Abstractions Without Regret with GraalVM

Java Language

Performance-aware code often sacrifices elegance and readability for being fast. Previously, to get the best performance developers often had to manually tweak the code to follow certain patterns known to run faster. Nowadays we have better compilers which often don't require such efforts and allow one to write readable code without sacrificing performance. In this session, we discuss how to write Java code without worrying about performance regressions very much. We'll look at the typical code patterns used for writing high-performance Java, refactor them into an easier maintainable, better-looking code without losing performance. You'll learn more about the GraalVM's compiler and how it operates, which optimizations help the most and how to make use of GraalVM in your projects


Oleg Ĺ elajev


Hello there! Oleg is a friendly neighborhood developer advocate for @GraalVM at OracleLabs, Oracle. Loves all languages. Helps @virtualJUG, @GDGTartu. In 2017 became a Java Champion.

Vojin Jovanovic

Oracle Labs

Vojin believes that programs can be described in an abstract way and at the same time be executed as quickly as their manually optimized counterparts. To this end, he is working in Oracle Labs to improve the compilation of multilingual programs. Before joining Oracle, Vojin received his Ph.D. in the Scala laboratory at the Swiss Federal Institute of Technology in Lausanne (EPFL), where he developed a platform for simply adding domain-specific optimizations to existing Scala libraries.

Thomas Wuerthinger

Oracle Labs

Thomas Wuerthinger is a Senior Research Director at Oracle Labs leading the GraalVM project with teams implementing programming languages including Java, JavaScript, Ruby, Python, and R. He is the architect of the GraalVM compiler and the Truffle self-optimizing runtime system. Previously, he worked on the Crankshaft optimizing compiler of V8 at Google, and the Maxine research virtual machine at Sun Microsystems. He received a PhD degree from JKU Linz for his research about dynamic code evolution.

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