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8 October 1998 Rapid implementation of mathematical and DSP algorithms in configurable computing devices
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Proceedings Volume 3526, Configurable Computing: Technology and Applications; (1998)
Event: Photonics East (ISAM, VVDC, IEMB), 1998, Boston, MA, United States
Many real-time DSP applications can benefit from the use of FPGA or adaptive computing devices because these devices provide very high throughput for a small hardware cost. This efficiency comes with a price: it is very time consuming to actually program complicated algorithms in these devices. We have developed a new method of performing this implementation process, providing for an order of magnitude reduction in design time. Our approach consists of an interactive algorithm development tool closely coupled to a set of FPGA devices. From an algorithm script, the tool derives a hardware design, which includes the data path, host interface, custom sequencer, and address generators. The design is loaded and executed in the FPGA whenever a call for the function is encountered in the algorithm script. Pieces of the algorithm may be ported incrementally; the algorithm will always execute properly, regardless of the state of porting from software to hardware. This approach is optimized to allow mathematicians, generally unskilled in efficient hardware algorithm design, to directly implement algorithms in FPGAs. This enables designers to quickly see the effect of algorithmic changes and approximations on hardware efficiency, reducing the number and time of design iterations. We are currently porting our approach to the publicly available Ptolemy environment, which will facilitate the transfer of this methodology to the adaptive computing community.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul D. Fiore, Cory S. Myers, John M. Smith, and Eric K. Pauer "Rapid implementation of mathematical and DSP algorithms in configurable computing devices", Proc. SPIE 3526, Configurable Computing: Technology and Applications, (8 October 1998);

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