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Hardware specialization, in the form of accelerators that provide custom datapath and control for specific algorithms and applications, promises impressive performance and energy advantages compared to traditional architectures. Current research in accelerator analysis relies on RTL-based synthesis flows to produce accurate timing, power, and area(More)
—Recent high-level synthesis and accelerator-related architecture papers show a great disparity in workload selection. To improve standardization within the accelerator research community , we present MachSuite, a collection of 19 benchmarks for evaluating high-level synthesis tools and accelerator-centric ar-chitectures. MachSuite spans a broad application(More)
The continued success of Deep Neural Networks (DNNs) in classification tasks has sparked a trend of accelerating their execution with specialized hardware. While published designs easily give an order of magnitude improvement over general-purpose hardware, few look beyond an initial implementation. This paper presents Minerva, a highly automated co-design(More)
As the traditional performance gains of technology scaling diminish, one of the most promising directions is building special purpose fixed function hardware blocks, commonly referred to as accelerators. Accelerators have become prevalent in industrial SoC designs for their low power, high performance potential. In this work we explore thousands of(More)
We demonstrate a battery-powered multi-chip system optimized for insect-scale flapping wing robots that meets the tight weight limit and real-time performance demands of autonomous flight. Measured results show open-loop wing flapping driven by a power electronics unit and energy efficiency improvements via hardware acceleration. Introduction Recent(More)
—Deep learning has been popularized by its recent successes on challenging artificial intelligence problems. One of the reasons for its dominance is also an ongoing challenge: the need for immense amounts of computational power. Hardware architects have responded by proposing a wide array of promising ideas, but to date, the majority of the work has focused(More)
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