Catalyst Supercomputer at LLNL Available for Collaborative Research

May 7, 2014

May 7 — Catalyst, a first-of-a-kind supercomputer at Lawrence Livermore National Laboratory (LLNL), is available to industry collaborators to test big data technologies, architectures and applications.

Developed by a partnership of CrayIntel and Lawrence Livermore, this Cray CS300 high performance computing (HPC) cluster is available for collaborative projects with industry through Livermore’s High Performance Computing Innovation Center (HPCIC).

“Over the next decade, global data volume is forecasted to reach more than 35 zettabytes,” (a zettabyte is a trillion gigabytes) said Fred Streitz, director of the HPCIC. “That enormous amount of unstructured data provides an opportunity. But how do we extract value and inform better decisions out of that wealth of raw information?”

A resource for the National Nuclear Security Administration’s (NNSA) Advanced Simulation and Computing (ASC) program, the 150 teraflop/s (trillion floating operations per second) Catalyst cluster has 324 nodes, 7,776 cores and employs the latest-generation 12-core Intel Xeon E5-2695v2 processors. Catalyst runs the NNSA-funded Tri-lab Open Source Software (TOSS) that provides a common user environment across NNSA Tri-lab clusters (Los Alamos, Sandia and Lawrence Livermore national labs).

“The opportunity to work with Cray and Intel to design and deploy Catalyst, a novel computing platform optimized for HPC-end applications, has been very exciting,” said Robin Goldstone, Livermore HPC Solutions architect. “We have modified the Cray CS300 architecture in ways that make Catalyst an outstanding HPC platform for data-intensive computing.”

Catalyst features include 128 gigabytes (GB) of dynamic random access memory (DRAM) per node, 800 GB of non-volatile memory (NVRAM) per compute node, 3.2 terabytes (TB) of NVRAM per Lustre router node, and improved cluster networking with dual rail Quad Data Rate (QDR-80) Intel TrueScale fabrics. The addition of an expanded node local NVRAM storage tier based on PCIe high-bandwidth Intel Solid State Drives (SSD) allows for the exploration of new approaches to application check-pointing, in-situ visualization, out-of-core algorithms and big data analytics. NVRAM is familiar to anyone who uses USB sticks or an MP3 player; it is simply memory that is persistent and that remains on files even when the power is off, hence “non-volatile.”

Deployed in October 2013, the Catalyst architecture already has begun to provide insights into the kind of technologies the ASC program will require over the next decade to meet high performance simulation and big data computing mission needs. The increased storage capacity of the system (in both volatile and nonvolatile memory) represents the major departure from classic simulation-based computing architectures common at DOE laboratories and opens new opportunities for exploring the potential of combining floating point focused capability with data analysis in one environment. The machine’s expanded DRAM and fast, persistent NVRAM are well suited to a broad range of big data problems including bioinformatics, business analytics, machine learning and natural language processing.

Jonathan Allen, a Lawrence Livermore bioinformatics scientist, is working on new methods to rapidly detect and characterize pathogenic organisms such as viruses, bacteria or fungi in a biological sample.

“We’re working on developing scalable analysis tools for next generation sequencing, in particular metagenomic sequencing,” Allen said. “By comparing short genetic fragments in a query dataset against a large searchable index of genomes, we can make determinations about the potential threat an organism poses to human health.”

Traditional technologies and storage limitations made it challenging to rapidly search a database of reference genomes as more organisms were sequenced and more variants in the population of an organism were included. With Catalyst’s unique architecture, Allen and his team are able to store very large reference databases of genomes in memory and execute expansive analyses with higher resolution.

“We were able to do a metagenomic analysis on a fairly large sample in several hours on a single desktop. With Catalyst, we can process many hundreds of equal size in about the same time.”

Catalyst also will serve to host very large models for video analytics and machine learning.

“YouTube claims that 100 hours of video are uploaded to its website every minute,” explained Doug Poland, computational engineer working on video analytics. “As the fastest-growing type of content on the Internet, consumer-produced videos are a wealth of information about the world that’s essentially untapped.”

Yet current tools are unable to search through the richness of video elements such as visual, audio and motion, and associated metadata like semantic tags and geo-coordinates. Poland and his team are looking to build more complex models that consider the sum of those features, and that can be recognized in real-time for user-specific search needs.

“Catalyst allows us to explore entirely new deep learning architectures that could have a huge impact on video analytics as well as broader application to big data analytics.”

“Our purpose is to use Catalyst as a test bed to develop optimization strategies for data-intensive computing,” Streitz said. “We believe that advancing big data technology is a key to accelerating the innovation that underpins our economic vitality and global competiveness.”

Companies interested in access to Catalyst are invited to respond to the posted Notice of Opportunity through the Federal Business Opportunities website and visit the HPC Innovation Center website.

Source: Donald B. Johnston, Lawrence Livermore National Laboratory

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!

Researchers Scale COSMO Climate Code to 4888 GPUs on Piz Daint

October 17, 2017

Effective global climate simulation, sorely needed to anticipate and cope with global warming, has long been computationally challenging. Two of the major obstacles are the needed resolution and prolonged time to compute Read more…

By John Russell

UCSD Web-based Tool Tracking CA Wildfires Generates 1.5M Views

October 16, 2017

Tracking the wildfires raging in northern CA is an unpleasant but necessary part of guiding efforts to fight the fires and safely evacuate affected residents. One such tool – Firemap – is a web-based tool developed b Read more…

By John Russell

Exascale Imperative: New Movie from HPE Makes a Compelling Case

October 13, 2017

Why is pursuing exascale computing so important? In a new video – Hewlett Packard Enterprise: Eighteen Zeros – four HPE executives, a prominent national lab HPC researcher, and HPCwire managing editor Tiffany Trader Read more…

By John Russell

HPE Extreme Performance Solutions

Transforming Genomic Analytics with HPC-Accelerated Insights

Advancements in the field of genomics are revolutionizing our understanding of human biology, rapidly accelerating the discovery and treatment of genetic diseases, and dramatically improving human health. Read more…

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Intel Delivers 17-Qubit Quantum Chip to European Research Partner

October 10, 2017

On Tuesday, Intel delivered a 17-qubit superconducting test chip to research partner QuTech, the quantum research institute of Delft University of Technology (TU Delft) in the Netherlands. The announcement marks a major milestone in the 10-year, $50-million collaborative relationship with TU Delft and TNO, the Dutch Organization for Applied Research, to accelerate advancements in quantum computing. Read more…

By Tiffany Trader

Fujitsu Tapped to Build 37-Petaflops ABCI System for AIST

October 10, 2017

Fujitsu announced today it will build the long-planned AI Bridging Cloud Infrastructure (ABCI) which is set to become the fastest supercomputer system in Japan Read more…

By John Russell

HPC Chips – A Veritable Smorgasbord?

October 10, 2017

For the first time since AMD's ill-fated launch of Bulldozer the answer to the question, 'Which CPU will be in my next HPC system?' doesn't have to be 'Whichever variety of Intel Xeon E5 they are selling when we procure'. Read more…

By Dairsie Latimer

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Intel Debuts Programmable Acceleration Card

October 5, 2017

With a view toward supporting complex, data-intensive applications, such as AI inference, video streaming analytics, database acceleration and genomics, Intel i Read more…

By Doug Black

OLCF’s 200 Petaflops Summit Machine Still Slated for 2018 Start-up

October 3, 2017

The Department of Energy’s planned 200 petaflops Summit computer, which is currently being installed at Oak Ridge Leadership Computing Facility, is on track t Read more…

By John Russell

US Exascale Program – Some Additional Clarity

September 28, 2017

The last time we left the Department of Energy’s exascale computing program in July, things were looking very positive. Both the U.S. House and Senate had pas Read more…

By Alex R. Larzelere

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute 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

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

NERSC Scales Scientific Deep Learning to 15 Petaflops

August 28, 2017

A collaborative effort between Intel, NERSC and Stanford has delivered the first 15-petaflops deep learning software running on HPC platforms and is, according Read more…

By Rob Farber

Oracle Layoffs Reportedly Hit SPARC and Solaris Hard

September 7, 2017

Oracle’s latest layoffs have many wondering if this is the end of the line for the SPARC processor and Solaris OS development. As reported by multiple sources Read more…

By John Russell

US Coalesces Plans for First Exascale Supercomputer: Aurora in 2021

September 27, 2017

At the Advanced Scientific Computing Advisory Committee (ASCAC) meeting, in Arlington, Va., yesterday (Sept. 26), it was revealed that the "Aurora" supercompute Read more…

By Tiffany Trader

Google Releases Deeplearn.js to Further Democratize Machine Learning

August 17, 2017

Spreading the use of machine learning tools is one of the goals of Google’s PAIR (People + AI Research) initiative, which was introduced in early July. Last w Read more…

By John Russell

GlobalFoundries Puts Wind in AMD’s Sails with 12nm FinFET

September 24, 2017

From its annual tech conference last week (Sept. 20), where GlobalFoundries welcomed more than 600 semiconductor professionals (reaching the Santa Clara venue Read more…

By Tiffany Trader

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

Leading Solution Providers

Amazon Debuts New AMD-based GPU Instances for Graphics Acceleration

September 12, 2017

Last week Amazon Web Services (AWS) streaming service, AppStream 2.0, introduced a new GPU instance called Graphics Design intended to accelerate graphics. The 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

EU Funds 20 Million Euro ARM+FPGA Exascale Project

September 7, 2017

At the Barcelona Supercomputer Centre on Wednesday (Sept. 6), 16 partners gathered to launch the EuroEXA project, which invests €20 million over three-and-a-half years into exascale-focused research and development. Led by the Horizon 2020 program, EuroEXA picks up the banner of a triad of partner projects — ExaNeSt, EcoScale and ExaNoDe — building on their work... Read more…

By Tiffany Trader

Cray Moves to Acquire the Seagate ClusterStor Line

July 28, 2017

This week Cray announced that it is picking up Seagate's ClusterStor HPC storage array business for an undisclosed sum. "In short we're effectively transitioning the bulk of the ClusterStor product line to Cray," said CEO Peter Ungaro. Read more…

By Tiffany Trader

Delays, Smoke, Records & Markets – A Candid Conversation with Cray CEO Peter Ungaro

October 5, 2017

Earlier this month, Tom Tabor, publisher of HPCwire and I had a very personal conversation with Cray CEO Peter Ungaro. Cray has been on something of a Cinderell Read more…

By Tiffany Trader & Tom Tabor

Intel Launches Software Tools to Ease FPGA Programming

September 5, 2017

Field Programmable Gate Arrays (FPGAs) have a reputation for being difficult to program, requiring expertise in specialty languages, like Verilog or VHDL. Easin Read more…

By Tiffany Trader

IBM Advances Web-based Quantum Programming

September 5, 2017

IBM Research is pairing its Jupyter-based Data Science Experience notebook environment with its cloud-based quantum computer, IBM Q, in hopes of encouraging a new class of entrepreneurial user to solve intractable problems that even exceed the capabilities of the best AI systems. Read more…

By Alex Woodie

Intel, NERSC and University Partners Launch New Big Data Center

August 17, 2017

A collaboration between the Department of Energy’s National Energy Research Scientific Computing Center (NERSC), Intel and five Intel Parallel Computing Cente Read more…

By Linda Barney

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