April 8th 2014

Announcement: Audio TK 0.1.0

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A long time ago, I started implementing audio filters with a Qt GUI. I also started other pet projects in the same area, but I didn’t have a proper audio support library in C++ for that. Also Qt plugins are no longer an option (for me), I still hope to implement new filters in the future.

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March 27th 2014

On the importance of not reinventing the wheel in distributed applications

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Sometimes, it’s so easy to rewrite some existing code because it doesn’t fit exactly your bill.

I just so the example with an All To All communication that was written by hand. The goal was to share how many elements would be sent from one MPI process to another, and these elements were stored on one process in different structure instances, one for each MPI process. So in the end, you had n structures on each of the n MPI processes.

The MPI_Alltoall cannot map directly to this scattered structure, so it sounds fair to assume that using MPI_Isend and MPI_Irecv would be simpler to implement. The issue is that this pattern uses buffers on each process for each other process it will send values to or receive values from. A lot of MPI library allocate their buffer when needed, but will never let go of the memory until the end. So you end up with a memory consumption that doesn’t scale. In my case, when using more than 1000 cores, the MPI library uses more than 1GB per MPI process when it hits these calls, just for these additional hidden buffers. This is just no manageable.

Now, if you use MPI_Alltoall, two things happen:

  • there are no additional buffer allocated, so this scales nicely when you increase the number of cores
  • it is actually faster than your custom implementation

Now with MPI 3 standard having non-blocking collective operations, there is absolutely no reason to try to outsmart the library when you need a collective operation. It has heuristics when it knows that it is doing a collective call, so let them work. You won’t be smarter if you try, but you will if you use them.

In my case, the code to retrieve all values and store them in an intermediate buffer was smaller that the one with the Isend/Irecv.

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February 18th 2014

Book review: Learning scikit-learn – Machine Learning in Python

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It seems that Packt Publishing is on a publishing spree on Machine Learning in Python. After Building Machine Learning Systems In Python for which I was technical reviewer, Packt published Learning Scikit-Learn In Python last November.

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January 7th 2014

Book review: Boost.Asio C++ Network Programming

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I started using Boost.Asio years ago for my professional occupation. I remember difficult hours trying to understand its help and its tutorials. Would that have been different with the book?

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September 4th 2013

Book: Building Machine Learning Systems in Python

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I recently had the opportunity to be a technical reviewer for the new Building Machine Learning Systems in Python. As I took part in the book, I won’t write a review like what I did for other books.

First, I have to say that I was impressed by the quality of the content. Although I had some things that I thought were not excellent (I still need to check how my reviews changed the book), it’s the best book I’ve read from Packt so far. It has a good balance between code and comprehension, which is an equilibrium that is rarely achieved.

I don’t think it is possible to write a better book on Machine Learning in Python, unless the ecosystem evolves with new algorithms. Which it will, and it will mean a new edition of the book! Neat!

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August 20th 2013

Book review: The Cathedral and the Bazaar

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Open Source software seems for the young generation as sure as the sun rises. And even if I witnessed the emergence of Open Source, I more often than not forget that there was a time when Linux didn’t exist. This recent history brought us a lot, but we may only have handpicked some of this revolution’s fruit. Eric Raymond is one of the guys behind this revolution, and he took some time to think about the changes it brought.

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June 13th 2013

Book review: Numpy Beginner’s Guide

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I had the opportunity from Packt Publishing to review the second edition of Numpy Beginner’s Guide. Many thanks to the publisher for this and let’s go to the review.

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May 11th 2013

Annoucement: scikits.optimization 0.3

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I’m please to announce a new version for scikits.optimization. The main focus of this iteration was to finish usual unconstrained optimization algorithms.

Changelog

  • Fixes on the Simplex state implementation
  • Added several Quasi-Newton steps (BFGS, rank 1 update…)

The scikit can be installed with pip/easy_install or downloaded from PyPI

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May 2nd 2013

Comparison of optimization algorithms

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In the next version of scikits.optimization, I’ve added some Quasi-Newton steps. Before this version is released, I thought I would compare several methods of optimizing the Rosenbrock function.
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January 22nd 2013

Book review: Numpy Cookbook

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I had the opportunity from Packt Publishing to review Numpy Cookbook. Many thanks to the publisher for this and let’s go to the review.

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