After a long wait, GPULib 1.6 is finally ready to download! Here’s the brief version of the release notes (for a more detailed list, see the GPULib blog):

• All platforms, Windows, Linux, and OS X, are now distributed as binaries. No building from source required!
• Added MAGMA (GPU accelerated LAPACK library) linear algebra routines.
• GPULib can now load and execute custom CUDA kernels without having to link to it; you just compile your kernel to a .ptx file. We provide routines to load and execute that kernel at runtime.
• Support for CUDA 5.0.
• Added support for up to 8-dimensional arrays.