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CULA Sparse S3 (CUDA 4.2)  
Release Notes
EM Photonics, Inc.
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Installation Instructions
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For installation instructions, please consult the CULAProgrammersGuide.pdf file
included in the 'doc' folder of your CULA Sparse distribution.

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System Requirements
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CULA requires that your system be equipped with a NVIDIA CUDA-compatible device
in order to run CULA-enabled programs.  The NVIDIA drivers must be version 
301.32 (or greater) for Windows systems and 295.41 for Linux systems.  
Mac OS X systems must have 4.2.10 or newer.

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Supported Operating Systems
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All systems feature 32-bit and 64-bit support.

* Windows XP / Vista / 7 

* Ubuntu Linux 10.04 (and newer)

* Red Hat Enterprise Linux 5.3 (and newer)

* Fedora 11

* Mac OSX 10.6 Snow Leopard / 10.7 Lion

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Revision History
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CULA Sparse S3 (August 14, 2012)
CULA Sparse S2 (January 30, 2012)
CULA Sparse S1 (November 2, 2012)
CULA Sparse S1 Beta 2 (September 27, 2011)
CULA Sparse S1 Beta 1 (August 24, 2011)

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Changelog
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Release S3 CUDA 4.2 (August 14, 2012)
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* Announcement: All packages are now "universal" and contain both 32-bit and 64-bit binaries
* Feature: CUDA runtime upgraded to 4.2
* Feature: Kepler support
* Changed: Fortran module is now located in "include"

Release S2 CUDA 4.1 (January 30, 2012)
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* Feature: CUDA runtime upgraded to version 4.1
* Improved: Stability of COO and CSC interfaces
* Fixed: Now shipping all dependencies required by OSX systems

Release S1 CUDA 4.0 (November 2, 2011)
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* Feature: Improved speeds for all solvers
* Feature: Matrix reordering option; can lead to large perf gains for ILU
* Feature: MINRES solver
* Feature: Fully compatible with CULA R13 and above
* Feature: Option to disable stagnation checking for more speed
* Feature: Added iterativeBenchmark example for evaluating the performance of different solvers and options
* Improved: Result printout will show if useBestAnswer was invoked
* Changed: Header renamed to cula_sparse.h; transitional header available
* Notice: Integrated LGPL COLAMD package; see src folder and license

Release S1 Beta 2 CUDA 4.0 (September 27, 2011)
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* Feature: BiCGSTAB solver
* Feature: BiCGSTAB(L) solver
* Feature: Complex (Z) data types available for all solvers
* Feature: Fortran module added
* Feature: Configuration parameter to return best experienced solution 
* Feature: Maximum runtime configuration parameter
* Feature: New example for Fortran interface
* Feature: New example for MatrixMarket data
* Changed: Must link two libraries now (cula_sparse and cula_core)

Release S1 Beta 1 CUDA 4.0 (August 24, 2011)
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* Feature: Cg, BiCg, and GMRES solvers
* Feature: CSC, CSR, COO storage formats
* Feature: Jacobi, Block Jacobi, ILU0 preconditioners
* Feature: Double precision only
* Feature: Support for all standard CUDA platforms; Linux 32/64, Win 32/64, OSX


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More Information
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For more information on the CULAtools family of products, please visit our
webpage at http://www.culatools.com

To provide feedback, please visit http://www.culatools.com/forums and post in
the appropriate forum topic.

