WireGL: a scalable graphics system for clusters
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Chromium: a stream-processing framework for interactive rendering on clusters
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Infopipes: an abstraction for multimedia streaming
Multimedia Systems
Parallel Bindings in Distributed Multimedia Systems
ICDCSW '05 Proceedings of the Seventh International Workshop on Multimedia Network Systems and Applications - Volume 07
OpenVIDIA: parallel GPU computer vision
Proceedings of the 13th annual ACM international conference on Multimedia
Biomedical image analysis on a cooperative cluster of GPUs and multicores
Proceedings of the 22nd annual international conference on Supercomputing
Network-integrated multimedia middleware (NMM)
MM '08 Proceedings of the 16th ACM international conference on Multimedia
GpuCV: an opensource GPU-accelerated framework forimage processing and computer vision
MM '08 Proceedings of the 16th ACM international conference on Multimedia
The NIST Data Flow System II: A standardized interface for distributed multimedia applications
WOWMOM '08 Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks
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Available GPUs provide increasingly more processing power especially for multimedia and digital signal processing. Despite the tremendous progress in hardware and thus processing power, there are and always will be applications that require using multiple GPUs either running inside the same machine or distributed in the network due to computational intensive processing algorithms. Existing solutions for developing applications for GPUs still require a lot of hand-optimization when using multiple GPUs inside the same machine and provide in general no support for using remote GPUs distributed in the network. In this paper we address this problem and show that an open distributed multimedia middleware, like the Network-Integrated Multimedia Middleware (NMM), is able (1) to seamlessly integrate processing components using GPUs while completely hiding GPU specific issues from the application developer, (2) to transparently combine processing components using GPUs or CPUs, and (3) to transparently use local and remote GPUs for distributed processing.