Timo Bingmann from KIT will be visiting from October 10 to October 11 and give a talk on “Thrill: High-Performance Algorithmic Distributed Batch Data Processing with C++” in OH14 R202 on October 10 at 14:00.

Abstract - We present on-going work on a new distributed Big Data processing framework called Thrill. It is a C++ framework consisting of a set of basic scalable algorithmic primitives like mapping, reducing, sorting, merging, joining, and additional MPI-like collectives. This set of primitives goes beyond traditional Map/Reduce and can be combined into larger more complex algorithms, such as WordCount, PageRank, k-means clustering, and suffix sorting. These complex algorithms can then be run on very large inputs using a distributed computing cluster. Among the main design goals of Thrill is to lose very little performance when composing primitives such that small data types are well supported. Thrill thus raises the questions of a) how to design algorithms using the scalable primitives, b) whether additional primitives should be added, and c) if one can improve the existing ones using new ideas to reduce communication volume and how they can be scaled to very large cluster sizes.