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Compressive sensing is widely used in biomedical applications, and the sampling matrix plays a critical role on both quality and power consumption of signal acquisition. It projects a high-dimensional vector of data into a low-dimensional subspace by matrix-vector multiplication. An optimal sampling matrix can ensure accurate data reconstruction and/or high compression ratio. Most existing optimization...
Network functions virtualization is a new paradigm to offer flexibility of software network function processing on demand. Policy enforcement satisfies network function policies that requires flows to traverse through given sequences of network functions. We summarize three desired properties of virtual network function placement, namely policy enforcement, interference freedom, and resource isolation...
To reduce healthcare cost while simultaneously delivering high-quality health services, developing new portable and/or implantable biomedical devices is of great importance for both health monitoring and clinical treatment. In this paper, we describe a radically new design framework for ultra-low-power biomedical circuit design and optimization. The proposed framework seamlessly integrates data processing...
MapReduce plays an critical role in finding insights in Big Data. The performance optimization of MapReduce programs is challenging because it requires a comprehensive understanding of the whole system including both hardware layers (processors, storages, networks and etc), and software stacks (operating systems, JVM, runtime, applications and etc). However, most of the existing performance tuning...
Many advanced hardware accelerations for virtualization, such as Pause Loop Exit (PLE), Extended Page Table (EPT), and Single Root I/O Virtualization (SR-IOV), have been introduced recently to improve the virtualization performance and scalability. In this paper, we share our experience with the performance and scalability issues of virtualization, especially those brought by the modern, multi-core...
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