Very efficient sequential algorithms are not necessarily appropriate for use on massively parallel machines. The development of efficient parallel algorithms raises questions ranging from abstract parallel complexity to the effective implementation of algorithms on current architectures.
Useful algorithms are efficient and portable and perform predictably.
Load balance, scheduling, latency tolerance, data locality, and parallelism are all essential issues in the design and analysis of useful parallel algorithms. In an attempt to provide suitable abstractions for the development and analysis of highly parallel algorithms, we have been lead to ever more elaborate abstract machine models. The log P model and the theory of scalable algorithms may allow us to develop machine-independent parallel algorithm families. The workshop brings together algorithm developers from theory, combinatorics, and scientific computing. The topics will range over models, linear algebra, sorting, randomization, and graph algorithms and their analysis.