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Deep Computing Visualization (DCV) Solution is originated from an IBM research project. It leverages de facto standard software such as OpenGL and commodity graphics hardware to build a collaborative and scalable visualization environment.
It currently has two main functions:
(1) Remote Visualization Networking (RVN) provides multiple collaborative visual sessions in physically separated locations. And
(2) Scalable Visualization Networking (SVN) scales up images to large scale display devices such as multiple projector screen and cave by distributing rendering task to a cluster of graphic workstations.
These functions facilitate a mean to conduct activities with high performance visual effect at an affordable cost and hence, result in delivering benefit of visual effect to the general user community. IBM Research builds on the current DCV success to develop a (soon to release) new function called Scalable Parallel Visualization Networking (SPVN). SPVN provides user full distributed rendering capability, i.e. an unlimited scalability in theory and new flexibility in selecting rendering algorithmic and hardware rendering engines.
For example, it opens up the opportunity of utilizing the extreme digital processing power of the IBM-Sony-Toshiba jointly developed Cell Processor. One of the applications made possible by SPVN would be the “Simulation Steering” system environment long sought in computational science. Similar concept can also be applied to performing arts.
Dr. Dominic Lam graduated from the Department of Physics at the University of Toronto. He joined IBM as an Advisory System Engineer in 1988. His current position at IBM is National eServer Manager responsible for providing high performance computing solutions to clients across Canada. Dominic joined the Industrial Advisory Board of the Concordia Institute of Information System Engineering at Concordia University in 2003.
on the digital Interfaces Industry.
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