Reconfigurable Computing Research Pushes Forward

By Nicole Hemsoth

November 20, 2009

Despite all the all the recent hoopla about GPGPUs and eight-core CPUs, proponents of reconfigurable computing continue to sing the praises of FPGA-based HPC. The main advantage of reconfigurable computing, or RC for short, is that programmers are able to change the circuitry of the chip on the fly. Thus, in theory, the hardware can be matched to the software, rather than the other way around. While there are a handful of commercial offerings from companies such as Convey Computer, XtremeData, GiDel, Mitrionics, and Impulse Accelerated Technologies, RC is still an area of active research.

In the U.S., the NSF Center for High-Performance Reconfigurable Computing (CHREC, pronounced “shreck”), acts as the research hub for RC, bringing together more than 30 organizations in this field. CHREC is run by Dr. Alan George, who gave an address at the SC09 Workshop on High-Performance Reconfigurable Computing Technology and Applications (HPRCTA’09) on November 15. We got the opportunity to ask Dr. George about the work going on at the Center and what he thinks RC technology can offer to high performance computing users.

HPCwire: FPGA-based reconfigurable computing has captured some loyal followers in the HPC community. What are the advantages of FPGAs for high-performance computing compared to fixed-logic architectures such as CPUs, GPUs, the Cell processor?

Alan George: HPC is approaching a crossroads in terms of enabling technologies and their inherent strengths and weaknesses. Goals and challenges in three principal areas are vitally important yet increasingly in conflict: performance, productivity, and sustainability. For example, HPC machines lauded in the upper tier of the TOP500 list as most powerful in the world are remarkably high in performance yet also remarkably massive in size, energy, heat, and cost, all featuring programmable, fixed-logic devices, for example, CPU, GPU, Cell. Meanwhile, throughout society, energy cost, source, and availability are a growing concern. As life-cycle costs of energy and cooling rise to approach and exceed that of software and hardware in total cost of ownership, these technologies may become unsustainable.

By contrast, numerous research studies show that computing with reconfigurable-logic devices — FPGAs, et al. — is fundamentally superior in terms of speed and energy, due to the many advantages of adaptive, customizable hardware parallelism. Common sense confirms this comparison. Programmable fixed-logic devices no matter their form feature a “one size fits all” or “Jack of all trades” philosophy, with a predefined structure of parallelism, yet attempting to support all applications or some major subset. In contrast, the structure of parallelism in reconfigurable-logic devices can be customized, that is, reconfigured, for each application or task on the fly, being versatile yet optimized specifically for each problem at hand. With this perspective, fixed-logic computing and accelerators are following a more evolutionary path, whereas RC is relatively new and revolutionary.

It should be noted that RC, as a new paradigm of computing, is broader than FPGA acceleration for HPC. FPGA devices are the leading commercial technology available today that is capable of RC, albeit not originally designed for RC, and thus FPGAs are the focal point for virtually all experimental research and commercial deployments, with a growing list of success stories. However, looking ahead more broadly, reconfigurable logic may be featured in future devices with a variety of structures, granularities, functionalities, etc., perhaps very similar to today’s FPGAs or perhaps quite different.

HPCwire: What role, or roles, do you see for RC technology in high performance computing and high performance embedded computing? Will RC be a niche solution in specific application areas or do you see this technology being used in general-purpose platforms that will be widely deployed?

George: Naturally, as a relatively new paradigm of computing, RC has started with emphasis in a few targeted areas, for example, aerospace and bioinformatics, where missions and users require dramatic improvement only possible by a revolutionary approach. As principal challenges — performance, productivity, and sustainability — become more pronounced, and as R&D in RC progresses, we believe that the RC paradigm will mature and expand in its role and influence to eventually become dominant in a broad range of applications, from satellites to servers to supercomputers. We are already witnessing this trend in several sectors of high-performance embedded computing. For example, in advanced computing on space missions, high performance and versatility are critical with limited energy, size, and weight. NASA, DOD, and other space-related agencies worldwide are increasingly featuring RC technologies in their platforms, as is the aerospace community in general. The driving issues in this community — again performance, productivity, and especially sustainability — are becoming increasingly important in HPC.

HPCwire: In the past couple of years, non-RC accelerators like the Cell processor and now, especially, general-purpose GPUs have been making big news in the HPC world, with major deployments planned. What has held back reconfigurable computing technology in this application space?

George: There are several reasons why Cell and GPU accelerators are more popular in HPC at present. Perhaps most obviously, they are viewed as inexpensive, due to leveraging of the gaming market. Vendors have invested heavily, both marketing and R&D, to broaden the appeal of these devices for the HPC community. Moreover, in terms of fundamental computing principles, they are an evolutionary development in device architecture, and as such represent less risk. However, we believe that inherent weaknesses of any fixed-logic device technology … in terms of broad applicability at speed and energy efficiency, will eventually become limiting factors.

By contrast, reconfigurable computing is a relatively new and immature paradigm of computing. Like any new paradigm, there are R&D challenges that must be solved before it can become more broadly applicable and eventually ubiquitous. With fixed-logic computing, the user and application have no control over underlying hardware parallelism; they simply attempt to exploit as much as the manufacturer has deemed to provide. With reconfigurable-logic computing, the user and application define the hardware parallelism, featuring wide and deep parallelism as appropriate, with selectable precision, optimized data paths, etc., up to the limits of total device capacity. This tremendous advantage in parallel computing potency comes with the challenge of complexity. Thus, as is natural for any new paradigm and set of technologies, design productivity is an important challenge at present for RC in general and FPGA devices in particular, so that HPC users, and others, can take full advantage without having to be trained as electrical engineers.

It should be noted that this life-cycle is commonplace in the history of technology. An established technology is dominant for many years; it experiences growth over a long period of time from evolutionary advances, and one day it is partially or wholly supplanted by a new, revolutionary technology, but only after that new technology has navigated a long and winding road of research and development. Productivity is often a key challenge for a new IT technology, learning how to effectively harness and exploit the inherent advantages of the new approach.

HPCwire: What do you see on the horizon that could propel reconfigurable computing into a more mainstream role?

George: There are two major factors on the horizon that we believe will dramatically change the landscape. One factor is the trend for performance, productivity, and sustainability borne by growing concerns with conventional technologies about speed versus energy consumption, which increasingly favors RC. The conventional model of computing with fixed-logic multicore devices is limiting in terms of performance per unit of energy as compared to reconfigurable-logic devices. However, RC is viewed by many as lagging in effective concepts and tools for application development by domain scientists and other users to harness this potency without special skills. Thus, the second factor is taming this new paradigm of computing and innovations in its technologies, so that it is amenable to a broader range of users. In this regard, many vendors and research groups are conducting R&D and developing new concepts, tools, and products to address this challenge. In the future, RC will become more important for a growing set of missions, applications, and users and, concomitantly, it will become more amenable to them, so that productivity is maximized alongside performance and sustainability.

HPCwire: The new Novo-G reconfigurable computing system at the NSF Center for High-Performance Reconfigurable Computing (CHREC) has been up and running for just a few months. Can you tell us about the machine and what you hope to accomplish with it?

George: Novo-G became operational in July of this year and is believed to be the most powerful RC machine ever fielded for research. Its size, cooling and power consumption are modest by HPC standards, but they hide its computational superiority. For example, in our first application experiment working with domain scientists in computational biology, performance was sustained with 96 FPGAs that matched that of the largest machines on the NSF TeraGrid, yet provided by a machine that is hundreds of times lower in cost, power, cooling, size, etc.

Housed in three racks, Novo-G consists of 24 standard Linux servers, plus a head node, connected by DDR InfiniBand and GigE. Each server features a tightly-coupled set of four FPGA accelerators on a ProcStar-III PCIe board from GiDEL supported by a conventional multicore CPU, motherboard, disk, etc. Each FPGA is a Stratix-III E260 device from Altera with 254K logic elements, 768 18×18 multipliers, and more than 4GB of DDR2 memory directly attached via three banks. Altogether, Novo-G features 96 of these FPGAs, with an upgrade underway that by January will double its RC capacity to 192 FPGAs via two coupled RC boards per server.

The purpose of Novo-G is to support a variety of research projects in CHREC related to RC performance, productivity and sustainability. Founded in 2007, CHREC is a national research center under the auspices of the I/UCRC program of the National Science Foundation and consists of more than 30 academic, industry and government partners working collaboratively on research in this field. In addition, several new collaborations have been inspired by Novo-G, with other research groups, for example, Boston University and the Air Force Research Laboratory, as well as tools vendors such as Impulse Accelerated Technologies and Mitrionics.

HPCwire: Can you talk about a few of the projects at CHREC that look especially promising?

George: On-going research projects at the four university sites of CHREC — the University of Florida, Brigham Young University led by Dr. Brent Nelson, George Washington University led by Dr. Tarek El-Ghazawi, and Virginia Tech led by Dr. Peter Athanas — fall into four categories: productivity, architecture, partial reconfiguration, and fault tolerance. In the area of productivity, several projects are underway, crafting novel concepts for design of RC applications and systems, including new methods and tools for design formulation and prediction, hardware virtualization, module and core reuse, design verification and optimization, and programming with high-level languages. With respect to architecture, researchers are working to characterize and optimize new and emerging devices — both fixed and reconfigurable logic — and systems, as well as methods to promote autonomous hardware reconfiguration. Both of these project areas of productivity and architecture relate well to HPC.

Meanwhile, one of the unique features of some RC devices is their ability to reconfigure portions of the hardware of the chip while other portions remain unchanged and thus operational, and this powerful feature involves many research and design challenges being studied and addressed by several teams. Last but not least, as process densities increase and become more susceptible to faults, environments become harsher, and resources become more prone to soft or hard errors, research challenges arise in fault tolerance. In this area, CHREC researchers are developing device- and system-level RC concepts and architectures to support scenarios that require high performance, versatility, and reliability with low power, cooling, and size, be it for outer space or the HPC computer room.

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!

Democratization of HPC Part 3: Ninth Graders Tap HPC in the Cloud to Design Flying Boats

October 18, 2018

This is the third in a series of articles demonstrating the growing acceptance of high-performance computing (HPC) in new user communities and application areas. In this article we present UberCloud use case #208 on how Read more…

By Wolfgang Gentzsch and Håkon Bull Hove

Penguin Computing Launches Consultancy for Piecing AI Strategies Together

October 18, 2018

AI stands before the HPC industry as a beacon of great expectations, yet market research repeatedly shows that AI adoption is commonly stuck in the talking phase, on the near side of a difficult chasm to cross. In respon Read more…

By Tiffany Trader

When Water Quality—Not Quantity—Hinders HPC Cooling

October 18, 2018

Attention has been paid to the sheer quantity of water consumed by supercomputers’ cooling towers – and rightly so, as they can require thousands of gallons per minute to cool. But in the background, another factor can emerge, bottlenecking efficiency and raising costs: water quality. Read more…

By Oliver Peckham

HPE Extreme Performance Solutions

One Small Step Toward Mars: One Giant Leap for Supercomputing

Since the days of the Space Race between the U.S. and the former Soviet Union, we have continually sought ways to perform experiments in space. Read more…

IBM Accelerated Insights

Paper Offers ‘Proof’ of Quantum Advantage on Some Problems

October 18, 2018

Is quantum computing worth all the effort being poured into it or should we just wait for classical computing to catch up? An IBM blog today posed those questions and, you won’t be surprised, offers a firm “it’s wo Read more…

By John Russell

Penguin Computing Launches Consultancy for Piecing AI Strategies Together

October 18, 2018

AI stands before the HPC industry as a beacon of great expectations, yet market research repeatedly shows that AI adoption is commonly stuck in the talking phas Read more…

By Tiffany Trader

When Water Quality—Not Quantity—Hinders HPC Cooling

October 18, 2018

Attention has been paid to the sheer quantity of water consumed by supercomputers’ cooling towers – and rightly so, as they can require thousands of gallons per minute to cool. But in the background, another factor can emerge, bottlenecking efficiency and raising costs: water quality. Read more…

By Oliver Peckham

Paper Offers ‘Proof’ of Quantum Advantage on Some Problems

October 18, 2018

Is quantum computing worth all the effort being poured into it or should we just wait for classical computing to catch up? An IBM blog today posed those questio Read more…

By John Russell

Dell EMC to Supply U Michigan’s Great Lakes Cluster

October 16, 2018

The University of Michigan (U-M) today announced Dell EMC is the lead vendor for U-M’s $4.8 million Great Lakes HPC cluster scheduled for deployment in first Read more…

By John Russell

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

Nvidia Platform Pushes GPUs into Machine Learning, High Performance Data Analytics

October 10, 2018

GPU leader Nvidia, generally associated with deep learning, autonomous vehicles and other higher-end enterprise and scientific workloads (and gaming, of course) Read more…

By Doug Black

Federal Investment in Exascale – What It Really Means

October 10, 2018

Earlier this month, the EuroHPC JU (Joint Undertaking) reached critical mass, and it seems all EU and affiliated member states, bar the UK (unsurprisingly), have or will sign on. The EuroHPC JU was born from a recognition that individual EU member states, and the EU as a whole, were significantly underinvesting in HPC compared to the US, China and Japan, who all have their own exascale investment and delivery strategies (NSCI, 13th 5 Year Plan, Post-K, etc). Read more…

By Dairsie Latimer

NERSC-9 Clues Found in NERSC 2017 Annual Report

October 8, 2018

If you’re eager to find out who’ll supply NERSC’s next-gen supercomputer, codenamed NERSC-9, here’s a project update to tide you over until the winning bid and system details are revealed. The upcoming system is referenced several times in the recently published 2017 NERSC annual report. Read more…

By Tiffany Trader

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

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

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

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

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

Leading Solution Providers

HPC on Wall Street 2018 Booth Video Tours Playlist

Arista

Dell EMC

IBM

Intel

RStor

VMWare

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

HPE No. 1, IBM Surges, in ‘Bucking Bronco’ High Performance Server Market

September 27, 2018

Riding healthy U.S. and global economies, strong demand for AI-capable hardware and other tailwind trends, the high performance computing server market jumped 28 percent in the second quarter 2018 to $3.7 billion, up from $2.9 billion for the same period last year, according to industry analyst firm Hyperion Research. Read more…

By Doug Black

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

Germany Celebrates Launch of Two Fastest Supercomputers

September 26, 2018

The new high-performance computer SuperMUC-NG at the Leibniz Supercomputing Center (LRZ) in Garching is the fastest computer in Germany and one of the fastest i 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

Aerodynamic Simulation Reveals Best Position in a Peloton of Cyclists

July 5, 2018

Eindhoven University of Technology (TU/e) and KU Leuven research group conducts the largest numerical simulation ever done in the sport industry and cycling discipline. The goal was to understand the aerodynamic interactions in the peloton, i.e., the main pack of cyclists in a race. Read more…

Houston to Field Massive, ‘Geophysically Configured’ Cloud Supercomputer

October 11, 2018

Based on some news stories out today, one might get the impression that the next system to crack number one on the Top500 would be an industrial oil and gas mon Read more…

By Tiffany Trader

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