I came across the issue of how to teach a trainee how to write a parallel finite-difference time-domain (FDTD) method. There are a lot of books on the FDTD, but only a few on parallel ones. So I’ve decided to go for this book, knowing that some chapters won’t apply to our job (wave equations). My goal was to seek a book that would explain the basics of my issues.

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For each algorithm and program, there are architectures that are better than others. Some computation may need a lot of FLOPS, but FLOPS are not the only thing to consider. Communication and memory bandwidth and latency are as important as computational power, specially since memory speed and CPU speed are decoupled.

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It has been a while since my last post on manifold learning, and I still have some things to speak about (unfortunately, it will be the end post of the dimensionality reduction series on my blog, as my current job is not about this anymore). After the multidimensional regression, it is possible to use it to project new samples on the modelized manifold, and to classify data.

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I’m a very curious guy, and I wanted to know who is looking at my blog, and for my wife, who is interested by what is viewed on her decoration site (in construction as she wants to make a living of decoration advice). With my hosting service, I have access to Awstats, but Google Analytics seems better suited for data analysis. And this is what this book explains.

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I chose Eclipse as my new Linux IDE, instead of Konqueror + KWrite. The purpose was to be able to launch a SCons build from the IDE, get the errors in a panel and double-clicking on one of them would direct me to the location of the error.

So Eclipse seemed to fit my needs:

  • Plug-ins to add the support of various languages
  • Support of different construction tools
  • Support from the main C/C++/Fortran compiler developers (GNU, Intel, IBM, …)

So I will know show you two ways of enabling SCons support for Eclipse.

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I had this discussion with one of my Ph.D. advisors some months ago when we talked about correctly using the computers we had then (dual cores), and I had almost the same one in my new job here: applied maths (finite differences, signal processing, …) graduate students are not taught how to use current computers, so how could they develop an HPC program correctly?

I think it goes even further than that, and it will be a part of this post. What I see is that trainees and newly-hired people (to some extent myself included) lack a lot of basic Computer Science knowledge, and even IT knowledge.

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The book description was really appetizing: Machine Learning applied to the Internet, so it should be easy to understand, and Python as the mean to compute. Unfortunately, contrary to what I saw in different reviews, I was not pleased with the book, and here is why.

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This is the first time I will review a book on something I’m not familiar with at all. I’ve started now for more than two months a new job related to geophysics, and I had to catch up with my colleagues.
I’ve stopped studying geology ten years ago, so this is a review from someone who is learning geophysics and who wants to have a quick and global look on the different fields of geophysics.

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