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Algorithm Selection Using Behavioral Synthesis

出版	UCLA Computer Science Department, 1995
URL	http://books.google.com.hk/books?id=3UXRGwAACAAJ&hl=&source=gbs_api

註釋Abstract: "HYPER is a third generation high level synthesis system, targeted at numerically intensive applications. By shifting the emphasis from the traditional high level synthesis tasks (such as scheduling, assignment, allocation and module selection) to the domain of optimizing transformations, new avenues for high level synthesis are opened. One of the most exciting among them, which probably has the largest impact on the quality of the design, is to select and optimize the algorithms for a given application. The paper starts with a brief overview of the HYPER system, with special stress on the optimizing transformation methodology. After this, the paper concentrates on the exploration of the algorithmic design space. We show how HYPER can be used to guide and conduct a proper algorithmic selection process and how transformations in HYPER can improve the performance or cost of real life applications with orders of magnitude."