Saketh Rama

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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)
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)
Machine Learning (ML) techniques empower Internet of Things (IoT) devices with the capability to interpret the complex, noisy real-world data arising from sensorrich systems. Achieving sufficient energy efficiency to execute ML workloads on an edge-device necessitates specialized hardware with efficient digital circuits. Razor systems allow excessive(More)
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