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.
Charles Fry presents MapMaker, an in-memory caching solution on the JVM, discussing its API and implementation evolution along with internal details.
Cyprien Noel discusses distributed transactional memories along with ObjectFabric, a Java server based on eXtensible Software Transactional Memory, an OS library for concurrent and distributed apps.
Jonas Bonér introduces Akka, a JVM platform that wants to address the complex problems of concurrency, scalability and fault tolerance using Actors, STM and self-healing from crashes.
Jamie Ridgway explains what actors are, why we need them, what they are helpful for, the languages built around this programming paradigm, along with some demos showing actor-based apps.
Ulf Wiger advocates for a programming model change based on the actor model which more accurately reflects old human concurrency patterns that we have used in our daily lives for thousands of years.
Stuart Halloway discusses how we use a total control time model, proposing a different one that represents the world more accurately helping to solve some of the concurrency and parallelism problems.
Dale Schumacher explains the actor concept and how it helps us build a computational model resembling the reality around us more accurately than the object-oriented model.
David Syer and Mark Fisher on using Spring to develop concurrent and distributed apps, covering topics such as: asynchronous execution, intra-process, inter-process and inter-JVM communication.
Kresten Krab Thorup emphasizes existing problems with the Java concurrency model, explaining when to use Erjang, a JVM-based Erlang VM, built around the process and actor concepts.
Martin Thompson and Michael Barker talk about building a HPC financial system handling over 100K tps at less than 1ms latency by having a new approach to infrastructure and software. Some of the tips include: understand the platform, model the domain, create a clear separation of concerns, choose data structures wisely, and run business logic on a single thread.