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HyperSense: Hyperdimensional Intelligent Sensing for Energy-Efficient Sparse Data Processing
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DOI：10.1002/aisy.202400228.png)
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Abstract
En 中文
Introducing HyperSense, the co-designed hardware and software system efficiently controls analog-to-digital converter (ADC) modules' data generation rate based on object presence predictions in sensor data. Addressing challenges posed by escalating sensor quantities and data rates, HyperSense reduces redundant digital data using energy-efficient low-precision ADC, diminishing machine learning system costs. Leveraging neurally inspired hyperdimensional computing, HyperSense analyzes real-time raw low-precision sensor data, offering advantages in handling noise, memory-centricity, and real-time learning. The proposed HyperSense model combines high-performance software for object detection with real-time hardware prediction, introducing the novel concept of intelligent sensor control. Comprehensive software and hardware evaluations demonstrate the solution's superior performance, evidenced by the highest area under the curve and sharpest receiver operating characteristic curve among lightweight models. Hardware-wise, the field programmable gate array-based domain-specific accelerator tailored for HyperSense achieves a 5.6x speedup compared to YOLOv4 on NVIDIA Jetson Orin while showing up to 92.1% energy saving compared to the conventional system. These results underscore HyperSense's effectiveness and efficiency, positioning it as a promising solution for intelligent sensing and real-time data processing across diverse applications. The article introduces HyperSense, a novel system that enhances sensor efficiency through hyperdimensional computing. This innovative approach significantly reduces unnecessary data processing by focusing solely on crucial information, saving energy, and improving both the speed and accuracy of data analysis. Ideal for real-world applications, it holds promise for various industries.image (c) 2024 WILEY-VCH GmbH
Keywords:
artificial intelligent
energy efficiency
hyperdimensional computing
intelligent sensing
Journal
IF:
6.1
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2.0K
Citations:
8.4K
