Gil Tene examines the core issues that have historically kept Java environments from performing well in low latency environments and how it can perform now without trade-offs and compromises.
Todd Montgomery proposes a new approach to marshalling in Java using FIX/SBE, new marshalling API approaches, and the extensive application of mechanical sympathy to this problem domain.
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.
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.
Keith Adams shares HHVM insights showing how a system can become very performant if it is well tuned.
Michael Kopp explains how to run performance code at scale with Hadoop and how to analyze and optimize Hadoop jobs.
Charlie Hunt and Monica Beckwith describe the operational basics of G1 and how to tune it, along with tips on what to expect when migrating from Parallel GC or CMS to G1 GC.
Charlie Hunt presents the fundamentals of JVM tuning and provides advice for developers on writing a Java application that performs well at runtime.
Gil Tene discusses JVM observation-based runtime optimizations, ordering and memory model rules, basics GC functions, memory management, and JVM mechanics.