rCUDA

rCUDA

From the post:

We are glad to announce the new version 3.1 of rCUDA. It has been developed in a joint collaboration with the Parallel Architectures Group from the Technical University of Valencia.

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 increased GPU usage and therefore 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.

This was mentioned in the Letting GPUs run free post but I thought it merited a separate entry. This is very likely to be important.

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