HPCwire: Reconfigurable Computing Research Pushes Forward

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November 20, 2009

Reconfigurable Computing Research Pushes Forward

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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.

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