公开(公告)号：US09471289B2

公开(公告)日：2016-10-18

申请号：US14667819

申请日：2015-03-25

Applicant: NEC Laboratories America, Inc.

Inventor： Min Feng ,  Srimat Chakradhar ,  Linhai Song

IPC: G06F9/45

CPC classification number: G06F8/443 ,  G06F8/433 ,  G06F8/51

Abstract: Systems and methods for source-to-source transformation for compiler optimization for many integrated core (MIC) coprocessors, including identifying data dependencies in candidate loops and data elements used in each iteration for arrays, profiling candidate loops to find a proper number m, wherein data transfer and computation for m iterations take an equal amount of time, and creating an outer loop outside the candidate loop, with each iteration of the outer loop executing m iterations of the candidate loop. Data streaming is performed by determining optimum buffer size for one or more arrays and inserting code before the outer loop to create optimum sized buffers, overlapping data transfer between central processing units (CPUs) and MICs with the computation; reusing buffers to reduce memory employed on the MICs, and reusing threads on MICs to repeatedly launch kernels on the MICs for asynchronous data transfer.

Abstract translation: 用于许多集成核心（MIC）协处理器的编译器优化的源到源转换的系统和方法，包括识别用于阵列的每次迭代中使用的候选循环和数据元素中的数据依赖性，分析候选循环以找到适当数量m，其中 m次迭代的数据传输和计算需要等量的时间，并且在候选循环外部创建外部循环，每个外部循环的迭代执行候选循环的m次迭代。 通过确定一个或多个阵列的最佳缓冲区大小并在外部循环之前插入代码来创建最佳大小的缓冲区，在中央处理单元（CPU）与MIC之间重叠数据传输与计算来执行数据流; 重用缓冲区以减少在MIC上使用的存储器，并且在MIC上重复使用线程来重复地在MIC上启动内核以进行异步数据传输。

公开(公告)号：US20160299920A1

公开(公告)日：2016-10-13

申请号：US15088452

申请日：2016-04-01

Applicant: NEC Laboratories America, Inc.

Inventor： Min Feng ,  Giuseppe Coviello ,  Srimat Chakradhar ,  Nitin Agrawal ,  Yi Yang

IPC: G06F17/30 ,  G06K9/62 ,  G06K9/00

CPC classification number: G06F17/30277 ,  G06F17/30256 ,  G06F17/30781 ,  G06K9/00268 ,  G06K9/00711 ,  G06K9/6219 ,  G06K9/6223 ,  G06K9/6272

Abstract: Systems and methods for recognizing a face are disclosed and includes receiving images of faces; generating feature vectors of the images; generating clusters of feature vectors each with a centroids or a cluster representative; for a query to search for a face, generating corresponding feature vectors for the face and comparing the feature vector with the centroids of all clusters; for clusters above a similarity threshold, comparing cluster members with the corresponding feature vector; and indicating as matching candidates for cluster members with similarity above a threshold.

Abstract translation: 公开了用于识别面部的系统和方法，并且包括接收面部图像; 生成图像的特征向量; 产生每个具有质心或簇代表的特征向量簇; 用于搜索面部的查询，为面部生成相应的特征向量并将特征向量与所有聚类的质心进行比较; 对于高于相似性阈值的簇，将簇成员与对应的特征向量进行比较; 并且指示作为具有高于阈值的相似性的聚类成员的匹配候选。