Remote Execution for 3D Graphics

by Banerjee, Kutty S.

Mobile clients such as PDAs, laptops, wrist watches, smart phones are rapidly emerging in the consumer market and an increasing number of graphics applications are being developed for them. However, current hardware technology limits the processing power on these mobile devices and wireless network bandwidth can be scarce and unreliable. A modern photorealistic graphics application is resource-hungry, consumes large amounts of cpu cycles, memory and network bandwidth if distributed. Besides running them on mobile devices may also diminish their battery power in the process. Bulk of graphics computations involve floating point operations and the lack of hardware support for such on PDAs imposes further restrictions. Remote execution, wherein part or the entire rendering process is offloaded to a powerful surrogate server is an attractive solution. We propose pipeline-splitting, a paradigm whereby 15 sub-stages of the graphics pipeline are isolated and instrumented with networking code such that it can run on either a graphics client or a surrogate server. To validate our concepts, we instrument Mesa3D, a popular implementation of the OpenGL graphics to support pipeline-splitting, creating Remote Mesa (RMesa). We further extend the Remote Execution model to provide an analytical model for predicting the rendering time and memory consumption involved in Remote Execution. Mobile devices have limited battery power. Therefore, it is important to understand if during Remote Execution, communication is more power consuming than computation. In order to study the same, we develop PowerSpy, a Real Time Power Profiler for I/O devices and applications. Finally, we add Remote Execution to an existing Distributed Graphics Framework targeted for mobile devices, namely, MADGRAF. In addition to Remote Execution, MADGRAF has another policy known as the Transcoder Based iii Approach in which the original 3D graphics image is modified to suite the mobile devices’ rendering capacity. Though this speeds up the rendering process, it affects photorealism. We propose an intelligent runtime decision making engine, Intelligraph, which evaluates the runtime performance of the mobile client and decides between Remote Execution and the Transcoder Based Approach. iv