ORNL’s Future Technologies Group Tackles Memory and More

By John Russell

October 13, 2016

“Imagine if you’ve got a Titan-size computer (27 PFlops) and it has main memory that’s partially non-volatile memory and you could just leave your data in that memory between executions then just come back and start computing on that data as it sits in memory,” says Jeffrey Vetter, group leader of the Future Technologies Group at Oak Ridge National Labs.

“There are challenges with that in terms of how the systems are allocated, how the systems are organized and scheduled, and so those are the kind of things we’re trying to see before all the users and other folks see them and trying to come up with some solutions.” That in brief is the mission FTG is charged with by its main sponsors, the Department of Energy (DOE) and NSF, as well as collaboration with industry.

Jeffrey Vetter, ORNL Future Technologies Group
Jeffrey Vetter, ORNL Future Technologies Group

Formed roughly 13 years ago as a team focused on emerging technologies for HPC and led by Vetter who joined ORNL from Lawrence Livermore National Lab, FTG results have proven influential. Perhaps most notable is work on GPU architectures in the 2008 timeframe.

“We took those results and shared them with our sponsors (DOE and NSF) and they impacted the timelines and architectures for the systems we have now. We managed to become an XSEDE site running the largest GPU system in NSF and at Oak Ridge our results were very instrumental in Titan becoming a GPU-based system,” says Vetter.

“The idea [behind FTG] is that you’ve got these technologies and there’s a lot of assessment that has to happen in terms of mission applications. It’s not just this new technology is great for one application; it is how do we deploy it widely to our users. How do we make the programming model productive and the tool ecosystem productive around these [architectures] and try to find example of applications that perform well on these architectures.”

GPU-based systems, he notes, have become very effective for molecular dynamics, quantum chemistry dynamics, CFD, and neutron transport. FTG work has played a role helping to bring that about. The constant thread running through FTG projects is work to develop new insight and computational tools that allow emerging technologies to be put to useful work on science or DOE mission applications. The group’s work product, says Vetter, typically includes papers, software, and scientific advance – the perfect “trifecta” when everything works.

The influential GPU work is a good example. “We have several papers on our GPU work with applications,” says Vetter. “Two of the primary efforts [in the 2008 timeframe influencing system direction and timing] were:”

  • DCA++: a quantum materials application: Alvarez, M. Summers et al., “New algorithm to enable 400+ TFlop/s sustained performance in simulations of disorder effects in high-T c superconductors (Gordon Bell Prize Winner),” Proc. 2008 ACM/IEEE conference on Supercomputing Conference on High Performance Networking and Computing, 2008; J.S. Meredith, G. Alvarez et al., “Accuracy and performance of graphics processors: A Quantum Monte Carlo application case study,” Parallel Comput., 35(3):151-63, 2009, 10.1016/j.parco.2008.12.004.
  • S3D: a combustion application: Spafford, J. Meredith et al., “Accelerating S3D: A GPGPU Case Study,” in Seventh International Workshop on Algorithms, Models, and Tools for Parallel Computing on Heterogeneous Platforms (HeteroPar 2009). Delft, The Netherlands, 2009

screen-shot-2016-10-13-at-11-07-35-amIn recent years FTG has started looking a memory architecture. Vetter notes memory cuts across all areas of computing – scientific HPC, traditional enterprise, and mobile. “The Department of Energy funded a project with my group plus some external collaborators at Michigan and Penn state and HP to look at how non-volatile memory could offset this trend of shrinking node memory capacity,” he says.

One challenge, of course, is that DRAMs don’t scale as they once did. They are also power hungry compared to other technologies. Vetter’s group is tracking various memory technologies (FLASH in terms of NAND and 3D NAND as well as resistive memristors, resistive RAM, phase change, etc.)

“We say, OK this technology looks like it has a nice trajectory and [we] go back to determine how can our applications make use of it and how can it be architected into a system so that users can make use of it. We’ve started looking very carefully at programming models and user scenarios of how non volatile memory could be integrated into a systems and how it would be used and those two are interrelated right,” he says.

“Right now people put an SSD in a system and you’ve got non-volatile memory in a system but it’s usually hidden behind a POSIX IO or some type of IO interface that makes it a little less interesting and lower performing. If you think about moving that memory higher and moving it closer and closer to the processor,” says Vetter, the benefits could be substantial, such as in the Titan scenario mentioned earlier.

Seyong Lee, ORNL Future Technologies Group
Seyong Lee, ORNL Future Technologies Group

Exposing these new memory hierarchies directly to applications to take advantage of them is a hot topic these days. Along those lines Vetter and his FTG colleagues Joel Denny and Seyong Lee recently published a new paper – NVL-C: Static Analysis Techniques for Efficient, Correct Programming of Non-Volatile Main Memory Systems[i].

Here are two brief excerpts:

  • “As the NVM technologies continue to improve, they become more credible for integration at other levels of the storage and memory hierarchy, such as either a peer or replacement for DRAM. In this case, scientists will be forced to redesign the architecture of the memory hierarchy, the software stack, and, possibly, their applications to gain the full advantages of these new capabilities. Simply put, we posit that these new memory systems will need to be exposed to applications as first-class language constructs with full support from the software development tools (e.g., compilers, libraries) to employ them efficiently, correctly, and portably.”
  • “[W]e present NVL-C: a novel programming system that facilitates the efficient and correct programming of NVM main memory systems. The NVL-C programming abstraction extends C with a small set of intuitive language features that target NVM main memory, and can be combined directly with traditional C memory model features for DRAM. We have designed these new features to enable compiler analyses and run-time checks that can improve performance and guard against a number of subtle programming errors, which, when left uncorrected, can corrupt NVM-stored data.”

screen-shot-2016-10-13-at-11-08-24-amFTG’s early focus was on heterogeneous computing “because we thought there were going to be several options, things like multicore, early GPUs, and even FPGAs,” says Vetter wryly at what hardly sounds leading edge today. “So we started looking at those in terms of programming models and expected performance and shortcoming and benefits of the architectures.” Among projects showcased today on the FTG website are – Kneeland Project (heterogeneous/GPU computing), Oxbow Program (tools for characterizing of parallel applications), OpenARC (open-sourced, OpenACC compiler).

Currently there are 11 members of FTG comprised of a mix of post-docs and staff scientists etc. The number fluctuates, says Vetter: “Some stay for a few years and some stay for a decade or more. One of the things I’ll say that I really like about the lab is that it’s open. We can collaborate and publish and our software is open so we can work with pretty much everyone we want to work with. The goal is to advance science not just develop another software tool or just write another paper but actually have impact on our applications teams and the DOE mission.”

Vetter notes FTG mission continues to expand, not least because its primary sponsor, DOE, is also changing its perspective.

“DOE right now has started to seriously think what happens after the exascale and what types of computing not only can we use but also how can we even contribute to next generation technologies,” he says. DOE, he notes, has a great deal of materials science research going on – “low level chemistry and other things going on in their nanoscale materials centers” – which may be needed in the post Moore, post exascale era and DOE, he says, is working to become a contributor to solving these problems, not just a downstream consumer.”

As you would expect, the national labs communicate regularly and collaborate. Vetter, for example, has worked with Adolfy Hoise of Pacific Northwest National Laboratory (PNNL) and director of its Center for Advanced Technology Evaluation, and others putting on workshop to “discuss performance analysis and modeling and simulating on these types of architectures.” Vetter was also last year’s Technical Program Chair for SC15.

The FTG has come a long way since its founding. “When I first joined Oak Ridge I think we had a 1Tflops Cray on the floor and now we have a 27Pflops Titan, and hopefully a 200Pflops machine soon. I think this is a great time to be in computer science because we’re entering this space where it’s not a given that we’ll just get a next generation x86. We have to start thinking very carefully about these choices and that puts us in a great mode for science and engineering. FPGAs, ASICS, specialized processors are going top help round out the CMOS but what will be next?”

[i] HPDC ’16 Proceedings of the 25th ACM International Symposium on High-Performance Parallel and Distributed Computing; Pages 125-136; ISBN: 978-1-4503-4314-5 doi>10.1145/2907294.2907303

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!

Russian and American Scientists Achieve 50% Increase in Data Transmission Speed

September 20, 2018

As high-performance computing becomes increasingly data-intensive and the demand for shorter turnaround times grows, data transfer speed becomes an ever more important bottleneck. Now, in an article published in IEEE Tra Read more…

By Oliver Peckham

IBM to Brand Rescale’s HPC-in-Cloud Platform

September 20, 2018

HPC (or big compute)-in-the-cloud platform provider Rescale has formalized the work it’s been doing in partnership with public cloud vendors by announcing its Powered by Rescale program – with IBM as its first named Read more…

By Doug Black

Democratization of HPC Part 1: Simulation Sheds Light on Building Dispute

September 20, 2018

This is the first of three articles demonstrating the growing acceptance of High Performance Computing especially in new user communities and application areas. Major reasons for this trend are the ongoing improvements i Read more…

By Wolfgang Gentzsch

HPE Extreme Performance Solutions

Introducing the First Integrated System Management Software for HPC Clusters from HPE

How do you manage your complex, growing cluster environments? Answer that big challenge with the new HPC cluster management solution: HPE Performance Cluster Manager. Read more…

IBM Accelerated Insights

Clouds Over the Ocean – a Healthcare Perspective

Advances in precision medicine, genomics, and imaging; the widespread adoption of electronic health records; and the proliferation of medical Internet of Things (IoT) and mobile devices are resulting in an explosion of structured and unstructured healthcare-related data. Read more…

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Gordon Bell Prize used Summit in their work. That’s impres Read more…

By John Russell

Summit Supercomputer is Already Making its Mark on Science

September 20, 2018

Summit, now the fastest supercomputer in the world, is quickly making its mark in science – five of the six finalists just announced for the prestigious 2018 Read more…

By John Russell

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

Nvidia Accelerates AI Inference in the Datacenter with T4 GPU

September 14, 2018

Nvidia is upping its game for AI inference in the datacenter with a new platform consisting of an inference accelerator chip--the new Turing-based Tesla T4 GPU- Read more…

By George Leopold

DeepSense Combines HPC and AI to Bolster Canada’s Ocean Economy

September 13, 2018

We often hear scientists say that we know less than 10 percent of the life of the oceans. This week, IBM and a group of Canadian industry and government partner Read more…

By Tiffany Trader

Rigetti (and Others) Pursuit of Quantum Advantage

September 11, 2018

Remember ‘quantum supremacy’, the much-touted but little-loved idea that the age of quantum computing would be signaled when quantum computers could tackle Read more…

By John Russell

How FPGAs Accelerate Financial Services Workloads

September 11, 2018

While FSI companies are unlikely, for competitive reasons, to disclose their FPGA strategies, James Reinders offers insights into the case for FPGAs as accelerators for FSI by discussing performance, power, size, latency, jitter and inline processing. Read more…

By James Reinders

Update from Gregory Kurtzer on Singularity’s Push into FS and the Enterprise

September 11, 2018

Container technology is hardly new but it has undergone rapid evolution in the HPC space in recent years to accommodate traditional science workloads and HPC systems requirements. While Docker containers continue to dominate in the enterprise, other variants are becoming important and one alternative with distinctly HPC roots – Singularity – is making an enterprise push targeting advanced scale workload inclusive of HPC. Read more…

By John Russell

At HPC on Wall Street: AI-as-a-Service Accelerates AI Journeys

September 10, 2018

AIaaS – artificial intelligence-as-a-service – is the technology discipline that eases enterprise entry into the mysteries of the AI journey while lowering Read more…

By Doug Black

TACC Wins Next NSF-funded Major Supercomputer

July 30, 2018

The Texas Advanced Computing Center (TACC) has won the next NSF-funded big supercomputer beating out rivals including the National Center for Supercomputing Ap Read more…

By John Russell

IBM at Hot Chips: What’s Next for Power

August 23, 2018

With processor, memory and networking technologies all racing to fill in for an ailing Moore’s law, the era of the heterogeneous datacenter is well underway, Read more…

By Tiffany Trader

Requiem for a Phi: Knights Landing Discontinued

July 25, 2018

On Monday, Intel made public its end of life strategy for the Knights Landing "KNL" Phi product set. The announcement makes official what has already been wide Read more…

By Tiffany Trader

CERN Project Sees Orders-of-Magnitude Speedup with AI Approach

August 14, 2018

An award-winning effort at CERN has demonstrated potential to significantly change how the physics based modeling and simulation communities view machine learni Read more…

By Rob Farber

ORNL Summit Supercomputer Is Officially Here

June 8, 2018

Oak Ridge National Laboratory (ORNL) together with IBM and Nvidia celebrated the official unveiling of the Department of Energy (DOE) Summit supercomputer toda Read more…

By Tiffany Trader

New Deep Learning Algorithm Solves Rubik’s Cube

July 25, 2018

Solving (and attempting to solve) Rubik’s Cube has delighted millions of puzzle lovers since 1974 when the cube was invented by Hungarian sculptor and archite Read more…

By John Russell

AMD’s EPYC Road to Redemption in Six Slides

June 21, 2018

A year ago AMD returned to the server market with its EPYC processor line. The earth didn’t tremble but folks took notice. People remember the Opteron fondly Read more…

By John Russell

House Passes $1.275B National Quantum Initiative

September 17, 2018

Last Thursday the U.S. House of Representatives passed the National Quantum Initiative Act (NQIA) intended to accelerate quantum computing research and developm Read more…

By John Russell

Leading Solution Providers

SC17 Booth Video Tours Playlist

Altair @ SC17


AMD @ SC17


ASRock Rack @ SC17

ASRock Rack



DDN Storage @ SC17

DDN Storage

Huawei @ SC17


IBM @ SC17


IBM Power Systems @ SC17

IBM Power Systems

Intel @ SC17


Lenovo @ SC17


Mellanox Technologies @ SC17

Mellanox Technologies

Microsoft @ SC17


Penguin Computing @ SC17

Penguin Computing

Pure Storage @ SC17

Pure Storage

Supericro @ SC17


Tyan @ SC17


Univa @ SC17


Sandia to Take Delivery of World’s Largest Arm System

June 18, 2018

While the enterprise remains circumspect on prospects for Arm servers in the datacenter, the leadership HPC community is taking a bolder, brighter view of the x86 server CPU alternative. Amongst current and planned Arm HPC installations – i.e., the innovative Mont-Blanc project, led by Bull/Atos, the 'Isambard’ Cray XC50 going into the University of Bristol, and commitments from both Japan and France among others -- HPE is announcing that it will be supply the United States National Nuclear Security Administration (NNSA) with a 2.3 petaflops peak Arm-based system, named Astra. Read more…

By Tiffany Trader

MLPerf – Will New Machine Learning Benchmark Help Propel AI Forward?

May 2, 2018

Let the AI benchmarking wars begin. Today, a diverse group from academia and industry – Google, Baidu, Intel, AMD, Harvard, and Stanford among them – releas Read more…

By John Russell

D-Wave Breaks New Ground in Quantum Simulation

July 16, 2018

Last Friday D-Wave scientists and colleagues published work in Science which they say represents the first fulfillment of Richard Feynman’s 1982 notion that Read more…

By John Russell

Intel Pledges First Commercial Nervana Product ‘Spring Crest’ in 2019

May 24, 2018

At its AI developer conference in San Francisco yesterday, Intel embraced a holistic approach to AI and showed off a broad AI portfolio that includes Xeon processors, Movidius technologies, FPGAs and Intel’s Nervana Neural Network Processors (NNPs), based on the technology it acquired in 2016. Read more…

By Tiffany Trader

TACC’s ‘Frontera’ Supercomputer Expands Horizon for Extreme-Scale Science

August 29, 2018

The National Science Foundation and the Texas Advanced Computing Center announced today that a new system, called Frontera, will overtake Stampede 2 as the fast Read more…

By Tiffany Trader

Intel Announces Cooper Lake, Advances AI Strategy

August 9, 2018

Intel's chief datacenter exec Navin Shenoy kicked off the company's Data-Centric Innovation Summit Wednesday, the day-long program devoted to Intel's datacenter Read more…

By Tiffany Trader

GPUs Power Five of World’s Top Seven Supercomputers

June 25, 2018

The top 10 echelon of the newly minted Top500 list boasts three powerful new systems with one common engine: the Nvidia Volta V100 general-purpose graphics proc Read more…

By Tiffany Trader

The Machine Learning Hype Cycle and HPC

June 14, 2018

Like many other HPC professionals I’m following the hype cycle around machine learning/deep learning with interest. I subscribe to the view that we’re probably approaching the ‘peak of inflated expectation’ but not quite yet starting the descent into the ‘trough of disillusionment. This still raises the probability that... Read more…

By Dairsie Latimer

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