Accelerator Data-Path Synthesis for High-Throughput Signal Processing Applications

ISBN-13: 9780792398202 / Angielski / Twarda / 1996 / 263 str.

Werner Geurts; Francky Catthoor; Serge Vernalde

Opis

Accelerator Data-Path Synthesis for High-Throughput Signal Processing Applications is the first book to show how to use high-level synthesis techniques to cope with the stringent timing requirements of complex high-throughput real-time signal and data processing. The book describes the state-of-the-art in architectural synthesis for complex high-throughput real-time processing. Unlike many other, the Synthesis approach used in this book targets an architecture style or an application domain. This approach is thus heavily application-driven and this is illustrated in the book by several realistic demonstration examples used throughout.
Accelerator Data-Path Synthesis for High-Throughput Signal Processing Applications focuses on domains where application-specific high-speed solutions are attractive such as significant parts of audio, telecom, instrumentation, speech, robotics, medical and automotive processing, image and video processing, TV, multi-media, radar, sonar, etc. Moreover, it addresses mainly the steps above the traditional scheduling and allocation tasks which focus on scalar operations and data.
Accelerator Data-Path Synthesis for High-Throughput Signal Processing Applications is of interest to researchers, senior design engineers and CAD managers both in academia and industry. It provides an excellent overview of what capabilities to expect from future practical design tools and includes an extensive bibliography.

Spis treści

Preface. Glossary. 1. Introduction. 2. Applications and Architecture. 3. The Underlying Synthesis Data Models. 4. Literature Study. 5. The HLDM Script. 6. Operation Clustering. 7. Cluster to ASU Assignment. 8. ASU Synthesis. 9. Demonstrator Designs. 10. Conclusions. A: Timing Analysis on Flow Graphs. B: The Constructive Clustering Algorithms. C: Algorithms of the Assignment Chapter. D: Assignment Benchmarks. E: Proof of Theorem 8.1. F: ASU Synthesis Benchmarks.