Title:

 Parallel Computing -- A Theoretical Perspective 

Abstract:

The speeds of microprocessors are not increasing anymore. Yet the transistor sizes keep shrinking exponentially according to Moore's Law.  This resulted in the paradigm shift from sequential to parallel computing: multi-cores processors -- processors with multiple CPUs -- have become a norm, rather than exceptions.  Yet, we do not have good theoretical foundation for modern parallel systems and a clear understanding of what will make algorithms efficient on these systems.

In this presentation I will talk about the current landscape of modeling parallelism in modern multi-core architectures from the algorithmic perspective. I will also touch on emerging computational frameworks, alternative to multi-cores, such as GPUs and Google's MapReduce and how they are changing the landscape of parallel and distributed computing.

Bio:

Nodari Sitchinava received Bachelor and Master degrees in Electrical Engineering and Computer Science from MIT and a PhD in Computer Science from UC Irvine.  After graduating he accepted a postdoctoral appointment at the MADALGO Center at the CS department of Aarhus University where he is to this day. His research concentrates on developing accurate models of computation for modern parallel architectures and designing algorithms for them.  In particular, his PhD dissertation concentrated on combining cache-efficiency with parallelism for multi-core architectures and on the development of a number of fundamental combinatorial, graph and geometric algorithms in the new model.

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