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Customizable Composition and Parameterization of Hardware Design Transformations
<span title="">2010</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6nxn3oxzcveorfagbcbilem2ay" style="color: black;">2010 13th Euromicro Conference on Digital System Design: Architectures, Methods and Tools</a>
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A promising approach to high-level design is to start initially with an obvious but possibly inefficient design, and apply multiple transformations to meet design goals. Many hardware compilation tools support a fixed recipe of applying design transformations, but designers have few options to adapt the recipe without re-writing the tools themselves. In addition, complex transformations based on linear programming and geometric programming are often not included. This paper proposes a new
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... ch that enables designers to customize the composition and parameterization of different types of design transformations in a unified framework, using a high-level language to control a transformation engine to automate the application of design transformations. Our approach is implemented by a tool based on the Python language and the ROSE compiler framework, which supports both syntax-directed transformations such as loop coalescing, and goal-directed transformations such as geometric programming. We illustrate how customizing the composition and parameterization of design transformations can lead to designs with different trade-offs in performance, resource usage, and energy efficiency. We evaluate our approach on benchmarks including matrix multiplication, Monte Carlo simulation of Asian options, edge detection, FIR filtering, and motion estimation.
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