Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: KPynq: A Work-Efficient Triangle-Inequality based K-means on FPGA   K-means is a popular but computation-intensive algorithm for unsupervised
learning. To address this issue, we present KPynq, a work-efficient
triangle-inequality based K-means on FPGA for handling large-size,
high-dimension datasets. KPynq leverages an algorithm-level optimization to
balance the performance and computation irregularity, and a hardware
architecture design to fully exploit the pipeline and parallel processing
capability of various FPGAs. In the experiment, KPynq consistently outperforms
the CPU-based standard K-means in terms of its speedup (up to 4.2x) and
significant energy-efficiency (up to 218x).

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The categories of this paper are: plasm-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: dg-ga
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The categories of this paper are: bayes-an
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The categories of this paper are: math-ph
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The categories of this paper are: cmp-lg
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The categories of this paper are: ao-sci
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The categories of this paper are: adap-org
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The categories of this paper are: hep-lat
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The categories of this paper are: funct-an
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The categories of this paper are: astro-ph
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The categories of this paper are: alg-geom
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The categories of this paper are: cond-mat
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The categories of this paper are: comp-gas
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The categories of this paper are: acc-phys
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The categories of this paper are: hep-th