SCDSource ran a short but good article summarizing a few DAC talks that I would liked to attend. it mostly about the experience of long-term parallel programming research David Bailey in presenting results in the field…
Past Tuesday, I attended the Freescale Design With Freescale (DWF) one-day technology event in Kista, Stockholm. This is a small-scale version of the big Freescale Technology Forum, and featured four tracks of talks running from the morning into the afternoon. All very technical, aimed at designing engineers.
My post on SiCS multicore, as well as the SiCS multicore day itself, put a renewed spotlight on the GPGPU phenomenon. I have been following this at a distance, since it does not feel very applicable to neither my job of running Simics, nor do I see such processors appear in any customer applications. Still, I think it is worth thinking about what a GPGPU really is, at a high level.
Last Friday, I attended this year’s edition of the SiCS Multicore Day. It was smaller in scale than last year, being only a single day rather than two days. The program was very high quality nevertheless, with keynote talks from Hazim Shafi of Microsoft, Richard Kaufmann of HP, and Anders Landin of Sun. Additionally, there was a mid-day three-track session with research and industry talks from the Swedish multicore community. Continue reading “SiCS Multicore Day 2009”
Freescale has now released the collected, updated, and restyled book version of the article series on embedded multicore that I wrote last year together with Patrik Strömblad of Enea, and Jonas Svennebring, and John Logan of Freescale. The book covers the basics of multicore software and hardware, as well as operating systems issues and virtual platforms. Obviously, the virtual platform part was my contribution.
In a post from late June, Jeff Atwood at Coding Horror discusses the horrible cost of a large HP server (scaling up to 32 processor cores in eight AMD x86 sockets), compared to a bunch of simple single-socket basic servers. There are some interesting notes on relative costs of small-and-simple servers, including things like administration and power. There is an undercurrent to the post and the comments that the big HP machine is “overpriced”. I don’t think it is. If you have ever had Erik Hagersten as a teacher in computer architecture, you will know why.
About two months ago, Cavium Networks launched their second generation of Octeon chips, the Octeon II. The most obvious difference to the previous generation (Octeon, Octeon Plus) is a new MIPS64 core with much better support for hypervisors and virtualization. There are some other interesting aspects to this chip, though.
Last year in a blog post on video encoding for the iPod Nano, I complained about the lack of performance on my old Athlon. A bit later, I noted that (obviously) video encoding is a good example of an application that can take advantage of parallelism. Yesterday I put these two topics together in a practical test. And it worked nicely enough.
Yes, when does hardware acceleration make sense in networking? Hardware acceleration in the common sense of “TCP offload”. This question was answered by a very nicely reasoned “no” in an article by Mike Odell in ACM Queue called “Network Front-End Processors, Yet Again“.
The EETimes article Multicore CPUs face slow road in comms piqued my interest. There is an interesting chart in there about just how slow more-than-one-core processors will be in penetrating a vaguely defined “comms” market place. I can believe that, but I think their comments on the PowerQUICC series require some commentary…
A common question from simulation users to us simulation providers is “can I simulate a machine with N cores”, where N is “large”. As if running lots of cores was a simulation system or even a hardware problem. In almost all cases, the problem is with software. Creating an arbitrary configuration in a virtual platform is easy. Creating a software stack for that arbitrary platform is a lot harder, since an SMP software stack needs to understand about the cores and how they communicate.
Essentially, what you need is a hardware design that has addressing room for lots of cores, and a software stack that is capable of using lots of cores — even if such configurations do not exist in hardware. Unfortunately, since software is normally written to run on real existing machines, there tends to be unexpected limitations even where scalability should be feasible “in principle”.
Here is the story of how I convinced Linux to handle more than two cores in a virtual MPC8641D machine.
The best way to learn something is to try, fail, and then try again. That is how I just learned the basics of multiprocessor interrupt management. For an educational setup, I have been creating a purely virtual virtual platform from scratch. This setup contains a large number of processors with local memory, and then a global shared memory, as well as a means for the processors to interrupt each other in order to notify about the presence of a message or synchronize in general. Getting this really right turned out to be not so easy.
Jack Ganssle wrote a column about the failure of multicore to scale, based on an article in IEEE Spectrum. He makes the following claim:
Now a study in IEEE Spectrum shows that even for the classic embarrassingly parallel problems like weather simulations multicore offers little benefit. The curve in that article is priceless. As the number of cores grow from two to 64 performance plummets by a factor of five. Additional processors nullify each other.
Call it the Nulticore Effect.
I keep looking out for interesting examples of parallel software, and there is constant trickle of these. This past week I spotted a couple of new ones in the EDA field: SPICE simulation and chip timing analysis.