With the increasing amount of data,there is an urgent need for efficient sorting algorithms to process large data *** sorting algorithms have attracted much attention because they can take advantage of different hardw...
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With the increasing amount of data,there is an urgent need for efficient sorting algorithms to process large data *** sorting algorithms have attracted much attention because they can take advantage of different hardware's *** the traditional hardware sort accelerators suffer“memory wall”problems since their multiple rounds of data transmission between the memory and the *** this paper,we utilize the in-situ processing ability of the ReRAM crossbar to design a new ReCAM array that can process the matrix-vector multiplication operation and the vector-scalar comparison in the same array *** this designed ReCAM array,we present ReCSA,which is the first dedicated ReCAM-based sort *** hardware designs,we also develop algorithms to maximize memory utilization and minimize memory exchanges to improve sorting *** sorting algorithm in ReCSA can process various data types,such as integer,float,double,and *** also present experiments to evaluate the performance and energy efficiency against the state-of-the-art sort *** experimental results show that ReCSA has 90.92×,46.13×,27.38×,84.57×,and 3.36×speedups against CPU-,GPU-,FPGA-,NDP-,and PIM-based platforms when processing numeric data *** also has 24.82×,32.94×,and 18.22×performance improvement when processing string data sets compared with CPU-,GPU-,and FPGA-based platforms.
Air quality significantly impacts human health and economic conditions, making precise and timely assessment crucial in urban areas. Existing studies often fail to predict pollution accurately in smaller areas due to ...
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Most previous studies on discourse parsing have utilized discriminative models to construct tree structures. However, these models tend to overlook the global perspective of the tree structure as a whole during the st...
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Most of statistics and AI draw insights through modeling discord or variance between sources (i.e., intersource) of information. Increasingly however, research is focusing on uncertainty arising at the level of indivi...
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The adoption of Optical Character Recognition (OCR) tools has been central to the increased digitization of historical documents. However, the errors introduced during OCR, particularly in texts with a specialized voc...
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Cuckoo search (CS) algorithm is proposed by Yang and Deb, which is a simple and effective swarm intelligence algorithm. In each iteration, the CS search for new solutions by the global explorative random walk and the ...
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Progressive diagnosis prediction in healthcare is a promising yet challenging task. Existing studies usually assume a pre-defined prior for generating patient distributions (e.g., Gaussian). However, the inferred appr...
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In medical question-answering, traditional knowledge triples often fail due to superfluous data and their inability to capture complex relationships between symptoms and treatments across diseases. This limits models&...
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Event Extraction(EE)is a key task in information extraction,which requires high-quality annotated data that are often costly to *** classification-based methods suffer from low-resource scenarios due to the lack of la...
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Event Extraction(EE)is a key task in information extraction,which requires high-quality annotated data that are often costly to *** classification-based methods suffer from low-resource scenarios due to the lack of label semantics and fine-grained *** recent approaches have endeavored to address EE through a more data-efficient generative process,they often overlook event keywords,which are vital for *** tackle these challenges,we introduce KeyEE,a multi-prompt learning strategy that improves low-resource event extraction by Event Keywords Extraction(EKE).We suggest employing an auxiliary EKE sub-prompt and concurrently training both EE and EKE with a shared pre-trained language *** the auxiliary sub-prompt,KeyEE learns event keywords knowledge implicitly,thereby reducing the dependence on annotated ***,we investigate and analyze various EKE sub-prompt strategies to encourage further research in this *** experiments on benchmark datasets ACE2005 and ERE show that KeyEE achieves significant improvement in low-resource settings and sets new state-of-the-art results.
The Practical Byzantine Fault Tolerance protocol (PBFT) has been widely deployed in the blockchain network. However, two main issues, the communication complexity and the inability of nodes to join/exit the network wi...
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