Abstract
Coarse-Grained Reconfigurable Array (CGRA) architectures accelerate the same inner loops that benefit from the high ILP support in VLIW architectures. Unlike VLIWs, CGRAs are designed to execute only the loops, which they can hence do more efficiently. This chapter discusses the basic principles of CGRAs and the wide range of design options available to a CGRA designer, covering a large number of existing CGRA designs. The impact of different options on flexibility, performance, and power-efficiency is discussed, as well as the need for compiler support. The ADRES CGRA design template is studied in more detail as a use case to illustrate the need for design space exploration, for compiler support and for the manual fine-tuning of source code.
Keywords
- Single Instruction Multiple Data
- Design Space Exploration
- Loop Body
- Very Long Instruction Word
- Loop Transformation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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De Sutter, B., Raghavan, P., Lambrechts, A. (2013). Coarse-Grained Reconfigurable Array Architectures. In: Bhattacharyya, S., Deprettere, E., Leupers, R., Takala, J. (eds) Handbook of Signal Processing Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6859-2_18
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