Videos tagged with Distributed Programming

Summary Ralph Johnson and Joe Armstrong discuss their ideas about parallel programming - whether shared memory is harmful, the place of message passing, fault tolerance, the importance of protocols and more. Bio Ralph Johnson, one of the GoF behind the Design Patterns book and behind the creation of the original Refactoring Browser, is now at the CS dept. at the UIUC and the leader of UIUC Patt...

Summary In this presentation from QCon London 2009, Steve Vinoski discusses what RPC means, the origin and history of RPC, RFC 707, the origins of Distributed Computing Environment (DCE), the growth of the Internet, standardization, distributed objects, CORBA, DCOM, Java, SOAP, WS-*, the fundamental flaws in RPC, REST properties and constraints, REST vs RPC philosophy, Erlang reliability and co...

Building multiple applications that all need to share data and other information between can be a daunting and challenging task. Mark will help to demystify the use of Ruby systems such as Rinda and DRb and show you how they can be used to link applications together. Through the development of the Mack framework and its use in building Helium.com, Mark will share the highlights and the pitfalls...

Server-side data processing can be difficult to get right with requirements like fault tolerance, consistency or real time response. We'll look at some generic characteristics of all distributed processing problems, examine open source tools which you can use to solve distributed computing problems and review a few Ruby examples to see their strengths and weaknesses. About Mike Perham Mike is a...

Lecture 5: Parallel Graph Algorithms with MapReduce. See Google: Cluster Computing and MapReduce for slides and other resources.

Lecture 4: Clustering Algorithms with MapReduce. See Google: Cluster Computing and MapReduce for slides and other resources.

Lecture 3: The Google File System. See Google: Cluster Computing and MapReduce for slides and other resources.

Lecture 2: The MapReduce programming model. See Google: Cluster Computing and MapReduce for slides and other resources.

Lecture 1 in a five part series introducing mapreduce and cluster computing. See Google: Cluster Computing and MapReduce for slides and other resources.

The General Systems Architecture Since the summer of 2007, I have been assembling my thoughts and programs on systems, machine learning, distributed programming, and problem solving in general. The meaning of these efforts, for me, is to 1) learn what I can about problem solving, 2) apply my education in formal systems, and 3) use these formal systems in solving real-world problems. What this l...