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    • 33. 发明授权
    • Improving data locality and parallelism by code replication
    • 通过代码复制提高数据的局部性和并行性
    • US08453134B2
    • 2013-05-28
    • US12133268
    • 2008-06-04
    • John L. NgAlexander Y. OstanevichAlexander L. Sushentsov
    • John L. NgAlexander Y. OstanevichAlexander L. Sushentsov
    • G06F9/44
    • G06F8/4441
    • Provided are a method, system, and article of manufacture improving data locality and parallelism by code replication and array contraction. Source code including an array of elements referenced using at least two indices is processed. The array is nested within multiple loops, wherein at least two of the loops perform iterations with respect to the indices of the array, wherein the index incremented in at least one innermost loop of the loops does not comprise a leftmost index in the array. The source code is transformed to object code by performing operations including fusing at least two innermost loops of the loops in object code generated by compiling the source code by replicating statements from at least one of the innermost loops into a fused innermost loop and performing loop interchange in the object code to have the fused innermost loop provide iterations with respect to the leftmost index in the array.
    • 提供了通过代码复制和阵列收缩改进数据局部性和并行性的方法,系统和制品。 包含使用至少两个索引引用的元素数组的源代码被处理。 阵列嵌套在多个循环中,其中至少两个循环相对于阵列的索引执行迭代,其中在循环的至少一个最内循环中递增的索引不包括阵列中最左侧的索引。 通过执行操作,将源代码转换为目标代码,该操作包括通过将至少一个最内循环的语句复制到融合的最内循环并执行循环交换来编译源代码而生成的目标代码中的至少两个最内循环 在目标代码中使融合的最内层循环相对于数组中最左侧的索引提供迭代。
    • 38. 发明授权
    • Methods and apparatus for retrieving images from a large collection of images
    • 从大量图像中检索图像的方法和装置
    • US08565537B2
    • 2013-10-22
    • US13421406
    • 2012-03-15
    • Jean-Yves BouguetCarole DulongIgor V. KozintsevYi WuAra Nefian
    • Jean-Yves BouguetCarole DulongIgor V. KozintsevYi WuAra Nefian
    • G06K9/62
    • G06K9/6253G06F17/30256G06F17/30259
    • A processing system may receive an example image for use in querying a collection of digital images. The processing system may use local and global feature descriptors to perform a content-based image comparison of the digital images with the example image, to automatically rank the digital images with respect to similarity to the example image. A local feature descriptor may represent a portion of the contents of a digital image. A global feature descriptor may represent substantially all of the contents of that digital image. The global feature descriptor may be content based, not keyword based. Intermediate and final classifiers may be used to perform the automatic ranking. Different intermediate classifiers may generate intermediate relevance metrics with respect to different modalities. The final classifier may use results from the intermediate classifiers to produce a final relevance metric for the digital images. Other embodiments are described and claimed.
    • 处理系统可以接收用于查询数字图像集合的示例图像。 处理系统可以使用本地和全局特征描述符来执行数字图像与示例图像的基于内容的图像比较,以便根据与示例图像的相似度对数字图像进行自动排序。 局部特征描述符可以表示数字图像内容的一部分。 全局特征描述符可以基本上代表该数字图像的所有内容。 全局特征描述符可以是基于内容的,而不是基于关键字。 中级和最终分类器可用于执行自动排序。 不同的中间分类器可以产生关于不同模态的中间相关性度量。 最终分类器可以使用来自中间分类器的结果来产生数字图像的最终相关性度量。 描述和要求保护其他实施例。