LAPACK++: a design overview of object-oriented extensions for high performance linear algebra
Proceedings of the 1993 ACM/IEEE conference on Supercomputing
Matrix computations (3rd ed.)
Co-array Fortran for parallel programming
ACM SIGPLAN Fortran Forum
Reliable Computation of the Condition Number of a Tridiagonal Matrix in O(n) Time
SIAM Journal on Matrix Analysis and Applications
Accurate Symmetric Indefinite Linear Equation Solvers
SIAM Journal on Matrix Analysis and Applications
A framework for symmetric band reduction
ACM Transactions on Mathematical Software (TOMS)
A recursive formulation of Cholesky factorization of a matrix in packed storage
ACM Transactions on Mathematical Software (TOMS)
FLAME: Formal Linear Algebra Methods Environment
ACM Transactions on Mathematical Software (TOMS)
LAPACK95 users' guide
Numerical Linear Algebra for High Performance Computers
Numerical Linear Algebra for High Performance Computers
An updated set of basic linear algebra subprograms (BLAS)
ACM Transactions on Mathematical Software (TOMS)
Design, implementation and testing of extended and mixed precision BLAS
ACM Transactions on Mathematical Software (TOMS)
The Multishift QR Algorithm. Part I: Maintaining Well-Focused Shifts and Level 3 Performance
SIAM Journal on Matrix Analysis and Applications
The Multishift QR Algorithm. Part II: Aggressive Early Deflation
SIAM Journal on Matrix Analysis and Applications
The Quadratic Eigenvalue Problem
SIAM Review
ACM Transactions on Mathematical Software (TOMS)
ACM Transactions on Mathematical Software (TOMS)
Statistical Models for Automatic Performance Tuning
ICCS '01 Proceedings of the International Conference on Computational Sciences-Part I
Key Concepts for Parallel Out-Of-Core LU Factorization
Key Concepts for Parallel Out-Of-Core LU Factorization
The Design and Implementation of the Parallel Out-of-coreScaLAPACK LU, QR, and Cholesky Factorization Routines
An Orthogonal High Relative Accuracy Algorithm for the Symmetric Eigenproblem
SIAM Journal on Matrix Analysis and Applications
Fast and Stable Algorithms for Banded Plus Semiseparable Systems of Linear Equations
SIAM Journal on Matrix Analysis and Applications
A Schur-Parlett Algorithm for Computing Matrix Functions
SIAM Journal on Matrix Analysis and Applications
Orthogonal Eigenvectors and Relative Gaps
SIAM Journal on Matrix Analysis and Applications
An evaluation of global address space languages: co-array fortran and unified parallel C
Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
Towards an Accurate Model for Collective Communications
International Journal of High Performance Computing Applications
International Journal of Parallel Programming
Error bounds from extra-precise iterative refinement
ACM Transactions on Mathematical Software (TOMS)
Multishift Variants of the QZ Algorithm with Aggressive Early Deflation
SIAM Journal on Matrix Analysis and Applications
Design for Interoperability in stapl: pMatrices and Linear Algebra Algorithms
Languages and Compilers for Parallel Computing
Towards dense linear algebra for hybrid GPU accelerated manycore systems
Parallel Computing
Detecting cyberbullying: query terms and techniques
Proceedings of the 5th Annual ACM Web Science Conference
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New releases of the widely used LAPACK and ScaLAPACK numerical linear algebra libraries are planned. Based on an on-going user survey (www.netlib.org/lapack-dev) and research by many people, we are proposing the following improvements: Faster algorithms, including better numerical methods, memory hierarchy optimizations, parallelism, and automatic performance tuning to accommodate new architectures; More accurate algorithms, including better numerical methods, and use of extra precision; Expanded functionality, including updating and downdating, new eigenproblems, etc. and putting more of LAPACK into ScaLAPACK; Improved ease of use, e.g., via friendlier interfaces in multiple languages. To accomplish these goals we are also relying on better software engineering techniques and contributions from collaborators at many institutions.