Parallel Computing with FPGAs - Concepts and Applications

… , Signal Processing and …, 2009

Algorithms used in signal and image processing applications are computationally intensive. For optimized hardware realization of such algorithms with efficient utilization of available resources, an in-depth knowledge of the targeted field programmable gate array (FPGA) technology is required. This paper presents an overview of the architectures and technologies used in modern FPGAs. A case study of most popular and widely used state-of-the-art commercial FPGA technologies from Xilinx and Altera is also presented. Three-Dimensional (3D)-FPGA architecture is also discussed.

Parallel computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated using parallel computing techniques. Specialized parallel computer architectures are used for accelerating specific tasks. High-Energy Physics Experiments measuring systems often uses FPGAs for fine-grained computation. FPGA combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be reconfigured over the lifetime of the system. FPGAs therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Creating parallel programs implemented in FPGAs is not trivial. This paper presents existing methods and tools for fine-grained computation implemented in FPGA using High Level Programming Languages.

2013

Introduction .................................................................................................... 1 Current Technology .......................................................................................... 2 Case Study ...................................................................................................... 3 Challenges ...................................................................................................... 7 Summary ........................................................................................................ 8

Current high performance computing (HPC) applications are found in many consumer, industrial and research fields. From web searches to auto crash simulations to weather predictions, these applications require large amounts of power by the compute farms and supercomputers required to run them. The demand for more and faster computation continues to increase along with an even sharper increase in the cost of the power required to operate and cool these installations. The ability of standard processor based systems to address these needs has declined in both speed of computation and in power consumption over the past few years. This paper presents a new method of computation based upon programmable logic as represented by Field Programmable Gate Arrays (FPGAs) that addresses these needs in a manner requiring only minimal changes to the current software design environment.

MASAUM Journal of Computing, 2009

Algorithms used in signal processing, image processing and high performance computing applications are computationally intensive. For efficient implementation of such algorithms with efficient utilization of available resources, an indepth knowledge of the targeted field programmable gate array (FPGA) technology is required. This paper presents a state-ofthe-art review of the architectures and technologies used in modern FPGAs. A case study of most popular and widely used state-of-the-art commercial FPGA technologies from Xilinx and Altera is also presented in this paper. Upcoming three-Dimensional (3D)-FPGA architecture is also discussed.

2008

Since their introduction in the 1985, field programmable gate arrays (FPGAs) have become increasingly important to the electronics industry. They have the potential for higher performance and lower power consumption than microprocessors and compared with application specific integrated circuits (ASICs), offer lower non-recurrent engineering (NRE) costs, reduced development time, easier debugging and reduced risk. Since modern FPGAs can meet many of the performance requirements of ASICs, they are being increasingly used in their place. In this paper, some recent developments in FPGA devices, platforms and applications are reviewed, with a focus on high performance applications of this technology.

Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2013, 2013

Parallel computing is emerging as an important area of research in computer architectures and software systems. Many algorithms can be greatly accelerated using parallel computing techniques. Specialized parallel computer architectures are used for accelerating specific tasks. High-Energy Physics Experiments measuring systems often use FPGAs for fine-grained computation. FPGA combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be reconfigured over the lifetime of the system. FPGAs therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Creating parallel programs implemented in FPGAs is not trivial. This paper presents existing methods and tools for fine-grained computation implemented in FPGA using Behavioral Description and High Level Programming Languages.

Microprocessors and Microsystems, 2004

2020

2011

Abstract-Field-Programmable Gate-Arrays (FPGAs) are becoming increasingly popular as computing platforms for high-performance embedded systems. Their flexibility and customization capabilities allow them to achieve orders of magnitude better performance than conventional embedded computing systems. Programming FPGAs is, however, cumbersome and error-prone and as a result their true potential is often only achieved at unreasonably high design efforts.