Peter Van Roy discusses solving concurrency issues with deterministic concurrency using Ozma, an extension of the Scala language employing the Oz deterministic dataflow concepts.
Trisha Gee introduces Disruptor, a concurrency framework based on a data structure – a ring buffer – that enables fast message passing in a parallel environment.
Jeff Lindsay discusses creating distributed and concurrent systems using ZeroMQ – a lightweight message queue-, and gevent – a coroutine-based networking library.
Steve Vinoski believes that actor-oriented languages such as Erlang are better prepared for the challenges of the future: cloud, multicore, high availability and fault tolerance.
Joshua Bloch, Robert Bocchino, Sebastian Burckhardt, Hassan Chafi, Russ Cox, Benedict Gaster, Guy Steele, David Ungar, and Tucker Taft discuss the future of computing in a multicore world.
Martin Thompson and Michael Barker explain how Intel x86_64 processors and their memory model work along with low-level techniques that help creating lock-free software.
Ivan Sutherland elaborates on the idea of a “prison” defined by sequential computers that work with sequential character strings making communication expensive and obstructing concurrency.
Dierk König introduces GPars, Groovy’s library for concurrent programming, explaining a simpler and less error-prone way to use fork/join, map/reduce, actors, and dataflow in Java and Groovy.
Josh Suereth presents the new features available in Akka 2.0: clustered actors, including stateless and stateful ones, replication and the Cluster API.
Bob Ippolito explains how to solve concurrent update conflicts with Statebox, an open source library for automatic conflict resolution, running on top of Riak.
Dave Farley and Martin Thompson discuss solutions for doing low-latency high throughput transactions based on the Disruptor concurrency pattern.
Dale Schumacher presents several patterns of actor interaction that can be used in collaborative programs written in any language.