Due to its potential to greatly accelerate a wide variety of applications, reconfigurable computing has become a subject of a great deal of research. Its key feature is the ability to perform computations in hardware to increase performance, while retaining much of the flexibility of a software solution. In this survey, we explore the hardware aspects of reconfigurable computing machines, from single chip architectures to multi-chip systems, including internal structures and external coupling. We also focus on the software that targets these machines, such as compilation tools that map high-level algorithms directly to the reconfigurable substrate. Finally, we consider the issues involved in run-time reconfigurable systems, which reuse the configurable hardware during program execution.

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Reconfigurable computing: a survey of systems and software

The main characteristic of Reconfigurable Computing is the presence of hardware that can be reconfigured to implement specific functionality more suitable for specially tailored hardware than on a simple uniprocessor. Reconfigurable computing systems join microprocessors and programmable hardware in order to take advantage of the combined strengths of hardware and software and have been used in applications ranging from embedded systems to high performance computing. Many of the fundamental theories have been identified and used by the Hardware/Software Co-Design research field. Although the same background ideas are shared in both areas, they have different goals and use different approaches.This book is intended as an introduction to the entire range of issues important to reconfigurable computing, using FPGAs as the context, or "computing vehicles" to implement this powerful technology. It will take a reader with a background in the basics of digital design and software programming and provide them with the knowledge needed to be an effective designer or researcher in this rapidly evolving field.

· Treatment of FPGAs as computing vehicles rather than glue-logic or ASIC substitutes
· Views of FPGA programming beyond Verilog/VHDL
· Broad set of case studies demonstrating how to use FPGAs in novel and efficient ways

Reconfigurable Computing: The Theory and Practice of FPGA-Based Computation

Various projects and products have been built using off-the-shelf field-programmable gate arrays (FPGAs) as computation accelerators for specific tasks. Such systems typically connect one or more FPGAs to the host computer via an I/O bus. Some have shown remarkable speedups, albeit limited to specific application domains. Many factors limit the general usefulness of such systems. Long reconfiguration times prevent the acceleration of applications that spread their time over many different tasks. Low-bandwidth paths for data transfer limit the usefulness of such systems to tasks that have a high computation-to-memory-bandwidth ratio. In addition, standard FPGA tools require hardware design expertise which is beyond the knowledge of most programmers. To help investigate the viability of connected FPGA systems, the authors designed their own architecture called Garp and experimented with running applications on it. They are also investigating whether Garp's design enables automatic, fast, effective compilation across a broad range of applications. They present their results in this article.

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The Garp architecture and C compiler

Future computing workloads will emphasize an architecture's ability to perform relatively simple calculations on massive quantities of mixed-width data. This paper describes a novel reconfigurable fabric architecture, PipeRench, optimized to accelerate these types of computations. PipeRench enables fast, robust compilers, supports forward compatibility, and virtualizes configurations, thus removing the fixed size constraint present in other fabrics. For the first time we explore how the bit-width of processing elements affects performance and show how the PipeRench architecture has been optimized to balance the needs of the compiler against the realities of silicon. Finally, we demonstrate extreme performance speedup on certain computing kernels (up to 190x versus a modern RISC processor), and analyze how this acceleration translates to application speedup.

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PipeRench: a co/processor for streaming multimedia acceleration

Reconfigurable computing is becoming increasingly attractive for many applications. This survey covers two aspects of reconfigurable computing: architectures and design methods. The paper includes recent advances in reconfigurable architectures, such as the Alters Stratix II and Xilinx Virtex 4 FPGA devices. The authors identify major trends in general-purpose and special-purpose design methods. It is shown that reconfigurable computing designs are capable of achieving up to 500 times speedup and 70% energy savings over microprocessor implementations for specific applications.

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Reconfigurable computing: architectures and design methods

The National Adaptive Processing Architecture (NAPA) is a major effort to integrate the resources needed to develop teraops class computing systems based on the principles of adaptive computing. The primary goals for this effort include: (1) the development of an example NAPA component which achieves an order of magnitude cost/performance improvement compared to traditional FPGA based systems, (2) the creation of a rich but effective application development environment for NAPA systems based on the ideas of compile time functional partitioning and (3) significantly improve the base infrastructure for effective research in reconfigurable computing. This paper emphasizes the technical aspects of the architecture to achieve the first goal while illustrating key architectural concepts motivated by the second and third goals.

T. Garverick

Papers

The NAPA adaptive processing architecture