Hi, this might be of interest for people who are look for practical information on doing real-time signal processing, possibly using multiple CPUs, and wonder whether it's possible to use Python for audio-type worst case latencies (around 25 ms). I've done that in my PhD work, both with real-time requirements on dual-CPU 64 bit platforms, and with very complex algorithms running on multicomputers. What I found is that numerical Python is a great environment for such tasks. I've used it as well for massively parallel algorithms (particle filters) for simulations of auditory scene analysis. What is a very special advantage is that if you get faster hardware, you can simply copy your algorithms to a new system and compile - even if it has a different CPU! I've documented the approach in my PhD thesis, in Appendix A, starting with some thoughts on developments in signal processing in the last years. This piece is available online. Title and abstract of that chapter read as follows: -------------------------------------------------------------- A real-time, script-based, multiprocessing Solution for experimental Development of Signal Processing Algorithms Evaluation of audio signal processing algorithms on real-time platforms has unique advantages. However, such environments also used to have the disadvantage of requiring expensive hardware, and tedious work to set them up, while providing only a short useful life. This report proposes to exploit advances in hardware and software development by integrating real-time processing with script-based explorative development and use of multiprocessing hardware. The concept was implemented based on standard hardware and open source software, and its realization and characteristics are presented here. Applications of the system for algorithm development and evaluation are described briefly. -------------------------------------------------------------- Here is the download link for several paper formats: http://medi.uni-oldenburg.de/members/jnix/index.html#thesisdownload Alternatively, for ISO A4 paper, use one of these two URLs: http://medi.uni-oldenburg.de/download/paper/Nix,Johannes-PhDthesis-2005-ISO-... http://docserver.bis.uni-oldenburg.de/publikationen/dissertation/2006/nixloc... (for that paper size, this are the PDF pages 155 - 163) If you want to cite the chapter, e.g. when doing advocacy for scientific computing using SciPy, please do this as follows: Nix, Johannes (2005), "A real-time, script-based, multiprocessing Solution for experimental Development of Signal Processing Algorithms", in: Localization and Separation of Concurrent Talkers Based on Principles of Auditory Scene Analysis and Multi-Dimensional Statistical Methods, Appendix A, Ph.D. thesis, Universität Oldenburg, Germany. Also, I am currently looking for interesting further work opportunities or contracts in the domain of scientific computing and statistical estimation. If you know some interesting position, don't hesistate to contact me. Kind regards, Johannes -- Dr. Johannes Nix Energy & Meteo Systems GmbH Research & Development of windpower forecasts Bremen, Germany Phone: + 49 421 8963914