Titan Sets High Water Mark for GPU Supercomputing

By Michael Feldman

October 29, 2012

Oak Ridge National Laboratory (ORNL) has officially launched its much-anticipated Titan supercomputer, a Cray XK7 machine that will challenge IBM’s Sequoia for petaflop supremacy. With Titan, ORNL gets a system that is 10 times as powerful as Jaguar, the lab’s previous top system upon which the new machine is based. With a reported 27 peak petaflops, Titan now represents the most powerful number-cruncher in the world.

The 10-fold performance leap from Jaguar to Titan is courtesy of NVIDIA’s brand new K20 processors – the Kepler GPU that will be formally released sometime before the end of the year. Although the Titan upgrade also includes AMD’s latest 16-core Opteron CPUs, the lion’s share of the FLOPS will be derived from the NVIDIA chips.

In the conversion from Jaguar, a Cray XT5, ORNL essentially gutted the existing 200 cabinets and retrofitted them with nearly ten thousand XK7 blades. Each blade houses two nodes and each one of them holds a 16-core Opteron 6274 CPU and a Tesla K20 GPU module. The x86 Opteron chips run at a respectable 2.2 GHz, while the K20 hums along at a more leisurely 732 MHz. But because to the highly parallel nature of the GPU architecture, the K20 delivers around 10 times the FLOPS as its CPU companion. (Using the 27 peak PF value for Titan, a back-of-the-envelope calculation puts the new K20 at about 1.2-1.3 double precision teraflops.)

Thanks to the energy efficiency of the K20, which NVIDIA claims is going to three times as efficient its previous-generation Fermi GPU, Titan draws a mere 12.7 MW to power the whole system. That’s especially impressive when you consider that the x86-only Jaguar required 7 megawatts for a mere tenth of the FLOPS.

It would appear, though, that IBM’s Blue Gene/Q may retain the crown for energy-efficient supercomputing. The Sequoia system at Lawrence Livermore Lab draws just 7.9 MW to power its 20 peak petaflops. However, it’s a little bit of apples and oranges here. That 7.9 MW is actually the power draw for Sequoia’s Linpack run, which topped out at 16 petaflops. Since we don’t have the Linpack results for Titan just yet, it’s hard to tell if the GPU super will be able to come out ahead of Blue Gene/Q platform.

For multi-petaflopper, Titan is a little shy on memory capacity, claiming just 710 terabytes – 598 TB on the CPU side and 112 TB for the GPUs. The FLOPS-similar Sequoia has more than twice that – nearly 1.6 petabytes. Back in the day, the goal for balanced supercomputing was at least one byte of memory for every FLOP, but that era is long gone.

Titan provides around 1/40 of a byte per FLOP and from the GPU’s point of view, most of the memory on the wrong side of the PCIe bus – that is, next to the CPU. Welcome to the new normal.

Titan is more generous with disk space though, 13.6 PB in all, although again, a good deal less than that of its Sequoia cousin at 55 PB. Apparently disk storage is being managed by 192 Dell I/O servers, which, in aggregate, provide 240 GB/second of bandwidth to the storage arrays.
Titan’s big claim to fame is that it’s the first GPU-accelerated supercomputer in the world that’s has been scaled into the multi-petaflop realm. IBM’s Blue Gene/Q and Fujitsu’s K computer — both powered by custom CPU SoCs — are the only other platforms that have broken the 10-petaflop mark. Titan is also the first GPU-equipped machine of any size in the US. As such, it will provide a test platform for a lot of big science codes that have yet to take advantage of accelerators at scale.

Acceptance testing is already underway at Oak Ridge and users are in the process of porting and testing a variety of DOE-type science applications to the CPU-GPU supercomputer. These include codes in climate modeling (CAM-SE), biofuels (LAMMPS), astrophysics (NRDF), combustion (S3D), material science (WL-LSMS), and nuclear energy (Denovo).

According to Markus Eisenbach, his team has already been able to run the WL-LSMS code above the 10-petaflop mark on Titan. He says that level of performance will allow them to study the behavior of materials at temperatures above the point where they lose their magnetic properties.

At the National Center for Atmospheric Research (NCAR), they are already using the new system to speed atmospheric modeling codes. With Titan, Warren Washington’s NCAR team has been able to execute high-resolution models representing one to five years of simulations in just one computing day. On Jaguar, a computing day yielded only three months worth of simulations.

ORNL’s Tom Evans is using Titan cycles to model nuclear energy production. The simulations are for the purpose of improving the safety and performance of the reactors, while reducing the amount of waste. According to Evans, they’ve been able to run 3D simulations of a nuclear reactor core in hours, rather than weeks.

The machine will figure prominently into the upcoming INCITE awards. INCITE, which stands for Innovative and Novel Computation Impact on Theory of Experiment, is the DOE’s way of sharing with  the FLOPS with scientists and industrial users on the agency’s fastest machines. The program only accepts proposals for end users with “grand challenge”-type problems worthy of top tier supercomputing.

With its 20-plus-petaflop credentials, Titan will be far and away the most powerful system available for open science. (Sequoia belongs to the NNSA and spends most its cycles on classified nuclear weapons codes.) The DOE has received a record number of proposals for the machine, representing three times what Titan will be able to donate to the INCITE program.

Undoubtedly some of that pent-up demand is a result of the delayed entry of the US into GPU-accelerated supers. Over the past three years, American scientists and engineers have watched heterogeneous petascale systems being built overseas. China (with Tianhe-1A, Nebulae, and Mole 8.5), Japan (with TSUBAME 2.0), and even Russia (with Lomonosov) all managed to deploy ahead of the US.

Some of that is due to the slow uptake of GPU computing by IBM and Cray, the US government’s two largest providers of top tier HPC machinery. IBM offers GPU-accelerated gear on it x86 cluster offerings, but its flagship supercomputers are based on their in-house Blue Gene and Power franchises. Cray waited until May 2011 to deliver its first GPU-CPU platform, the XK6 (with Fermi Tesla GPUs), preferring to skip the earlier renditions of NVIDIA technology.

While Titan could be viewed as just another big supercomputer, there is a lot on the line here, especially for NVIDIA. If the system can be a productive petascale machine, it will go a long way toward establishing the company’s GPU computing architecture as the go-to accelerator technology for the path to exascale. The development that makes this less than assured is the imminent emergence of Intel’s Xeon Phi manycore coprocessor, and to a lesser extent, AMD’s future GPU and APU platforms.

Intel will get its initial chance to prove Xeon Phi’s worth as an HPC accelerator with Stampede, a 10 petaflop supercomputer that will be installed at the Texas Advanced Computing Center (TACC) before the end of the year. That Dell cluster will have 8 of those 10 petaflops delivered by Xeon Phi silicon and, as such, the system will represent the first big test case for Intel’s version of accelerated supercomputing.

It also represents the first credible challenge to NVIDIA on this front since the GPU-maker got into the HPC business in 2006. Whichever company is more successful at delivering HPC on a chip, the big winners will be the users themselves, who will soon have two vendors offering accelerator cards with over a teraflop of double precision performance. At a few thousand dollars per teraflop, supercomputing has never been so accessible.

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!

At Long Last, Supercomputing Helps to Map the Poles

August 22, 2019

“For years,” Paul Morin wrote, “those of us that made maps of the Poles apologized. We apologized for the blank spaces on maps, we apologized for mountains being in the wrong place and out-of-date information.” Read more…

By Oliver Peckham

Xilinx Says Its New FPGA is World’s Largest

August 21, 2019

In this age of exploding “technology disaggregation” – in which the Big Bang emanating from the Intel x86 CPU has produced significant advances in CPU chips and a raft of alternative, accelerated architectures... Read more…

By Doug Black

Supercomputers Generate Universes to Illuminate Galactic Formation

August 20, 2019

With advanced imaging and satellite technologies, it’s easier than ever to see a galaxy – but understanding how they form (a process that can take billions of years) is a different story. Now, a team of researchers f Read more…

By Oliver Peckham

AWS Solution Channel

Efficiency and Cost-Optimization for HPC Workloads – AWS Batch and Amazon EC2 Spot Instances

High Performance Computing on AWS leverages the power of cloud computing and the extreme scale it offers to achieve optimal HPC price/performance. With AWS you can right size your services to meet exactly the capacity requirements you need without having to overprovision or compromise capacity. Read more…

HPE Extreme Performance Solutions

Bring the combined power of HPC and AI to your business transformation

FPGA (Field Programmable Gate Array) acceleration cards are not new, as they’ve been commercially available since 1984. Typically, the emphasis around FPGAs has centered on the fact that they’re programmable accelerators, and that they can truly offer workload specific hardware acceleration solutions without requiring custom silicon. Read more…

IBM Accelerated Insights

Keys to Attracting the Newest HPC Talent – Post-Millennials

[Connect with HPC users and learn new skills in the IBM Spectrum LSF User Community.]

For engineers and scientists growing up in the 80s, the current state of HPC makes perfect sense. Read more…

Singularity Moves Up the Container Value Chain

August 20, 2019

The enterprise version of the Singularity HPC container platform released this week by Sylabs is designed to allow users to create, secure and share the high-end containers in self-hosted production deployments. The e Read more…

By George Leopold

At Long Last, Supercomputing Helps to Map the Poles

August 22, 2019

“For years,” Paul Morin wrote, “those of us that made maps of the Poles apologized. We apologized for the blank spaces on maps, we apologized for mountains being in the wrong place and out-of-date information.” Read more…

By Oliver Peckham

IBM Deepens Plunge into Open Source; OpenPOWER to Join Linux Foundation

August 20, 2019

IBM today announced it was contributing the instruction set (ISA) for its Power microprocessor and the designs for the Open Coherent Accelerator Processor Inter Read more…

By John Russell

Ayar Labs to Demo Photonics Chiplet in FPGA Package at Hot Chips

August 19, 2019

Silicon startup Ayar Labs continues to gain momentum with its DARPA-backed optical chiplet technology that puts advanced electronics and optics on the same chip Read more…

By Tiffany Trader

Scientists to Tap Exascale Computing to Unlock the Mystery of our Accelerating Universe

August 14, 2019

The universe and everything in it roared to life with the Big Bang approximately 13.8 billion years ago. It has continued expanding ever since. While we have a Read more…

By Rob Johnson

AI is the Next Exascale – Rick Stevens on What that Means and Why It’s Important

August 13, 2019

Twelve years ago the Department of Energy (DOE) was just beginning to explore what an exascale computing program might look like and what it might accomplish. Today, DOE is repeating that process for AI, once again starting with science community town halls to gather input and stimulate conversation. The town hall program... Read more…

By Tiffany Trader and John Russell

Cray Wins NNSA-Livermore ‘El Capitan’ Exascale Contract

August 13, 2019

Cray has won the bid to build the first exascale supercomputer for the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laborator Read more…

By Tiffany Trader

AMD Launches Epyc Rome, First 7nm CPU

August 8, 2019

From a gala event at the Palace of Fine Arts in San Francisco yesterday (Aug. 7), AMD launched its second-generation Epyc Rome x86 chips, based on its 7nm proce Read more…

By Tiffany Trader

Lenovo Drives Single-Socket Servers with AMD Epyc Rome CPUs

August 7, 2019

No summer doldrums here. As part of the AMD Epyc Rome launch event in San Francisco today, Lenovo announced two new single-socket servers, the ThinkSystem SR635 Read more…

By Doug Black

High Performance (Potato) Chips

May 5, 2006

In this article, we focus on how Procter & Gamble is using high performance computing to create some common, everyday supermarket products. Tom Lange, a 27-year veteran of the company, tells us how P&G models products, processes and production systems for the betterment of consumer package goods. Read more…

By Michael Feldman

Supercomputer-Powered AI Tackles a Key Fusion Energy Challenge

August 7, 2019

Fusion energy is the Holy Grail of the energy world: low-radioactivity, low-waste, zero-carbon, high-output nuclear power that can run on hydrogen or lithium. T Read more…

By Oliver Peckham

Cray, AMD to Extend DOE’s Exascale Frontier

May 7, 2019

Cray and AMD are coming back to Oak Ridge National Laboratory to partner on the world’s largest and most expensive supercomputer. The Department of Energy’s Read more…

By Tiffany Trader

Graphene Surprises Again, This Time for Quantum Computing

May 8, 2019

Graphene is fascinating stuff with promise for use in a seeming endless number of applications. This month researchers from the University of Vienna and Institu Read more…

By John Russell

AMD Verifies Its Largest 7nm Chip Design in Ten Hours

June 5, 2019

AMD announced last week that its engineers had successfully executed the first physical verification of its largest 7nm chip design – in just ten hours. The AMD Radeon Instinct Vega20 – which boasts 13.2 billion transistors – was tested using a TSMC-certified Calibre nmDRC software platform from Mentor. Read more…

By Oliver Peckham

TSMC and Samsung Moving to 5nm; Whither Moore’s Law?

June 12, 2019

With reports that Taiwan Semiconductor Manufacturing Co. (TMSC) and Samsung are moving quickly to 5nm manufacturing, it’s a good time to again ponder whither goes the venerable Moore’s law. Shrinking feature size has of course been the primary hallmark of achieving Moore’s law... Read more…

By John Russell

Cray Wins NNSA-Livermore ‘El Capitan’ Exascale Contract

August 13, 2019

Cray has won the bid to build the first exascale supercomputer for the National Nuclear Security Administration (NNSA) and Lawrence Livermore National Laborator Read more…

By Tiffany Trader

Deep Learning Competitors Stalk Nvidia

May 14, 2019

There is no shortage of processing architectures emerging to accelerate deep learning workloads, with two more options emerging this week to challenge GPU leader Nvidia. First, Intel researchers claimed a new deep learning record for image classification on the ResNet-50 convolutional neural network. Separately, Israeli AI chip startup Hailo.ai... Read more…

By George Leopold

Leading Solution Providers

ISC 2019 Virtual Booth Video Tour

CRAY
CRAY
DDN
DDN
DELL EMC
DELL EMC
GOOGLE
GOOGLE
ONE STOP SYSTEMS
ONE STOP SYSTEMS
PANASAS
PANASAS
VERNE GLOBAL
VERNE GLOBAL

Nvidia Embraces Arm, Declares Intent to Accelerate All CPU Architectures

June 17, 2019

As the Top500 list was being announced at ISC in Frankfurt today with an upgraded petascale Arm supercomputer in the top third of the list, Nvidia announced its Read more…

By Tiffany Trader

Top500 Purely Petaflops; US Maintains Performance Lead

June 17, 2019

With the kick-off of the International Supercomputing Conference (ISC) in Frankfurt this morning, the 53rd Top500 list made its debut, and this one's for petafl Read more…

By Tiffany Trader

AMD Launches Epyc Rome, First 7nm CPU

August 8, 2019

From a gala event at the Palace of Fine Arts in San Francisco yesterday (Aug. 7), AMD launched its second-generation Epyc Rome x86 chips, based on its 7nm proce Read more…

By Tiffany Trader

A Behind-the-Scenes Look at the Hardware That Powered the Black Hole Image

June 24, 2019

Two months ago, the first-ever image of a black hole took the internet by storm. A team of scientists took years to produce and verify the striking image – an Read more…

By Oliver Peckham

Cray – and the Cray Brand – to Be Positioned at Tip of HPE’s HPC Spear

May 22, 2019

More so than with most acquisitions of this kind, HPE’s purchase of Cray for $1.3 billion, announced last week, seems to have elements of that overused, often Read more…

By Doug Black and Tiffany Trader

Chinese Company Sugon Placed on US ‘Entity List’ After Strong Showing at International Supercomputing Conference

June 26, 2019

After more than a decade of advancing its supercomputing prowess, operating the world’s most powerful supercomputer from June 2013 to June 2018, China is keep Read more…

By Tiffany Trader

Ayar Labs to Demo Photonics Chiplet in FPGA Package at Hot Chips

August 19, 2019

Silicon startup Ayar Labs continues to gain momentum with its DARPA-backed optical chiplet technology that puts advanced electronics and optics on the same chip Read more…

By Tiffany Trader

Qualcomm Invests in RISC-V Startup SiFive

June 7, 2019

Investors are zeroing in on the open standard RISC-V instruction set architecture and the processor intellectual property being developed by a batch of high-flying chip startups. Last fall, Esperanto Technologies announced a $58 million funding round. Read more…

By George Leopold

  • arrow
  • Click Here for More Headlines
  • arrow
Do NOT follow this link or you will be banned from the site!
Share This