Jacket DLA

    鴻鵠國際為台灣區JACKET代理商,同時也是NVIDIA GPU在台灣的代理商。
    針對此產品教育訓練以及任何諮詢 請來電 廖先生  0917-782-811  terence@honghutech.com  
    Jacket DLA
     
    Double Precision Linear Algebra 
    Jacket DLA provides dense linear algebra support for the base Jacket product. Functions for matrix analysis, linear systems solutions, eigen analysis, singular value decomposition, and various factorizations are enabled for both single- and double-precision as well as for complex values with Jacket DLA. AccelerEyes, our partners, and the CUDA community of developers are continuing to expand support for high performance linear algebra in every release so check our documentation and release notes for the latest functions supported.
     

    The following MATLAB functions are currently enabled with JacketDLA:

     MLDIVIDE - Least-squares solutions to over- and under-determined systems
     LU - LU decomposition
     SVD - Singular value decomposition
     EIG - Eigenvalues
     QR - QR factorization
     CHOL - Cholesky decomposition
     NV - Matrix inverse
     MPOWER - Matrix power
     NORM - L2 matrix norm
     DET - Matrix determinant
     HESS - Hessenberg form of matrix
     
    For applications that do not require double-precision, the base Jacket license provides limited, single precision versions of matrix power, SVD, LU, QR, and MLDIVIDE.
     
     
     
     
     
    Jacket DLA

    雙精度線性代數
    Jacket DLA提供基礎Jacket產品密集的線性代數支持。矩陣分析,線性系統的解決方案,特徵分析,奇異值分解,以及各種因子分解的功能單一精度和雙精度都可以啟用以及Jacket DLA複數。AccelerEyes,我們的合作夥伴,開發者的CUDA社會正在在每一個版本的高性能線性代數繼續擴大它的支持,请观看我們的文檔和發行說明寻找最新支持的功能。

    一下的MATLAB功能目前與 JacketDLA啟用

     MLDIVIDE - Least-squares solutions to over- and under-determined systems
     LU - LU decomposition
     SVD - Singular value decomposition
     EIG - Eigenvalues
     QR - QR factorization
     CHOL - Cholesky decomposition
     NV - Matrix inverse
     MPOWER - Matrix power
     NORM - L2 matrix norm
     DET - Matrix determinant
     HESS - Hessenberg form of matrix

    對於不需要雙精度的應用,基礎Jacket許可證提供有限單一精度矩陣能力,SVDLUQR,並 MLDIVIDE