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Driven by the rapid hardware development of parallel CPU/GPU architectures, we have witnessed emerging relational query processing techniques and implementations on those parallel architectures. However, most of those implementations are not portable across different architectures, because they are usually developed from scratch and target at a specific(More)
Recently, there have been some emerging processor designs that the CPU and the GPU (Graphics Processing Unit) are integrated in a single chip and share Last Level Cache (LLC). However, the main memory bandwidth of such coupled CPU-GPU architectures can be much lower than that of a discrete GPU. As a result, current GPU query co-processing paradigms can(More)
Environmental problems have attracted increasing attention, yet individuals' connectedness to nature remains a significant concern for potential solutions to these problems. In this article, we propose a novel method to promote connectedness to nature: mindful learning. One hundred and thirty-four students participated in the experiment. First, baseline(More)
In the big data era, in-memory data analytics is an effective means of achieving high performance data processing and realizing the value of data in a timely manner. Efforts in this direction have been spent on various aspects, including in-memory algorithmic designs and system optimizations. In this paper, we propose to develop the next-generation(More)
Avoiding threatened ventriculostomy shunt exposure in the pediatric population remains a difficult problem for the neurosurgeon and reconstructive surgeon. In this case series, the authors present a novel method of augmenting scalp soft tissue with acellular dermal matrix (ADM) in patients with a history of ventricular shunt revisions. Soft tissue(More)
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