Handling massive data often requires use of parallel or distributed algorithms. Current technology offers many ways of implementing such algorithms, e.g. GPUs, multi-core CPUs, the map-reduce framework, etc. Each technology has its strengths, but also comes with some limitations.
The goal of the summer school is to provide an in-depth introduction to some of the models of modern parallel and distributed technology, and the key techniques used to design efficient algorithms in these models. A number of open problems will also be highlighted.
The goal of the summer school is to provide an in-depth introduction to some of the models of modern parallel and distributed technology, and the key techniques used to design efficient algorithms in these models. A number of open problems will also be highlighted.
The school will be taught by experts in the area of
parallel and distributed algorithms.
The summer school will take place on August 20-23, 2012 at Center for Massive Data Algorithmics (MADALGO) in the Department of Computer Science, Aarhus University, Denmark.
The school is targeted at graduate students, as well as researchers interested in an in-depth introduction to Algorithms for Modern parallel and Distributed Models.
The capacity of the summer school is limited. Prospective participants should register as soon as possible. Registering graduate students must also have their supervisor send a letter confirming their graduate student status directly to madalgo@madalgo.au.dk; the subject line of the email should be ''student_<last name>/SS_2012/confirming'. Registration is on a first-come-first-serve basis and will close on Friday July 13, 2012.
Registration is free; handouts, coffee breaks, lunches and a dinner will be provided by MADALGO and Aarhus University.