Systolic array for matrix triangularization and back-substitution
    21.
    发明授权
    Systolic array for matrix triangularization and back-substitution 有权
    用于矩阵三角化和反向替代的收缩阵列

    公开(公告)号:US08510364B1

    公开(公告)日:2013-08-13

    申请号:US12552178

    申请日:2009-09-01

    IPC分类号: G06F7/32 G06F7/00

    CPC分类号: H04W24/10 G06F17/12 G06F17/16

    摘要: Methods for matrix processing and devices therefor are described. A systolic array in an integrated circuit is coupled to receive a first matrix as input; and is capable of operating in two modes, namely a triangularization mode and a back-substitution mode. The systolic array, when in a triangularization mode, is coupled to triangularize the first matrix to provide a second matrix. When in a back-substitution mode, the systolic array is coupled to invert the second matrix.

    摘要翻译: 对矩阵处理方法及其装置进行说明。 集成电路中的收缩阵列被耦合以接收第一矩阵作为输入; 并且能够以三角化模式和后置换模式两种模式操作。 当处于三角化模式时,收缩阵列被耦合到使第一矩阵三角化以提供第二矩阵。 当处于后置替代模式时,收缩阵列被耦合以反转第二矩阵。

    Combining multiple clusterings by soft correspondence
    22.
    发明授权
    Combining multiple clusterings by soft correspondence 有权
    通过软对应组合多个集群

    公开(公告)号:US08499022B1

    公开(公告)日:2013-07-30

    申请号:US13476100

    申请日:2012-05-21

    IPC分类号: G06F7/32

    CPC分类号: G06F17/30598

    摘要: Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because there is no explicit correspondence between the classes from different clusterings. Provided is a framework based on soft correspondence to directly address the correspondence problem in combining multiple clusterings. Under this framework, an algorithm iteratively computes the consensus clustering and correspondence matrices using multiplicative updating rules. This algorithm provides a final consensus clustering as well as correspondence matrices that gives intuitive interpretation of the relations between the consensus clustering and each clustering from clustering ensembles. Extensive experimental evaluations demonstrate the effectiveness and potential of this framework as well as the algorithm for discovering a consensus clustering from multiple clusterings.

    摘要翻译: 在各种重要的数据挖掘方案中,组合了多个集群。 然而,从多个集群中找到共识聚类是一项具有挑战性的任务,因为不同集群的类之间没有明确的对应关系。 提供了一种基于软对应的框架,直接解决组合多个集群的对应问题。 在这个框架下,算法使用乘法更新规则迭代地计算共享聚类和对应矩阵。 该算法提供最终的一致聚类以及对应矩阵,从而可以直观地解释聚类集合中的共聚集和聚类之间的关系。 广泛的实验评估表明了该框架的有效性和潜力,以及从多个聚类中发现共聚集的算法。

    Systems and methods for electronic postmarking of data including location data
    23.
    发明授权
    Systems and methods for electronic postmarking of data including location data 有权
    包括位置数据在内的数字电子邮戳的系统和方法

    公开(公告)号:US08417958B2

    公开(公告)日:2013-04-09

    申请号:US12830731

    申请日:2010-07-06

    IPC分类号: H04L25/493 G06F7/32

    CPC分类号: G06Q10/10

    摘要: Systems and methods for electronic postmarking of location data are provided. Electronic postmarking of location data (S.20) includes generating a hash value corresponding to merged data (S.30). Electronic postmarking further includes generating an electronic postmark data structure (S.40) comprising the hash value and a date/time stamp. The electronic postmarking data structure (S.40) may further include a digital signature.

    摘要翻译: 提供了位置数据电子邮戳的系统和方法。 位置数据的电子邮戳(S.20)包括产生对应于合并数据的散列值(S.30)。 电子邮戳还包括生成包括哈希值和日期/时间戳的电子邮戳数据结构(S.40)。 电子邮戳数据结构(S.40)还可以包括数字签名。

    Eigenvalue decomposition and singular value decomposition of matrices using Jacobi rotation
    25.
    发明授权
    Eigenvalue decomposition and singular value decomposition of matrices using Jacobi rotation 有权
    使用Jacobi旋转的矩阵的特征值分解和奇异值分解

    公开(公告)号:US07895254B2

    公开(公告)日:2011-02-22

    申请号:US11280596

    申请日:2005-11-15

    IPC分类号: G06F7/32

    摘要: Techniques for decomposing matrices using Jacobi rotation are described. Multiple iterations of Jacobi rotation are performed on a first matrix of complex values with multiple Jacobi rotation matrices of complex values to zero out the off-diagonal elements in the first matrix. For each iteration, a submatrix may be formed based on the first matrix and decomposed to obtain eigenvectors for the submatrix, and a Jacobi rotation matrix may be formed with the eigenvectors and used to update the first matrix. A second matrix of complex values, which contains orthogonal vectors, is derived based on the Jacobi rotation matrices. For eigenvalue decomposition, a third matrix of eigenvalues may be derived based on the Jacobi rotation matrices. For singular value decomposition, a fourth matrix with left singular vectors and a matrix of singular values may be derived based on the Jacobi rotation matrices.

    摘要翻译: 描述了使用雅可比旋转分解矩阵的技术。 对具有复数值的多个Jacobi旋转矩阵的复数值的第一矩阵执行Jacobi旋转的多次迭代,以将第一矩阵中的非对角线元素归零。 对于每次迭代,可以基于第一矩阵形成子矩阵并分解以获得子矩阵的特征向量,并且可以与特征向量形成雅可比旋转矩阵并用于更新第一矩阵。 基于Jacobi旋转矩阵导出包含正交向量的第二个复数值矩阵。 对于特征值分解,可以基于Jacobi旋转矩阵导出特征值的第三矩阵。 对于奇异值分解,可以基于雅可比旋转矩阵导出具有左奇异矢量的第四矩阵和奇异值矩阵。

    Method For Solving Reservoir Simulation Matrix Equation Using Parallel Multi-Level Incomplete Factorizations
    26.
    发明申请
    Method For Solving Reservoir Simulation Matrix Equation Using Parallel Multi-Level Incomplete Factorizations 审中-公开
    使用并行多级不完全因式分解求解油藏模拟矩阵方程的方法

    公开(公告)号:US20100082724A1

    公开(公告)日:2010-04-01

    申请号:US12505275

    申请日:2009-07-17

    IPC分类号: G06F7/32

    CPC分类号: G06F17/16 G06F17/12

    摘要: A parallel-computing iterative solver is provided that employs a preconditioner that is processed using parallel-computing for solving linear systems of equations. Thus, a preconditioning algorithm is employed for parallel iterative solution of a large sparse system of linear system of equations (e.g., algebraic equations, matrix equations, etc.), such as the linear system of equations that commonly arise in computer-based 3D modeling of real-world systems (e.g., 3D modeling of oil or gas reservoirs, etc.). A novel technique is proposed for application of a multi-level preconditioning strategy to an original matrix that is partitioned and transformed to block bordered diagonal form. An approach for deriving a preconditioner for use in parallel iterative solution of a linear system of equations is provided. In particular, a parallel-computing iterative solver may derive and/or apply such a preconditioner for use in solving, through parallel processing, a linear system of equations.

    摘要翻译: 提供了一种并行计算迭代求解器,其使用预处理器,其使用并行计算来处理以求解线性方程组。 因此,采用预处理算法用于线性方程组(例如代数方程组,矩阵方程式等)的大型稀疏系统的并行迭代解,如基于计算机的3D建模中通常出现的线性方程组 的现实系统(例如,油气藏三维建模等)。 提出了一种新颖的技术,用于将多级预处理策略应用于原始矩阵,该原始矩阵被分割和转换为块边界对角线形式。 提供了一种用于导出用于线性方程组的迭代解的预处理器的方法。 特别地,并行计算迭代求解器可以导出和/或应用这样的预处理器,以用于通过并行处理来求解线性方程组。

    SOLVER FOR HARDWARE BASED COMPUTING
    27.
    发明申请
    SOLVER FOR HARDWARE BASED COMPUTING 审中-公开
    用于硬件计算的解决方案

    公开(公告)号:US20090292520A1

    公开(公告)日:2009-11-26

    申请号:US12373481

    申请日:2007-07-27

    IPC分类号: G06F9/455 G06F9/00 G06F7/32

    CPC分类号: G06F17/5027 G06F17/16

    摘要: Full-AC load flow constitutes a core computation in power system analysis. The present invention provides a performance gain with a hardware implementation of a sparse-linear solver using a Field Programmable Gate Array (FPGA). The invention also relates to the design, simulation, and hardware verification of a static transmission line model for analog power flow computation. Operational transconductance amplifiers are employed in the model based on a previously proposed DC emulation technique of power flow computation, and provide reconfigurability of transmission line parameters via transconductance gain. The invention also uses Analog Behavioral Models (ABMs) in an efficient strategy for designing analog emulation engines for large-scale power system computation. Results of PSpice simulations of these emulation circuits are compared with industrial grade numerical simulations for validation. The application is also concerned with the development of a generator model using analog circuits for load flow emulation for power system analysis to reduce computation time. The generator model includes reconfigurable parameters using operational transconductance amplifiers (OTAs). The circuit module is used with other reconfigurable circuits, i.e., transmission lines and loads.

    摘要翻译: 全交流负载流是电力系统分析中的核心计算。 本发明通过使用现场可编程门阵列(FPGA)的稀疏线性求解器的硬件实现来提供性能增益。 本发明还涉及用于模拟功率流计算的静态传输线模型的设计,仿真和硬件验证。 基于先前提出的功率流计算的直流仿真技术,在模型中采用运算跨导放大器,并通过跨导增益提供传输线参数的可重新配置。 本发明还在用于设计用于大规模电力系统计算的模拟仿真引擎的有效策略中使用模拟行为模型(ABM)。 将这些仿真电路的PSpice仿真结果与工业级数值模拟进行比较以进行验证。 该应用还涉及使用模拟电路用于电力系统分析的负载流仿真的发电机模型的开发,以减少计算时间。 发生器模型包括使用运算跨导放大器(OTA)的可重新配置的参数。 电路模块与其他可重新配置的电路,即传输线路和负载一起使用。

    Processing device for a pseudo inverse matrix and V-BLAST system
    28.
    发明授权
    Processing device for a pseudo inverse matrix and V-BLAST system 失效
    用于伪逆矩阵和V-BLAST系统的处理装置

    公开(公告)号:US07571203B2

    公开(公告)日:2009-08-04

    申请号:US10972235

    申请日:2004-10-21

    IPC分类号: G06F7/32

    摘要: Disclosed is a V-BLAST system for a MIMO communication system.In the V-BLAST system for a MIMO communication system, a pseudo inverse matrix calculator receives a channel transfer function matrix including channel information and produces a cofactor matrix and a determinant for a pseudo inverse matrix. A norm & minimum calculator calculates a minimum index for the cofactor matrix outputted from the pseudo inverse matrix calculator, a weight vector selector selects a row vector having the minimum index and calculates a transposed matrix for the row vector; an adder adds the transposed matrix to a received input symbol, and a subtractor subtracts the determinant to the output. A demapper performs a determined function operation to the output and produces estimated information.

    摘要翻译: 公开了一种用于MIMO通信系统的V-BLAST系统。 在用于MIMO通信系统的V-BLAST系统中,伪逆矩阵计算器接收包括信道信息的信道传递函数矩阵,并产生用于伪逆矩阵的辅因子矩阵和行列式。 规范和最小计算器计算从伪逆矩阵计算器输出的辅因子矩阵的最小索引,权重向量选择器选择具有最小索引的行向量并计算行向量的转置矩阵; 加法器将转置的矩阵添加到接收到的输入符号,并且减法器将输出的行列式减去。 解映射器对输出执行确定的功能操作并产生估计信息。

    METHOD AND STRUCTURE FOR FAST IN-PLACE TRANSFORMATION OF STANDARD FULL AND PACKED MATRIX DATA FORMATS
    29.
    发明申请
    METHOD AND STRUCTURE FOR FAST IN-PLACE TRANSFORMATION OF STANDARD FULL AND PACKED MATRIX DATA FORMATS 有权
    标准完整和包装矩阵数据格式的快速插入转换的方法和结构

    公开(公告)号:US20090063607A1

    公开(公告)日:2009-03-05

    申请号:US11849272

    申请日:2007-09-01

    IPC分类号: G06F7/32

    摘要: A method and structure for an in-place transformation of matrix data. For a matrix A stored in one of a standard full format or a packed format and a transformation T having a compact representation, blocking parameters MB and NB are chosen, based on a cache size. A sub-matrix A1 of A, A1 having size M1=m*MB by N1=n*NB, is worked on, and any of a residual remainder of A is saved in a buffer B. Sub-matrix A1 is worked on by contiguously moving and contiguously transforming A1 in-place into a New Data Structure (NDS), applying the transformation T in units of MB*NB contiguous double words to the NDS format of A1, thereby replacing A1 with the contents of T(A1), and moving and transforming NDS T(A1) to standard data format T(A1) with holes for the remainder of A in buffer B. The contents of buffer B is contiguously copied into the holes of A2, thereby providing in-place transformed matrix T(A).

    摘要翻译: 矩阵数据的就地转换的方法和结构。 对于以标准全格式或打包格式之一存储的矩阵A和具有紧凑表示的变换T,基于高速缓存大小来选择阻塞参数MB和NB。 对于具有M1 = m * MB的N1 = n * NB的A的A1的矩阵A1进行加工,并且A的剩余余数中的任一个保存在缓冲器B中。子矩阵A1由 将A1原位连续移动并连续地转换为新数据结构(NDS),将以MB * NB连续双字为单位的变换T应用于A1的NDS格式,从而将A1替换为T(A1)的内容, 并且将NDS T(A1)移动并变换为具有用于缓冲器B中的剩余部分的空穴的标准数据格式T(A1)。缓冲器B的内容被连续地复制到A2的孔中,从而提供就地变换矩阵T (一个)。

    Parallel processing method for inverse matrix for shared memory type scalar parallel computer
    30.
    发明授权
    Parallel processing method for inverse matrix for shared memory type scalar parallel computer 有权
    用于共享内存类型标量并行计算机的逆矩阵并行处理方法

    公开(公告)号:US07483937B2

    公开(公告)日:2009-01-27

    申请号:US10692533

    申请日:2003-10-24

    申请人: Makoto Nakanishi

    发明人: Makoto Nakanishi

    IPC分类号: G06F7/52 G06F7/32

    CPC分类号: G06F17/16

    摘要: A Matrix decomposition (LU decomposition) is carried out on a block E and H. Then, a block B is updated using an upper triangular portion of the block E, and a block D is updated using a lower triangular portion of the block E. At this time, in an LU decomposition, blocks F and I have been updated. Then, using the blocks B, D, F, and H, blocks A, C, G, and I are updated, an upper triangular portion of the block E is updated, and finally, the blocks D and F are updated. Then, the second updating process is performed on the block E. Using the result of the process, the blocks B and H are updated. Finally, the block E is updated, and the pivot interchanging process is completed, thereby terminating the process. These processes on the blocks are performed in a plurality of divided threads in parallel.

    摘要翻译: 在块E和H上执行矩阵分解(LU分解)。然后,使用块E的上三角形部分更新块B,并且使用块E的下三角形部分来更新块D. 此时,在LU分解中,块F和I已被更新。 然后,使用块B,D,F和H,块A,C,G和I被更新,块E的上三角形部分被更新,最后更新块D和F。 然后,在块E上执行第二更新处理。使用该处理的结果,更新块B和H。 最后,更新块E,完成枢纽交换处理,从而终止进程。 块上的这些处理是并行地在多个划分的线程中执行的。