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26th IEEE International Parallel & Distributed Processing Symposium, IPDPS 2012

May 21-25, 2012
Shanghai, China

IPDPS is an international forum for engineers and scientists from around the world to present their latest research findings in all aspects of parallel computation. In addition to technical sessions of submitted paper presentations, the meeting offers workshops, tutorials, and commercial presentations & exhibits.

IPDPS represents a unique international gathering of computer scientists from around the world. Now, more than ever, we prize this annual meeting as a testament to the strength of international cooperation in seeking to apply computer science technology to the betterment of our global village.
Topics of interest include, but are not limited to:

* Parallel and distributed algorithms, focusing on issues such as: stability, scalability, and fault-tolerance of algorithms and data structures for parallel and distributed systems, communication and synchronization protocols, network algorithms, scheduling, and load balancing.

* Applications of parallel and distributed computing, including web applications, peer-to-peer computing, cloud and grid computing, scientific applications, and mobile computing. Papers focusing on applications using novel commercial or research architectures, or discussing scalability toward the exascale level are encouraged.

* Parallel and distributed architectures, including architectures for instruction-level and thread-level parallelism; petascale and exascale systems designs; special-purpose architectures, including graphics processors, signal processors, network processors, media accelerators, and other special purpose processors and accelerators; impact of technology on architecture; network and interconnect architectures; parallel I/O and storage systems; architecture of the memory hierarchy; power-efficient architectures; dependable architectures; and performance modeling and evaluation.

* Parallel and distributed software, including parallel and multicore programming languages and compilers, runtime systems, operating systems, resource management, middleware for grids and clouds, libraries, performance modeling and evaluation, parallel programming paradigms, and programming environments and tools.

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