Archive of posts with the tag SOM

• Feb 23, 2024: Why Are My Bytecode Interpreters Slow? Hunting Truffles with VTune

  As part of our work on the AST vs. Bytecode Interpreters paper, I briefly looked at how the native code of ahead-of-time-compiled bytecode loops looks like, but except for finding much more code than what I expected, I didn’t look too closely at what was going on.

• Oct 16, 2023: Which Interpreters are Faster, AST or Bytecode?

  This post is a brief overview of our new study of abstract-syntax-tree and bytecode interpreters on top of RPython and the GraalVM metacompilation systems, which we are presenting next week at OOPSLA.

• Oct 10, 2022: The Cost of Safety in Java

  Overhead of Null Checks, Array Bounds, and Class Cast Exceptions in GraalVM Native Image

• Jul 7, 2020: Is This Noise, or Does This Mean Something? #benchmarking

  Do my performance measurements allow me to conclude anything at all?

• Jul 11, 2019: SOMns 0.7.0 Release with Extension Modules and Artifacts

  It has been a while since we put together a release for SOMns. And it has been even longer, since I last wrote about it on this blog.

• Oct 15, 2017: Debugging Concurrency Is Hard, but We Can Do Something About It!

  When we have to debug applications that use concurrency, perhaps written in Java, all we get from the debugger is a list of threads, perhaps some information about held locks, and the ability to step through each thread separately.

• Jul 5, 2017: A 10 Year Journey, Stop 5: Growing the SOM Family

• Jun 6, 2017: A 10 Year Journey, Stop 4: Concurrency and Tooling

  This post, the fourth in the series, is about my current work on concurrency and tooling. As mentioned before, I believe that there is not a single concurrency model that is suitable for all problems we might want to solve. Actually, I think, this can be stated even stronger: Not a single concurrency model is appropriate for a majority of the problems we want to solve.

• Apr 30, 2017: 10 Years of Language Implementations

  First Stop: VMs, Compilers, and Modularity

• Mar 7, 2017: SOMns 0.2 Release with CSP, STM, Threads, and Fork/Join

  Since SOMns is a pure research project, we aren’t usually doing releases for SOMns yet. However, we added many different concurrency abstractions since December and have plans for bigger changes. So, it seems like a good time to wrap up another step, and get it into a somewhat stable shape.

• Jan 10, 2017: Communicating Sequential Processes for Newspeak/SOMns

  One possible way for modeling concurrent systems is Tony Hoare’s classic approach of having isolated processes communicate via channels, which is called Communicating Sequential Processes (CSP). Today, we see the approach used for instance in Go and Clojure.

• Oct 25, 2016: Cross-Language Compiler Benchmarking: Are We Fast Yet?

  Research on programming languages is often more fun when we can use our own languages. However, for research on performance optimizations that can be a trap. In the end, we need to argue that what we did is comparable to state-of-the-art language implementations. Ideally, we are able to show that our own little language is not just a research toy, but that it is, at least performance-wise, competitive with for instance Java or JavaScript VMs.

• Oct 22, 2016: Language Research with Truffle at the SPLASH'16 Conference

  Next weekend starts one of the major conferences of the programming languages research community. The conference hosts many events including our Meta’16 workshop on Metaprogramming, SPLASH-I with research and industry talks, the Dynamic Languages Symposium, and the OOPSLA research track.

• Jan 12, 2016: Type Hierarchies and Guards in Truffle Languages

  Continuing a little bit with writing notes on Truffle and Graal, this one is based on my observations in SOMns and changes to its message dispatch mechanism. Specifically, I refactored the main message dispatch chain in SOMns. As in Self and Newspeak, all interactions with objects are message sends. Thus, field access and method invocation is essentially the same. This means that message sending is a key to good performance.

• Oct 23, 2015: JIT Data Structures, Fully Reflective VMs, and Meta-Circular Meta-Tracing

  The year leading up to SPLASH has been pretty busy. Beside my own talks on Tracing vs. Partial Evaluation and Optimizing Communicating Event-Loop Languages with Truffle, there are going to be three other presentations on work I was involved in.

• Oct 21, 2015: Optimizing Communicating Event-Loop Languages with Truffle

  The past few month, I have been busy implementing a fast actor language for the JVM. The language is essentially Newspeak with a smaller class library and without proving access to the underlying platform, which can lead to violations of the language’s guarantees.

• 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.

• 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.

• Sep 22, 2014: Are We There Yet? Simple Language-Implementation Techniques for the 21st Century

  The first results of my experiments with self-optimizing interpreters was finally published in IEEE Software. It is a brief and very high-level comparison of the Truffle approach with a classic bytecode-based interpreter on top of RPython. If you aren’t familiar with either of these approaches, the article is hopefully a good starting point. The experiments described in it use SOM, a simple Smalltalk.

• Feb 1, 2014: How to get a JIT Compiler for Free: Implementing SOM Smalltalk with RPython and Truffle

  Today at FOSDEM, I gave a brief talk on implementing SOM, a little Smalltalk, with RPython and Truffle. RPython, probably best known for the PyPy implementation, uses meta-tracing JIT compilation to make simple interpreters fast. Truffle, a research project of Oracle Lab, is an approach for building self-optimizing interpreters and in combination with Graal, it gives a JIT compiler for AST-like interpreters. In the talk, I briefly sketch both of them, without going into many details.