Seagate Sets Sights on Broader HPC Market

By John Russell

March 15, 2016

In a relatively short time, storage giant Seagate Technology has amped up its push into HPC. Today, four of the top ten supercomputer sites in the world run on Seagate, including all of the newcomers to the top ten, says Seagate[i]. It leads the SAGE project, a Horizon 2020 storage technology program in support of Europe’s exascale effort, and it’s the storage provider (with Cray) on the second phase of the Trinity Supercomputer at Los Alamos National Lab, which when finished will be the fastest storage system in the world at 1.6 TB/s.

“We have only been in the [HPC] business since about 2012,” said Ken Claffey, vice president of ClusterStor HPC and big data business. “The first [big HPC] system we ever really deployed broke the speed barrier; it was a 1TB/s system that we deployed with Cray at NCSA Blue Waters. Before that the fastest system in the world was the Spider (Lustre) system at Oak Ridge National Labs at just 250GB/s. We started with these high end systems and are now expanding through the [rest of] the top 100 and so forth.”

With $13.7 billion in revenue (2015) and 50,000 employees, Seagate (NASDAQ: STX) is a goliath that can’t be ignored. It manufactures on the order of one million drives per day according to Claffey, and spends approximately $900 million yearly on R&D that spans the “physics of the magnetic recording, material science, all the way up to file system and software development.”

Motivating Seagate’s heavy HPC pivot are current and future markets. Start with the current HPC-related storage sector, roughly a $4 billion pie. “Even when you are a $14-$15 billion dollar business, that’s a significant market,” said Claffey. Yet more important, he emphasized, is the collision of HPC and traditional enterprise technology, which is expanding the market.

Gaining HPC market share won’t happen easily. DataDirect Networks and IBM currently dominate what is a very fragmented HPC storage market with a long list of suppliers. They are all chasing what is the fastest growing segment in HPC; most are also eagerly expecting a rapid expansion of demand for high-end storage in the enterprise.

Seagate’s plunge into high performance computing was substantially driven by a series of acquisitions over the last 18 months costing more than $1 billion. (It’s nice to have resources.) Seagate acquired Xyratex (March 2014). It scooped up LSI’s broad flash portfolio (September 2014) from ASICs to PCIe cards to SSDs, and a large contingent of engineers (~600). Most recently, the acquisition of Dot Hill (October 2015) brought its portfolio of enterprise class RAID technology into Seagate.

Claffey came with the Xyratex acquisition. “People know Xyratex primarily for two areas,” said Claffey, “One was capital equipment and initially Seagate was one of our biggest customers. The second area was a business we started focused on developing a more engineered systems specifically for HPC.”

Ken Claffey
Ken Claffey

“Seagate has basically done these acquisitions all built around the HPC storage portfolio we have today,” said Claffey. Seagate’s vertical integration now covers fundamental storage media itself all the way up to the controllers, storage servers, file/fault systems, and storage cluster management software. “We have key intellectual property at every layer.”

“You can see by the investments we are making and some of the core technology innovations [introduced] that we’re focused on HPC because we believe that the architectures and technologies that we are creating to serve this market are informing us to the where the future of the enterprise is going,” he said.

The last few months have provided a glimpse of Seagate’s plans. At SC15, Seagate debuted a substantially updated ClusterStor line with Lustre and IBM Spectrum Scale (previously GPFS) offerings. It also introduced a new archiving platform and what it calls a ClusterStor HPC drive, specifically designed to boost performance in the ClusterStor line (more product details below). Just last week, Seagate demonstrated the fastest single flash-based SSD with throughput performance of 10 GB/; it’s scheduled for release this summer and meets Open Compute Project (OCP) specifications.

Having spent for product and expertise, and having made strides integrating both into its portfolio and organization, Seagate is now actively pursuing a higher profile in HPC. One of the clearest examples of the company’s effort to be associated with tip of the storage technology spear is its leadership of the SAGE project announced last October. This is Seagate’s first contribution to the European Commission (EC) Horizon 2020 Program. [ii]

SAGEUnder program guidelines, Seagate will provide next generation object storage based technologies through new APIs designed specifically for the exascale era. The idea is to create what Seagate calls “percipient storage” – storage that is purpose-built to meet both Big Data and Extreme Compute (BDEC) requirements. Certainly that’s a familiar clarion call in HPC and the enterprise.

The project will run for three years from September 2015 and has “eight fields of research, including: the study of the 1) application use cases co-designing solutions to address 2) Percipient Storage Methods, 3) Advanced Object Storage, and 4) tools for I/O optimization, supporting 5) next generation storage media and developing a supporting ecosystem of 6) Extreme Data Management, 7) Programming techniques and 8) Extreme Data Analysis tools.”

Malcolm Muggeridge, senior engineering director at Seagate based in the U.K. and another Xyratex veteran, is leading the initiative SAGE, which is one of 15 projects recently funded under Horizon 2020. Direct funding is actually through the European Technology Platforms (ETP) organization – “industry-led stakeholder groups recognized by the European Commission as key actors in driving innovation, knowledge transfer and European competitiveness. ETPs develop research and innovation agendas and roadmaps for action at EU and national level to be supported by both private and public funding.”

It probably doesn’t hurt that Muggeridge is vice chair of ETP. “We create the strategic research agenda which is the bible, if you like, that leads the way the programs will be laid out throughout the years of the horizon 2020 program.” The focuses of projects tend to be either technology or application-centric (centers of excellence) driven.

SAGE is focused on relieving storage IO problems and facilitating the capability to compute wherever the data is stored. Looking beyond burst-buffer approaches used now, the goal is to create a storage IO stack that can seamlessly accommodate next-gen NVRAM technologies without being locked in to any particular technology (resistive random access memory (RRAM or ReRAM) for example). Such an architecture, it’s expected, will ‘drastically’ reduce time-to-solution by moving compute to storage. A key to doing so will be use of novel extensions to existing objects.

As described by Sai Narasimhamurthy, Seagate research staff engineer responsible for coordinating the technical work, the stack would “have memory at the top, various NVRAM technologies in the middle, of course you have your flash technology as well as part of the stack, and then you have scratch disks and then archival disks.”

“You could have an object, or a piece of it, lying in high speed memory, a piece of it in NVRAM, and a piece of the object lying in scratch based upon the usage profile of the object,” explained Narasimhamurthy. “The view of the object is transparent to the application, it’s just I0 to an object, but on the back end you could have various types of layout which could be very interesting because you could optimize your layout for performance or for resiliency. You could do all sorts of things.”

Developing HSM tools is another important goal, said Muggeridge. “Currently in HPC you have some HSM tools which are very naïve and very simplistic and just work between the storage and the archive. In SAGE, we are looking to take advantage of the same concept that you can move object data, or piece of an object data, across the stack. So what are the policies that trigger these movements? There are lot of complex parameters that guide this data movement across the stack including all the inputs from the system administrator or equally machine-learning.”

Just six months old, SAGE is making good progress said Muggeridge. Work is following two tracks, one on design of the architecture and another for characterizing performance against different workloads. Eventually a small-scale system will be built and tested at European supercomputer. There’s a ninth-month review coming up in June to determine if the project is proceeding on schedule.

It bears repeating that much of the SAGE work is aimed at accommodating big data workloads (e.g. climate and nuclear fusion use cases now being studied) – as noted earlier, the fundamental idea is that the architecture will to handle most BDEC workflows.

clusterstor-l300-205x300If the SAGE program represents next-gen technology, Claffey said the recently refreshed ClusterStor product line is the current state of the art. At SC15, Seagate rolled the newest ClusterStor products which included a Lustre appliance (L300), IBM Spectrum Scale (G200) appliance, a new archiving product (A200) which works with the ClusterStor product line, and a Multi-Level Security for Lustre Storage (MLS) offering (SL200).

Seagate also introduced its ClusterStor HPC Drive, which it says can be integrated with the ClusterStor L300 for extra high-performing storage in big data environments; it supports up to four terabytes in a single drive slot with the highest sequential data rate of any hard disk drive on the market at 300 megabytes-per-second according to Seagate.

“It’s a hybrid drive. So not only have we done special things in terms of the rotation of the drive (runs at 7200 rpm) but we have also integrated a cache within the drive both for reads and writes and you see significant improvements, for example, at 4K random IO workload,” according to Claffey.

Connectivity improvements were also prominent. The L300 now supports Intel Omni-Path or Mellanox IB EDR Network (see diagram below) and offers performance increments of 12GB to 16GB/s per SSU (Scalable Storage Unit). Seagate promotes it as “the industry’s fastest converged scale-out platform.”

Seagate L300 OmniPath

The addition of the G200 offering means customers now have a ready Seagate choice between Lustre and Spectrum Scale solutions. In the last couple of years, there’s been a fair amount of jockeying between the two popular parallel files systems. Like most observers, Claffey said it’s not an either or question.

“In traditional HPC Lustre has obviously been very strong. All you have to do is look at the top 10 and top 20 systems. IBM (GPFS) or Spectrum Scale has been more successful in the commercial space. GPFS does a very good job where small files move around and in mixed workloads. If you are typically dealing with larger files, more sequential reads, that’s where luster is optimized and does a phenomenal job. If a customer application has a lot of small files and they are random we are going to steer them towards spectrum scale. If the customer has a smaller number of larger files, that’s where Lustre does really well.

“What we are seeing relative to mainstream NAS systems is the adoption of parallel file systems is growing and both luster and spectrum scale are benefiting from that option. Scale-out NAS solutions are struggling with the growth in terms of their performance requirements and the capacity scalability requirements,” he said.

Given the size of the HPC storage market the stakes are high and Seagate has put a fair number of chips on the table. Differentiating itself and its products will depend delivering performance and developing approaches to solve the data IO problem currently hobbling storage system performance. Virtually all suppliers offer some work-around; it’s a blend of cache and traffic monitoring techniques to make the storage ‘application aware.’

“All these options are basically caching, right, at what level, where are you doing the caching, and you are trying to get more flash into the system,” said Claffey who contends there are really just two options: 1) you can throw a lot of flash at it and that’s going to be an expensive option; or 2) you can come in with a more hybrid architecture.

“What we are proposing is a hybrid architecture. Our approach is to have multiple layers of caching but we do not want to add additional software layers into the stack. Users and storage systems builders are struggling to manage the movement of data within the software layers that are already there,” he said.

The Seagate approach is to add multiple layers of caching “within the file system itself both from a software perspective, from a hardware perspective and a system perspective without adding in an additional layer. Look at what Cray is doing. Look at what Intel is doing with the Aurora system. We think the majority of the market has already determined that that is probably the best approach rather than adding in more layers to an already complicated stack,” said Claffey

According to Claffey, Seagate customers have collectively stood up more than an exabyte of total storage – to put that into perspective the Titan supercomputer at ORNL has roughly 40 petabytes of storage. Claffey also said Seagate’s four largest storage installations are all in the oil and gas sector although he didn’t identify them.

It will be interesting to see how Seagate’s expansion into HPC affects the supplier landscape. There’s no lack of competitive zeal at Seagate. Claffey said about one prominent competitor, “If I show them in their most favorable light, in the most optimum, downhill, wind assisted configuration, I mean that very genuinely, actually it’s pretty comparable to our previous generation the cs9000 product.” Time will tell.

[i] Top500 List, 11/2015

[ii] In addition to Seagate Systems (UK) Limited, the SAGE participants include Allinea Software  (UK),  BULL SAS (Atos SE) (France), Culham Centre for Fusion Energy (CCFE)  (UK), French Alternative Energies and Atomic Energy Commission (CEA) (France), Deutsches Forschungszentrum für Künstliche Intelligenz (DFKI) (Germany), Diamond Light Source (UK), Forschungszentrum Jülich (Germany), Kungliga Tekniska Hoegskolan (KTH) (Sweden) and the Science and Technology Facilities Council (STFC) (UK).

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 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

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 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

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

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

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

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