Matthieu Brucher's blog

Due to the end of the free lunch, manufacturers started to provide differents processing units and developers started to go parallel. It’s kind of back to the future, as accelerators existed before today (the x87 FPU started as a coprocessor, for instance). If those accelerators were integrated into the CPU, their instruction set were also.

Today’s accelerators are not there yet. The tools are not ready yet (code translators) and usual programming practices may not be adequate. All the ecosystem will evolve, accelerators will change (GPUs are the main trend, but they will be different in a few years), so what you will do today needs to be shaped with these changes in mind. How is it possible to do so? Is it even possible?
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Free lunch is over, it’s time to go concurrent. The Art of Concurrency addresses the need for a workflow to develop concurrent/parallel applications.
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I’ve played a little bit with Intel Parallel Studio. Let’s say it has been a pleasant trip out in the wildness of multithreaded applications.

Intel Parallel Studio is a set of tools geared toward multithreaded applications. It consists of three Visual Studio plugins (so you need a fully-fledged Visual Studio, not an Express edition):

• Parallel Inspector for memory analysis
• Parallel Amplifier for thread behavior and concurrency
• Parallel Composer for parallel debugging

This is an update of the review I’ve done for the beta version. Since this first review, I’ve tried the official first version.

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(5 votes, average: 5.00 out of 5)

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Since this post, Intel has officially released Parallel Studio. This is why I’ve published a new, up-to-date review here.

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Some months ago, I’ve decided to dig into raytracing, and more exactly interactive raytracing. So I’ve started writting my own library, based on several publications.
nVidia announced recently its own framework, Intel wants also to do raytracing on Larrabee, it is the current trend.
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Profiling comes in three different flaviors. The first is emulation, where a processor behavior is emulated, the second is sampling, where at regular intervals, the profiler samples the status of a program, and fianlly instrulentation, where the profiler gets information when a subroutine is called and when it returns. As with the Heisenberg uncertainty, profiling changes the exact behavior of your program. This is something you have to remember when analyzing a profile.

Valgrind is an Open Source emulation profiler. It is freely available on standard Linux platforms. As it is an emulation, it is far slower than the actual program. This means that the I/O are underestimated. The advantage is that you can have every detail on the memory behavior (cache misses for instance). Valgrind does not emulate all processors, but you can tweak it to approach your own one.
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Some months ago, I had a TotalView tutorial, thanks to my job. Now, I’ve actually used it to debug one of my parallel applications and I would like to share my experience with fantastic tool.
First TotalView is not only a parallel debugger available on several Linux and Unix platforms. It also is a memory checker (MemoryScape and the TotalView plugin) as well as a reverse debugger, that is, you can roll back the execution of a program, even after it crashed (where it would be useless with a standard debugger like GDB).
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As I have to parellize some programs developed in my new lab, I monitor CPU usage during thier execution. I do not usually need MPI to optimize them (although sometimes it is needed), only OpenMP, which means I can track /proc/ to get CPU and instantaneously memory usages.

So I wrote a small script that can be used by anyone for this purpose. I’ll explain how it works now.
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(4 votes, average: 4.75 out of 5)

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After some general books on grid computation, I needed to change the subject of my readings a little bit. As Intel Threading Building Blocks always intrigued me, I chose the associated book.
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