Introducing the CULA Sparse Demo

We are very pleased to announce that we have recently released a free demo for CULA Sparse. This demo is manifested in a standalone, command line driven program with which you can choose your options and see the performance for a particular routine. All solvers and most features that are provided by CULA Sparse are supported.

For example, to run the demo with a cg solver and jacobi preconditioner, you can use the command below. The demo accepts matrices that are in the matrix market format (.mtx). For information on this format, see the resources provided by this NIST site.

iterativeBenchmark solver=cg preconditioner=jacobi A=myfile.mtx b=ones tolerance=1e-5

The CULA Sparse demo is powerful because it allows you to easily try our several different solvers, preconditioners, and other features without coding or building any software. And once you’ve found out the combination of inputs that is ideal for you, you can easily transition this knowledge into your CULA Sparse implementation.

Download the CULA Sparse demo today and see how our GPU-accelerated solvers can work for you.

CULA Sparse Available!

After several months of valuable Beta testing, we are pleased to announce the release and immediate availability of CULA Sparse. Our first release contains 6 solvers, 3 preconditioners, and supports double-precision and double-precision complex in a variety of matrix formats. Performance of 10x or more versus a fully threaded CPU solution is now available in an easy to use package!

CULA Dense R13 is a simultaneous release, also available now, and features three new routines (potri, gesdd, and geqrfp) as well as explicit compatibility with CULA Sparse.

For current users, we have changed the name of CULA Premium to CULA Dense, and CULA Basic is now CULA Dense Free Edition.

CULA Sparse Beta 2

CULA Sparse Beta 2 is undergoing final packaging and testing to be sent out to our Beta testers very soon. This is a Feature update, with the following changes:

• Added the BiCGSTAB solver
• Added the BiCGSTAB(L) solver
• Complex (Z) data types available for all solvers
• Fortran module added
• Configuration parameter to return best experienced solution
• Maximum runtime configuration parameter
• New example for Fortran interface
• New example for MatrixMarket data
• Several important bug fixes, as noted by the Beta testers

This release also contains the first steps towards interoperability with CULA for dense linear algebra, which some hybrid methods require. A user will now need to link cula_core and cula_sparse rather than just the sparse lib. Full interoperability will require CULA R13, which is also coming soon.

We are still accepting Sparse Beta applications, so register soon!