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• W3100932218 abstract "Hardware accelerators are key to the efficiency and performance of system-on-chip (SoC) architectures. With high-level synthesis (HLS), designers can easily obtain several performance-cost trade-off implementations for each component of a complex hardware accelerator. However, navigating this design space in search of the Pareto-optimal implementations at the system level is a hard optimization task. We present COSMOS, an automatic methodology for the design-space exploration (DSE) of complex accelerators, that coordinates both HLS and memory optimization tools in a compositional way. First, thanks to the co-design of datapath and memory, COSMOS produces a large set of Pareto-optimal implementations for each component of the accelerator. Then, COSMOS leverages compositional design techniques to quickly converge to the desired trade-off point between cost and performance at the system level. When applied to the system-level design (SLD) of an accelerator for wide-area motion imagery (WAMI), COSMOS explores the design space as completely as an exhaustive search, but it reduces the number of invocations to the HLS tool by up to 14.6×." @default.
• W3100932218 created "2020-11-23" @default.
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• W3100932218 date "2017-09-27" @default.
• W3100932218 modified "2023-10-18" @default.
• W3100932218 title "COSMOS" @default.
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• W3100932218 doi "https://doi.org/10.1145/3126566" @default.
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