PPT-PBGL: A High-Performance Distributed-Memory Parallel Graph

Andrew Lumsdaine Indiana University lumsosliuedu My Goal in Life Performance with elegance Introduction Overview of our highperformance industrial strength graph library Comprehensive features. Aapo. Kyrola. Danny. Bickson. A Framework for Machine Learning and Data Mining in the Cloud . Joseph. Gonzalez. Carlos. Guestrin. Joe. Hellerstein. Big Data is Everywhere. 72 Hours . a Minute. YouTube. April 10, 2012. Parallel Graph Algorithms. Aydın . Buluç. ABuluc@lbl.gov. Lawrence Berkeley National Laboratory. Some slides from: . Kamesh. . Madduri. , John Gilbert, Daniel . Delling. . Graph Preliminaries. Improving Computer Performance. What performance translates into:. Time taken to do computation. Improving performance . → reducing time taken. What key benefits improving performance can bring:. Can solve “now-computationally-attainable” problems in . Dimension Reduction. Student: . Seung-Hee. . Bae. Advisor: . Dr. Geoffrey C. Fox. School of Informatics and Computing. Pervasive Technology Institute. Indiana University. Thesis Defense, Jan. 17, 2012. What is Multiprocessing?. Enables several programs to run concurrently. Coordinated processing of Programs by more than one processor. Use of 2 or more CPUs within a single computer system. Ability of a system to support more than one processor and to allocate tasks between them. Workshops . on Dynamic . Data Driven Applications Systems(DDDAS) In conjunction . with: 22nd . International Conference on . High. . Performance . Computing (. HiPC. ), Bengaluru. , India . 12/16/2015. William Cohen. 1. Announcements. Next Tuesday 12/8:. Presentations for 10-805 projects.. 15 minutes per project.. Final written reports due Tues 12/. 15. For exam:. S. pectral clustering will not be cov. for Billion-Scale Graph Analytics. Miraj Kheni. Authors: . Toyotaro. . Suzumura. , . Koji Ueno. ScaleGraph. : Motivations. Growing interest in the field of large-scale graph mining. Achieving high performance and low software complexity at the same time. Bickson. A Framework for Machine Learning and Data Mining in the Cloud . Joseph. Gonzalez. Carlos. Guestrin. Joe. Hellerstein. Big Data is Everywhere. 72 Hours . a Minute. YouTube. 28 . Million . Wikipedia Pages. Data in the Cloud. AFOSR FA9550-13-1-0225: Cloud-Based Perception and Control of Sensor Nets and Robot Swarms . 01/27/2016. 1. Geoffrey Fox, David . Crandall,. Supun. . Kamburugamuve. , . Jangwon. Lee, . Recall: Microprocessors are classified by how memory is organized. Tightly-coupled multiprocessor systems use the same memory. They are also referred to as . shared memory multiprocessors. .. The processors do not necessarily have to share the same block of physical memory: . Early Adopter: ASU - Intel Collaboration in Parallel and Distributed Computing Yinong Chen , Eric Kostelich , Yann -Hang Lee, Alex Mahalov , Gil Speyer, and Violet R. Syrotiuk 1 st NSF /TCPP Workshop on Parallel and Distributed Computing Education ( . with Distributed Immutable View. Rong Chen. +. , . Xin. Ding. +. , . Peng. Wang. +. , Haibo Chen. +. , . Binyu . Zang. +. and Haibing Guan. *. Institute of Parallel and Distributed Systems. +. Just a PC. Aapo Kyrölä . akyrola@cs.cmu.edu. Carlos . Guestrin. University of . Washington & CMU. Guy . Blelloch. CMU. Alex . Smola. CMU. Dave Andersen. CMU. Jure . Leskovec. Stanford. Thesis Committee:.