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. Hardware Parallelism. Computing: execute instructions that operate on data.. Flynn’s . taxonomy (Michael Flynn, 1967) classifies computer architectures based on the number of instructions that can be executed and how they operate on data.. 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. Copyright © 2014 by ScaleOut Software, Inc.. Portland Big Data Users Group. October 23, 2014. Bill . Bain, CEO . (. wbain@scaleoutsoftware.com). What Is Operational Intelligence?. Example: Tracking Cable Viewers. 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. 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. 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. 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, . : . A Fault-Tolerant Abstraction for In-Memory Cluster Computing. Matei. . Zaharia. , . Mosharaf. Chowdhury, . Tathagata. Das, . Ankur. Dave, Justin Ma, Murphy McCauley, Michael J. Franklin, Scott . Parallel Processing, Multicores. Prof. Gennady . Pekhimenko. University of Toronto. Fall 2017. The content of this lecture is adapted from the lectures of . Onur. . Mutlu. @ CMU. Summary . Parallelism. Mahesh Ravishankar. 1. , John Eisenlohr. 1. , . Louis-Noël Pouchet. 1,3. , J. Ramanujam. 2. , . Atanas. Rountev. 1. , P. Sadayappan. 1. 1. Dept. of Computer Science & Engineering. The Ohio State University. 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 ( We will Study …. Concurrency . Parallelism. Distributed computing. Evaluation. Assignments 40%, . Minor-1 15%, . Minor-2 15%, . Major 30%. Plagiarism is unacceptable. Offenders will be . penalized by a failing. Adeetya's Kitchen & Furniture in Pune offers a selection of top-quality kitchen trolleys to maximize storage space and improve the functionality of any kitchen. https://adeetyas.com/high-quality-kitchen-trolleys-in-pune.php