Stefan Marr

Associate Professor (Senior Lecturer)
and Royal Society Industry Fellow

Stefan Marr I am working at the School of Computing at the University of Kent. My work focuses on programming language implementation techniques, complex concurrent systems, and tooling.

Much of work revolves around making interpreters faster, detecting and preventing concurrency bugs at run time, and use modern language runtime systems to provide programmers with better tooling.

For contact details see my page at the School of Computing.

Archive of posts with the tag meta-tracing

May 14, 2017: A 10 Year Journey, Stop 3: Performance, Performance, and Metaprogramming

The third post of this series is about how I started using Truffle and Graal, pretty much 4 years ago. It might be in parts ranty, but I started using it when it was in a very early stage. So, things are a lot better today.
Oct 19, 2015: Tracing vs. Partial Evaluation: Comparing Meta-Compilation Approaches for Self-Optimizing Interpreters

Back in 2013 when looking for a way to show that my ideas on how to support concurrency in VMs are practical, I started to look into meta-compilation techniques. Truffle and RPython are the two most promising systems to build fast language implementations without having to implement a compiler on my own. While these two approaches have many similarities, from a conceptual perspective, they take two different approaches that can be seen as the opposite ends of a spectrum. So, I thought, it might be worthwhile to investigate them a little closer.
Apr 28, 2015: Zero-Overhead Metaprogramming

Runtime metaprogramming and reflection are slow. That’s a common wisdom. Unfortunately. Using refection for instance with Java’s reflection API, its dynamic proxies, Ruby’s #send or #method_missing, PHP’s magic methods such as __call, Python’s __getattr__, C#’s DynamicObjects, or really any metaprogramming abstraction in modern languages unfortunately comes at a price. The fewest language implementations optimize these operations. For instance, on Java’s HotSpot VM, reflective method invocation and dynamic proxies have an overhead of 6-7x compared to direct operations.
Jan 31, 2015: FOSDEM 2015: Building High-Performance Language Implementations With Low Effort

Today, I gave a talk on implementing languages based on the ideas behind RPython and Truffle at FOSDEM on the main track. Please find abstract and slides below.
Nov 19, 2014: SOM Performance Numbers

Today, I got a few more benchmarks running to get a better idea of where RTruffleSOM and TruffleSOM stand in terms of their absolute performance.