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An FPGA-Based Cloud System for Massive ECG Data Analysis
DOI:10.1109/TCSII.2016.2556861.png)
Abstract
En 中文
In this brief, we propose a stand-alone system-on-a-programmable-chip (SOPC)-based cloud system to accelerate massive electrocardiogram (ECG) data analysis. The proposed system tightly couples network I/O handling hardware to data processing pipelines in a single field-programmable gate array (FPGA), offloading both networking operations and ECG data analysis. In this system, we first propose a massive-sessions optimized TCP/IP hardware stack using a macropipeline architecture to accelerate network packet processing. Second, we propose a streaming architecture to accelerate ECG signal processing, including QRS detection, feature extraction, and classification. We verify our design on XC6VLX550T FPGA using real ECG data. Compared to commercial servers, our system shows up to 38x improvement in performance and 142x improvement in energy efficiency.
Keywords:
Cloud computing
electrocardiogram (ECG) data analysis
field-programmable gate array (FPGA)
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