Applications of adaptive computing systems for signal processing challenges

Adaptive computing systems use FPGAs for custom hardware acceleration in high performance and real-time applications. Unlike single purpose dedicated hardware approaches, the reusable nature of the technology introduces system design tradeoffs that must balance processing density, memory, and I/O bandwidth, not to mention more subtle issues such as ease of programming, debugging, and physical integration into real-world systems. This paper describes results from the DARPA-funded SLAAC project, which developed three generations of adaptive computing systems for a diverse set of challenging signal processing applications.