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.
  • Added optimized scalar/array operations.
  • Miscellaneous bug fixes.

A lot of work was done on infrastructure to make releasing an easier process, hopefully resulting in more frequent releases. We have plans for some very exciting features in the coming year!

Full disclosure: I work for Tech-X Corporation and I am the product manager for GPULib.