Chris Newland discusses performance-boosting techniques used by the JVM’s JIT and introduces JITWatch, a tool helping to get the best JVM performance for a code.
Ashley Puls explains what happens to bytecode inside the JVM. It begins with an overview of the Just In Time (JIT) compiler and discusses JIT optimizations such as method inlining and loop unrolling.
Gil Tene provides an overview of JIT compiler optimization techniques and their impact on common market-open slowdown scenarios.
Maxime Chevalier-Boisvert introduces adaptive compilation strategies aiming to fulfill the seemingly conflicting goals of producing more optimal machine code while reducing compilation time.
Eddy Bruel details how objects are implemented internally in SpiderMonkey as shape trees and slot vectors to minimize the memory footprint and obtain better JIT optimization with inline caching.
Limin Fu introduces Dao, a lightweight and optionally typed programming language having a LLVM-based JIT compiler optimized for numeric computation, and a Clang-based tool generating C/C++ bindings.
Charlie Hunt explains what can be done to lower the latency introduced by the Java GC and JIT, including coding tips, and introducing tools for tuning the performance of Java applications.