Spider Up and Spinning Connections to All Computing Platforms at ORNL

By Agatha Bardoel

July 9, 2009

Spider, the world’s biggest Lustre-based, centerwide file system, has been fully tested to support Oak Ridge National Laboratory’s (ORNL’s) new petascale Cray XT4/XT5 Jaguar supercomputer and is now offering early access to scientists.

An extremely high-performance file system, Spider has 10.7 petabytes of disk space and can move data at more than 240 gigabytes a second. “It is the largest-scale Lustre file system in existence,” said Galen Shipman, Technology Integration Group leader at ORNL’s National Center for Computational Sciences (NCCS). “What makes Spider different [from large file systems at other centers] is that it is the only file system for all our major simulation platforms, both capable of providing peak performance and globally accessible.”

Ultimately, it will connect to all of ORNL’s existing and future supercomputing platforms as well as off-site platforms across the country via GridFTP (a protocol that transports large data files), making data files accessible from any site in the system.

Shipman said Spider has demonstrated stability on the XT5 and XT4 partitions of Jaguar, on Smoky (the center’s development cluster), and on Lens (the center’s visualization and data analysis cluster). “We’ve had all these systems running on the file system concurrently, with over 26,000 compute nodes (clients) mounting the file system and performing I/O [input and output]. It’s the largest demonstration of Lustre scalability in terms of client count ever achieved.”

Shipman said the file system is designed to support the latest incarnation of Jaguar, which is capable of 1.64 quadrillion calculations a second (1.64 petaflops). “When they told us they needed a file system to support it, we could not just pick up the phone and order one,” he said. “No vendor could deliver such a system, so we essentially trail-blazed.”

It was a phased approach. ORNL computer scientists and technicians (David Dillow, Jason Hill, Ross Miller, Sarp Oral, Feiyi Wang, and James Simmons) worked in close collaboration with partners Cray Inc., Data Direct Networks (DDN), Sun Microsystems, and Dell to bring Spider online. Cray provided the expertise to make the file system available on both Jaguar XT4 and Jaguar XT5. DDN provided 48 DDN 9900 storage arrays, Sun provided the Lustre parallel file system software, and Dell provided 192 I/0 servers. The vendors’ collaboration has produced a system which manages 13,000 disks and provides over 240 GB/s of throughput, a file system cluster that rivals the computational capability of many high-performance compute clusters.

The Spider parallel file system is similar to the disk in a conventional laptop — multiplied 13,000 times. A file system cluster sits in front of the storage arrays to manage the system and project a parallel file system to the computing platforms. A large-scale InfiniBand-based system area network connects Spider to each NCCS system, making data on Spider instantly available to them all.

“As new systems are deployed at the NCCS, we just plug them into our system area network; it is really about a backplane of services,” Shipman said. “Once they are plugged into the backplane, they have access to Spider and to HPSS [the center’s high-performance storage system] for data archival.  Users can access this file system from anywhere in the center. It really decouples data access and storage from individual systems.”
 
Before Spider each computing platform had its own file system. Once a project ran an application on Jaguar, it then had to move the data to the Lens visualization platform for analysis. Any problem encountered along the way would necessitate that the cumbersome process be repeated. With Spider connected to both Jaguar and Lens, however, this headache is avoided. “You can think of it as eliminating islands of data. Instead of having to multiply file systems all within the NCCS, one for each of our simulation platforms, we have a single file system that is available anywhere. If you are using extremely large data sets on the order of 200 terabytes, it could save you hours and hours.”

“Spider is one of the most important steps the NCCS has taken toward increasing the scientific productivity of our users,” said Bronson Messer, of the Scientific Computing Group and a participant in the “Three-Dimensional Model of SN1987A Frontier” early science project. “Sophisticated users have been asking for this, while new users I have spoken with immediately see the advantages and become very excited.”

Spider will have both scratch space (short-term storage for files involved in simulations, data analysis, etc.) and long-term storage for each user. Shipman said the technology integration team is now working with Sun to prepare for future NCCS platforms with even more daunting requirements.

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!

China’s Expanding Effort to Win in Microchips

July 27, 2017

The global battle for preeminence, or at least national independence, in semiconductor technology and manufacturing continues to heat up with Europe, China, Japan, and the U.S. all vying for sway. A fascinating article ( Read more…

By John Russell

Hyperion: Storage to Lead HPC Growth in 2016-2021

July 27, 2017

Global HPC external storage revenues will grow 7.8% over the 2016-2021 timeframe according to an updated forecast released by Hyperion Research this week. HPC server sales, by comparison, will grow a modest 5.8% to $14.8 Read more…

By John Russell

Exascale FY18 Budget – The Senate Provides Their Input

July 27, 2017

In the federal budgeting world, “regular order” is a meaningful term that is fondly remembered by members of both the Congress and the Executive Branch. Regular order is the established process whereby an Administrat Read more…

By Alex R. Larzelere

HPE Extreme Performance Solutions

HPE Servers Deliver High Performance Remote Visualization

Whether generating seismic simulations, locating new productive oil reservoirs, or constructing complex models of the earth’s subsurface, energy, oil, and gas (EO&G) is a highly data-driven industry. Read more…

India Plots Three-Phase Indigenous Supercomputing Strategy

July 26, 2017

Additional details on India's plans to stand up an indigenous supercomputer came to light earlier this week. As reported in the Indian press, the Rs 4,500-crore (~$675 million) supercomputing project, approved by the Ind Read more…

By Tiffany Trader

Exascale FY18 Budget – The Senate Provides Their Input

July 27, 2017

In the federal budgeting world, “regular order” is a meaningful term that is fondly remembered by members of both the Congress and the Executive Branch. Reg Read more…

By Alex R. Larzelere

India Plots Three-Phase Indigenous Supercomputing Strategy

July 26, 2017

Additional details on India's plans to stand up an indigenous supercomputer came to light earlier this week. As reported in the Indian press, the Rs 4,500-crore Read more…

By Tiffany Trader

Tuning InfiniBand Interconnects Using Congestion Control

July 26, 2017

InfiniBand is among the most common and well-known cluster interconnect technologies. However, the complexities of an InfiniBand (IB) network can frustrate the Read more…

By Adam Dorsey

NSF Project Sets Up First Machine Learning Cyberinfrastructure – CHASE-CI

July 25, 2017

Earlier this month, the National Science Foundation issued a $1 million grant to Larry Smarr, director of Calit2, and a group of his colleagues to create a comm Read more…

By John Russell

Graphcore Readies Launch of 16nm Colossus-IPU Chip

July 20, 2017

A second $30 million funding round for U.K. AI chip developer Graphcore sets up the company to go to market with its “intelligent processing unit” (IPU) in Read more…

By Tiffany Trader

Fujitsu Continues HPC, AI Push

July 19, 2017

Summer is well under way, but the so-called summertime slowdown, linked with hot temperatures and longer vacations, does not seem to have impacted Fujitsu's out Read more…

By Tiffany Trader

Researchers Use DNA to Store and Retrieve Digital Movie

July 18, 2017

From abacus to pencil and paper to semiconductor chips, the technology of computing has always been an ever-changing target. The human brain is probably the com Read more…

By John Russell

The Exascale FY18 Budget – The Next Step

July 17, 2017

On July 12, 2017, the U.S. federal budget for its Exascale Computing Initiative (ECI) took its next step forward. On that day, the full Appropriations Committee Read more…

By Alex R. Larzelere

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

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

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

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

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

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’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

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

Leading Solution Providers

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

Reinders: “AVX-512 May Be a Hidden Gem” in Intel Xeon Scalable Processors

June 29, 2017

Imagine if we could use vector processing on something other than just floating point problems.  Today, GPUs and CPUs work tirelessly to accelerate algorithms Read more…

By James Reinders

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

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

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

Six Exascale PathForward Vendors Selected; DoE Providing $258M

June 15, 2017

The much-anticipated PathForward awards for hardware R&D in support of the Exascale Computing Project were announced today with six vendors selected – AMD Read more…

By John Russell

Top500 Results: Latest List Trends and What’s in Store

June 19, 2017

Greetings from Frankfurt and the 2017 International Supercomputing Conference where the latest Top500 list has just been revealed. Although there were no major Read more…

By Tiffany Trader

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