Joint Seminar, Computer Science and Electrical, Computer and Systems Engineering
Finding the Right Type of Parallelism in an "Embarrassingly Parallel" Algorithm
University of Utah
Wednesday, June 20, 2007
Unlike many areas of computer science interactive ray tracing
algorithms have evolved several times to remain at the cutting edge
of computing performance. Early work on multiprocessor super
computers directed the field towards fine-grained task-parallelism.
Later as desktop performance increased and memory became the
predominant bottleneck, algorithms evolved to increase memory
coherence by operating more coarsely on packets of data in parallel.
Today these algorithms are undergoing another transition to utilize
wide data parallel programming models on GPUs. These processors rely
on extensive SIMD operational coherence. This talk will describe
interactive ray tracing's transition from massive task parallel super
computers to multi-core CPUs, and recently to high performance
commodity data parallel models like CUDA. This transition illustrates
how other workloads might be adapted to leverage increasing degrees
of parallelism in mainstream platforms.
Bio: Abe Stephens is a PhD student at the University of Utah's Scientific
Computing and Imaging Institute where he works with Steven Parker.
His research focuses on parallel techniques for temporally adaptive
rendering and large data visualization. He is a principle contributor
to the Manta Interactive Ray Tracer and has worked with Intel and
Silicon Graphics to improve interactive ray tracing techniques on
parallel systems. Abe has published several papers on interactive ray
tracing and has spoken at Siggraph and Eurographics courses on the
subject. He received a BS in Computer Science from Rensselaer
Polytechnic Institute in 2003.
Hosted by: Carlos A. Varela (x6912)
Last updated: June 8, 2007