Zach Allaun shows how to build a functional and persistent vector, hash map, and set on top of the same data structure, and how to optimize the code for performance.
Martin Thompson discusses Java, concurrency, operating systems, and functional programming in the context of designing and testing high-performance systems.
Martin Thompson overviews Java's evolution, comparing it with C++'s, discussing the challenges of pushing the performance limits.
Matt West explains how to use technologies like CloudStack, Beanstalk, Gearman, mod_gearman, Nagios, nagconf and other tools to monitor large web applications at scale deployed in the zCloud.
Leo Meyerovich introduces Superconductor, a browser-based language for massive interactive visualizations using end-to-end parallel DSLs and a synthesis DSL for parallel layout.
Daniel Cukier shares insight in using cloud services to scale web applications, dealing with load balancing, session sharing, email, asynchronous processing, logging, monitoring, CD, RUM, etc.
Maxime Chevalier-Boisvert discusses making dynamic languages faster providing various examples of optimizations: SmallTalk, LISP machine, Google V8 and others.
Alex Gaynor explains how he solved the usual Ruby VM speed problems with Topaz, a high performance VM built on the same technologies that power PyPy.
Craig Smith, Renee Troughton discuss improving visual management: different types of story walls, ways to visualize the product backlog, the important of queue columns and WIP limitation, etc.
Keith Adams shares HHVM insights showing how a system can become very performant if it is well tuned.
Ariel Tseitlin discusses Netflix' failure-based suite of tools, collectively called the Simian Army, used to improve resiliency and maintain the cloud environment.
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