Armin Rigo

Armin Rigo is one of the founders and lead developers of the PyPy project which began in 2003. He has taken part in all areas, from the Python language definition to the RPython translation framework, including the garbage collector, the tracing just-in-time compiler, and now the Software Transactional Memory part.

Software Transactional Memory with PyPy

PyPy is a fast alternative Python implementation. Software Transactional Memory is a current academic research topic. Put the two together --brew for a couple of years-- and we get a version of PyPy that runs on multiple cores, without the infamous Global Interpreter Lock (GIL). It has been freshly released in beta, including integration with the Just-in-Time compiler.

But its point is not only of being "GIL-less": it can also give the illusion of single-threaded programming. I will give examples of what exactly I mean by that. Starting from the usual explicitly multithreaded demos, I will move to other examples where the actual threads are hidden from the programmer. I will explain how the core of async libraries (Twisted, Tornado, gevent, ...) can be modified to use multiples threads, without exposing any concurrency issues to the user of the library --- existing Twisted/etc. programs still run correctly without change. (They may need a few small changes to enable parallelism.)

I will also give an overview of how things work under the cover: the 10000-feet view is to internally create copies of objects and write changes into these copies. This allows the originals to continue being used by other threads.