applications. ISV applications are also important at the high end, but industry typically buys midrange systems and relies more heavily on third-party apps than government and academia do. The Cray XT5m is the initial product on our midrange roadmap.

HPCwire: Why would someone buy a Cray XT5m system instead of a same-size cluster? What are the key differences?

Bolding: Primarily they get Cray’s more capable SeaStar interconnect and interconnect roadmap. The Cray SeaStar has proven itself over the past several years as the industry-leading interconnect for MPI scalability.  With the Cray SeaStar interconnect, the Cray XT5m handles complex messaging traffic very efficiently.  You also get the entire Cray software stack that has been scaled and validated up to the petascale performance level, plus the network roadmap driving toward global addressability and high-performance UPC and Co-Array Fortran, along with MPI of course. So, Cray XT5m customers are buying into a broader portfolio than just a typical midrange system.  They’re buying into the demonstrated petascale scalability of the XT5 architecture. To achieve true scaling today, even at midrange size, one needs a full portfolio of network, software and infrastructure support, which Cray provides in the XT5m. And with multicore processors becoming prevalent, users will soon be facing the need to scale substantially higher even with midrange systems, especially starting in 2010.  Our midrange systems are designed to benefit from Cray’s high-end system development and this will continue. For example, the Cray XT5m line provides the same TCO benefits to our midrange customers as our largest supercomputer customers enjoy with the ECOphlex cooling technology we developed for petascale systems.

HPCwire: Assuming the Cray XT5m has a more capable network and memory subsystem than a standard cluster, with better bandwidth and latency characteristics, wouldn’t it be able to tackle a broader range of applications efficiently?

Bolding: The Cray XT5m today is a midrange industry leader from a network bandwidth and latency perspective. This gives users an important advantage over commodity InfiniBand networks and allows the Cray XT5m to handle a broader range of applications efficiently. The system is aimed at codes scaling to 256 cores and beyond, and in this range users typically see significant benefits from the overall system and software design.

HPCwire: Are customers using their Cray XT5m systems as their main HPC systems or for specific portions of their workloads?

Bolding: It varies. In production weather forecasting, we have a customer using it as their primary production system. At academic sites it varies from being primary system to one among multiple HPC systems. Some users are experimenting with the new functionalities, including the network features and the Cray software and compilers. It’s also allowing users to experiment with scalability in ways they haven’t been able to do before. So, the Cray XT5m is being used both as a development platform and a production platform.

HPCwire: Is there any customer who operates both a Cray XT5 and a Cray XT5m system?

Bolding: There are customers running applications across both Cray XT5 and Cray  XT5m systems, although they don’t have both systems in-house today.  By the end of this year, we’ll have sites that have both in their data centers.

HPCwire: The XT5m is a compatible downward extension of the Cray XT5 architecture, but uses a 2D torus interconnect instead of the XT5’s 3D torus. What’s the strategy behind this change?

Bolding: It’s a cost-saving strategy for the midrange scale. With a Cray XT5m system consisting of 1-6 cabinets, customers tend not to have applications that require the full 3D topology as much as with a larger, high-end Cray XT5. We right-sized the Cray XT5m for midrange requirements, including the interconnect, allowing us to provide a price-competitive product in this space. We’ve done extensive studies on application performance on the Cray XT5m, and there has been minimal performance impact at six cabinets and below. Above that size, you need the Cray XT5’s 3D torus to maintain scalability. For most apps in the 1-6 cabinet range, performance degradation due to the topology is less than 5 percent even for applications running across several thousand cores of a Cray XT5m.

HPCwire: If a site maxes out on their XT5m, what’s the upgrade path to a Cray XT5 system?

Bolding: It’s very simple. Today, it just involves replacing the network mezzanine card and adding more cables to transform the 2D torus into a 3D torus. We’ll make the upgrade path even simpler in the future of our midrange systems.

HPCwire: Do you expect some users to take advantage of non-MPI programming models that are available on the XT5m, such as SHMEM, UPC and Co-Array Fortran?

Bolding: We do. We port those in the software today and will be making announcements of enhancements to the hardware support for some of these features in the next 12 months. We are committed to making more innovations and remaining a leader in HPC, and this requires providing our customers with multiple, high performance programming models.

HPCwire: What is the Data Virtualization Service that comes with the XT5 and XT5m, and why is it important?

Bolding: DVS is an important part of Cray systems. DVS is a flexible virtualization layer that Cray plans use to expand our software functionality and performance . One feature of DVS is that it can allow Cray to project various file systems onto the compute nodes (which are diskless on Cray XT5 systems). This allows Cray systems to act more like a standard commodity cluster if it needs to.  We support IO and storage functionalities that we haven’t in the past. We can share file systems with high-performance file systems on platforms other than clusters. Customers such as NERSC and Oak Ridge are doing very innovative things with file systems and DVS can play a role in providing the flexibility they need.  So, DVS helps us both with compute and IO/storage.

HPCwire: Where is the Cray XT5m product line headed in the future?

Bolding: We are going to continue driving into the midrange market, which is a segment that has excellent growth opportunities for Cray. We want to build a substantial and sustainable market presence there, especially with customers focused on scalability of applications. To grow the XT5m line we need to continue to be competitive on cost while improving price/performance, network scalability,  software features and ISV availability, and we’ll be doing all those things. We’ll also be improving the processor roadmap with new technologies coming into market place. Cray’s innovation, combined with AMD’s strong roadmap is a winning combination for the next few years for the entire XT family of systems. 
HPCwire: What should we look for next?

Bolding: At SC09, we plan to talk more specifically about our future plans for the Cray XT5m product line.

For more information on how the Cray XT5m is making petaflops performance affordable, download the AMD white paper here.

 

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!

TACC Helps ROSIE Bioscience Gateway Expand its Impact

April 26, 2017

Biomolecule structure prediction has long been challenging not least because the relevant software and workflows often require high end HPC systems that many bioscience researchers lack easy access to. Read more…

By John Russell

Messina Update: The U.S. 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

IBM, Nvidia, Stone Ridge Claim Gas & Oil Simulation Record

April 25, 2017

IBM, Nvidia, and Stone Ridge Technology today reported setting the performance record for a “billion cell” oil and gas reservoir simulation. Read more…

By John Russell

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

HPE Extreme Performance Solutions

Remote Visualization Optimizing Life Sciences Operations and Care Delivery

As patients continually demand a better quality of care and increasingly complex workloads challenge healthcare organizations to innovate, investing in the right technologies is key to ensuring growth and success. Read more…

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 a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

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

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

Messina Update: The U.S. 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

ASC17 Makes Splash at Wuxi Supercomputing Center

April 24, 2017

A record-breaking twenty student teams plus scores of company representatives, media professionals, staff and student volunteers transformed a formerly empty hall inside the Wuxi Supercomputing Center into a bustling hub of HPC activity, kicking off day one of 2017 Asia Student Supercomputer Challenge (ASC17). Read more…

By Tiffany Trader

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 a new generation of chips designed specifically for deep learning workloads. Read more…

By Alex Woodie

NERSC Cori Shows the World How Many-Cores for the Masses Works

April 21, 2017

As its mission, the high performance computing center for the U.S. Department of Energy Office of Science, NERSC (the National Energy Research Supercomputer Center), supports a broad spectrum of forefront scientific research across diverse areas that includes climate, material science, chemistry, fusion energy, high-energy physics and many others. Read more…

By Rob Farber

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

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

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

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

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

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

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

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

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

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

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