Cliff Click explains 0xdata's H20, a clustering and in-memory math and statistics solution (available for Hadoop and standalone), writing H20's memory representation and compression in Java, low latency Java vs GCs, and much more.
Todd Montgomery talks about improving serialization times and throughput can by understanding how your computer processes and stores data. With this new understanding, architects and developers can build their own protocols to efficiently transmit data. Todd's advice sheds new light on why software developers choose their current serialization and marshaling techniques and how they can improve.
Jim Hirschauer describes the application monitoring tool landscape, KPIs and metrics to consider when monitoring, and compares monitoring traditional vs. cloud-based applications. He talks about performance considerations when instrumenting code, how organizations can be 'Smarter' about their Big Data, and looks at what's new in AppDynamics 3.7.
John Nolan shows the state of hardware acceleration with GPUs and FPGAs, why it's hard to write efficient code for them, and why to favor polymorphism over if statements for performance.
Cliff Click discusses the Pauseless GC algorithm and how Azul's Zing implements it on plain x86 CPUs. Also: what keeps dynamic languages slow on the JVM, invokedynamic, concurrency and much more.
Jon Travis explains Hyperic HQU as well as Spring Insight, a tool for monitoring Java web apps, how it uses AspectJ to instrument Java code, how to use it to find performance problems and more.
Chris Wanstrath discusses the state of GitHub's architecture, how GitHub is used and its impact on open source collaboration.
Heroku's Adam Wiggins talks about how Heroku, Add-Ons, Ruby, and how Heroku manages to work around Ruby's inefficiencies using Erlang and other languages.