# 263-4505-00L Algorithms for Large-Scale Graph Processing

Semester | Autumn Semester 2018 |

Lecturers | M. Ghaffari |

Periodicity | yearly recurring course |

Language of instruction | English |

Comment | The deadline for deregistering expires at the end of the second week of the semester. Students who are still registered after that date, but do not attend the seminar, will officially fail the seminar. |

Abstract | This is a theory seminar, where we present and discuss recent algorithmic developments for processing large-scale graphs. In particular, we focus on Massively Parallel Computation (MPC) algorithms. MPC is a clean and general theoretical framework that captures the essential aspects of computational problems in large-scale processing settings such as MapReduce, Hadoop, Spark, Dryad, etc. |

Objective | This seminar familiarizes students with foundational aspects of large-scale graph processing, and especially the related algorithmic tools and techniques. In particular, we discuss recent developments in the area of Massively Parallel Computation. This is a mathematical abstraction of practical large-scale processing settings such as MapReduce, and it has been receiving significant attention over the past few years. The seminar assumes no particular familiarity with parallel computation. However, we expect that all the students are comfortable with basics of algorithms design and analysis, as well as probability theory. In the course of the seminar, the students learn how to structure a scientific presentation (in English) which covers the key ideas of a paper, while omitting the less significant details. |

Content | The seminar will cover a number of the recent papers on Massively Parallel Computation. As mentioned above, no familiarity with parallel computation is needed and all the relevant background information will be explain by the instructor in the first lecture. |

Literature | The papers will be presented in the first session of the seminar. |