We are happy to announce the new version 3.1.1 of rCUDA. It has been developed in a joint collaboration between the Parallel Architectures Group from the Universitat Politecnica de Valencia and the High Performance Computing and Architectures Group from the Universitat Jaume I.

The rCUDA Framework enables the concurrent usage of CUDA-compatible devices remotely.

rCUDA employs the socket API for the communication between clients and servers. Thus, it can be useful in three different environments:

• Clusters. To reduce the number of GPUs installed in High Performance Clusters. This leads to increase GPUs use and to energy savings, as well as other related savings like acquisition costs, maintenance, space, cooling, etc.
• Academia. In commodity networks, to offer access to a few high performance GPUs concurrently to many students.
• Virtual Machines. To enable the access to the CUDA facilities on the physical machine.

The current version of rCUDA (v3.1) implements most of the functions in the CUDA Runtime API version 4.0, excluding only those related with graphics interoperability. rCUDA 3.1 targets the Linux OS (for 32- and 64-bit architectures) on both client and server sides.

Currently, rCUDA-ready applications have to be programmed using the plain C API. In addition, host and device code need to be compiled separately. Find code examples in the rCUDA SDK 4.0 package or in the rCUDA SDK 3.1 package, based on the NVIDIA CUDA SDK 4.0 and 3.1, respectively. For further information, refer to the rCUDA User's Guide.

If you are interested in evaluating rCUDA, please proceed to the Software request form page. The rCUDA team will be glad to send you a copy of the software at no cost. The framework is free for institutional use.

For further information, please refer to the papers listed in the developer's personal webpage.