Probably thanks to the yearly Mobile World Congress, there have been a slew of recent announcements of mobile application processors recently. Everything is ARM-based, but show quite some variety in the CPU core configurations used. Indeed, I think this variety has something to say on the general state of multicore.
Category Archives: Parallel Computing
There is a new post at my Wind River blog, telling the story of how some of the Simics developers used Simics itself to debug an intermittent Simics program crash caused by a timing-sensitive race condition.
Running Simics on itself is pretty cool, and shows the power of the simulator and its applicability even to really complex software.
A few years ago, I built a demo on Simics that used a hacked Freescale MPC8641D target that was forced to scale from 1 to 8 cores. Some interesting experiements could be made using this target, and it was nicely scalable for its time. However, I always wanted to have something just a bit bigger. Say 20 cores, or 100. Just to see what would happen. Finally, I got it.
The Simics QSP target that we quietly launched earlier this Summer is such a scalable target. As discussed in a blog post describing the architecture, it is designed to scale to 128 cores currently. Using this ability, I repeated my old experiments, but trying very large threads counts and target core counts. The results show clearly that the way that I coded my parallel computation program was pretty bad, and I really would like to try to rewrite it using some more modern threading library. All I need is time and a way to cross-compile Wool…
Anyway, the new blog post is here.
When IBM moved their mainframe systems (the S/360 family that is today called System Z) from BiCMOS to mainstream CMOS in 1994, the net result was a severe loss in clock frequency and thus single-processor performance. Still, the move had to be done, since CMOS would scale much better into the future. As a result, IBM introduced additional parallelism to the system in order to maintain performance parity. Parallelism as a patch, essentially.
I was recently pointed to a 2011 SPLASH presentation by David Ungar, an IBM researcher working on parallel programming for manycore systems. In particular, in a project called Renaissance, run together with the Vrije Universiteit Brussels in Belgium (VUB) and Portland State University in the US. The title of the presentation is “Everything You Know (about Parallel Programming) Is Wrong! A Wild Screed about the Future“, and it has provoked some discussion among people I know about just how wrong is wrong.
I just read a quite interesting article by Christian Pinto et al, “GPGPU-Accelerated Parallel and Fast Simulation of Thousand-core Platforms“, published at the CCGRID 2011 conference. It discusses some work in using a GPGPU to run simulations of massively parallel computers, using the parallelism of the GPU to speed the simulation. Intriguing concept, but the execution is not without its flaws and it is unclear at least from the paper just how well this generalizes, scales, or compares to parallel simulation on a general-purpose multicore machine.
Nvidia recently announced that their already-known “Kal-El” quad-core ARM Cortex-A9 SoC actually contains five processor cores, not just four as a “normal” quad-core would. They call the architecture “Variable SMP”, and it is a pretty smart design. The one where you think, “I should have thought of that”, which is the best sign of something truly good.
By chance, I got to attend a day at the UPMARC Summer School with a very enjoyable talk by Francesco Zappa Nardelli from INRIA. He described his work (along with others) on understanding and modeling multiprocessor memory models. It is a very complex subject, but he managed to explain it very well.
Episodes 299 and 301 of the SecurityNow podcast deal with the problem of how to get randomness out of a computer. As usual, Steve Gibson does a good job of explaining things, but I felt that there was some more that needed to be said about computers and randomness, as well as the related ideas of predictability, observability, repeatability, and determinism. I have worked and wrangled with these concepts for almost 15 years now, from my research into timing prediction for embedded processors to my current work with the repeatable and reversible Simics simulator.
I just finished reading the October 2010 issue of Communications of the ACM. It contained some very good articles on performance and parallel computing. In particular, I found the ACM Case Study on the parallelism of Photoshop a fascinating read. There was also the second part of Cary Millsap’s articles about “Thinking Clearly about Performance”.
Looks like S4D (and the co-located FDL) is becoming my most regular conference. S4D is a very interactive event. With some 20 to 30 people in the room, many of them also presenting papers at the conference, it turns into a workshop at its best. There were plenty of discussion going on during sessions and the breaks, and I think we all got new insights and ideas.
I listened to an interesting FLOSS Weekly interview with Adam Hall and Achim Hasenmuller of VirtualBox. For someone interested in virtual machines and hardware simulation, the interview was full of interested tidbits. I think the best part was the discussion on multiprocessing in Virtualbox.
I recently read a couple of articles on multicore that felt a bit like jumping back in time. In IEEE Spectrum, David Patterson at Berkeley’s parallel computing lab brings up the issue of just how hard it is to program in parallel and that this makes the wholesale move to multicore into something like a “hail Mary pass” for the computer industry. In Computer World, Chris Nicols at NICTA in Australia asks what you will do with a hundred cores – implying that there is not much you can do today. While both articles make some good points, I also think they should be taken with a grain of salt. Things are better than they make them seem. Read More →
I have another blog up at Wind River. This one is about multicore bugs that cannot happen on multithreaded systems, and is called True Concurrency is Truly Different (Again). It bounces from a recent interesting Windows security flaw into how Simics works with multicore systems.
For my parental leave, I have just bought myself a Lego Mindstorm NXT 2.0 kit. It is not much fun for our youngest, who mostly gets a bit scared by a piece of Lego driving around making noises, but I hope to be able to use it to teach my older child (almost five) to program. Let’s see how that turns out. It looks hard to make the NXT environment provide the kind of Roborally-style programming blocks that I had hoped to create, as I cannot for some reason get a sufficiently custom icon onto custom blocks.
It also presented me with an opportunity to try some domain-specific high-level graphical programming. The programming environment provided for the NXT series of Mindstorms kits is based on LabView from National Instruments, and it really does seem to work. It even features parallel tasks, which I tried to use…
Today here at the MCC 2009 workshop, I heard an interesting talk by David Black-Schaffer of Stanford university. His work is on stream programming for image processing (“2D streams”). Pretty simple basic idea, to use 2D blobs of pixels as kernel inputs rather than single values or vectors. Makes eminent sense for image processing.
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. Read More →
Øredev is the premier software development conference in Sweden and Europe (they claim). I gave some presentations there in 2006 and 2007, but since then they have dropped the general embedded software development track and just focused on programming for mobile phones. Most of the material is “general IT”. If you are doing software development on the desktop or for servers, it is a good place to go to learn new things from the general world of computing.