I have read a few news items and blog posts recently about how various types of software running on top of virtual machines and emulators have managed to either break the emulators or at least detect their presence and self-destruct. This is a fascinating topic, as it touches on the deep principles of computing: just because a piece of software can be Turing-equivalent to a piece of hardware does not mean that software that goes looking for the differences won’t find any or won’t be able to behave differently on a simulator and on the real thing.
There is a new post at my Wind River blog, about the Trinity of Simulation – the computer, the system, and the world. It discusses how you build a really complete system model using not just a virtual platform like Simics, but you also integrate it with a model of the system the computer sits in, as well as the world around it. Like this:
Read more about it in the blog post, and all the older blog posts it links to!
Last year, I concluded a programming project at work that clearly demonstrated that real programming tasks tend to involve multiple languages. I once made a remark to a journalist that there is a zoo of languages inside all real products, and my little project provided a very clear example of this. The project, as discussed previously, was to build an automated integration between a simple Simics target system and the Simulink processor-in-the-loop code testing system. In the course of this project, I used six or seven languages (depending on how you count), three C compilers, and three tools. Eight different compilers were involved in total.
There is a new post at my Wind River blog, about how Simics is used to simulate large wireless networks for IoT (Internet-of-Things) applications.
It is funny for me to be back at the IoT game. A decade ago (time flies, doesn’t it?), at Virtutech, I and Johan Runeson took part in an EU research project on exactly this topic. Unfortunately, we had to back out of that project due to economic circumstances and failing management commitment, but we still learnt a few things that were relevant now that we are back in the IoT game. In particular, how to simulate wireless networks in a reasonable way in a transaction-level simulator. Thus, payback for the investment took 10 years to arrive, but it did arrive. To me, that underscores the need to be a bit speculative, take some risk, and try to explore the future.
I am going to be speaking at the 2015 Embedded World Conference in Nürnberg, Germany. My talk is about Continuous Integration for embedded systems, and in particular how to enable it using simulation technology such as Simics.
My talk is at 16.00 to 16.30, in session 03/II, Software Quality I – Design & Verification Methods.
There is a new post at my Wind River blog, about how you can use Simics to enable the automatic testing of pretty much any computer system (as long as we can put it inside a simulator). This is a natural follow-up to the earlier post about continuous integration with Simics and Simics-Simulink integrations — automated test runs is a mandatory and necessary part of all modern software development.
At the Wind River corporate blog, there is a blog post that I wrote about continuous integration and Simics. At the Elsevier Computer Science Connect blog, there is also a blog post about continuous integration and Simics that I wrote. These two texts are essentially the same, and I had the good fortune to get it posted in multiple places. The reason it is up at Elsevier is to help promote our soon-to-be-released book at about virtual platforms and simulation (and a little bit about Simics), and hopefully we will reach a larger audience with both messages: CI with Simics is a great idea, and the book is a great book to buy.
During my vacation, a blog post went up on the Wind River blog with an interview with Hyungmin Cho, a researcher at Stanford. Hyungmin has done some seriously heavy and cool work with Simics, using it together with a circuit-level simulator to investigate error resiliency in hardware devices, and how errors propagate from hardware into the software. As part of this process, he has setup an automated test system using Simics, and this system has done more than a million automated Simics runs. That is an insane number – I have been using Simics for twelve years now, and if I had used it every day for all these years, I would have had to start 10 runs per hour, every hour of the day. It shows the power of automation along with parallel runs on clusters of machines – once the setup is automated, you can pour on the volume.
For the past six months I have not been doing much blogging at all, neither here nor on the Wind River blog. The reason is that I have been directing my writing energy into writing a text book about Simics together with Daniel Aarno at Intel. Last year, Daniel and I worked on an Intel Technology Journal issue on Simics. The ITJ issue was kind of a first step on the way to the book, collecting several articles about Simics usage at Intel and elsewhere. The book itself will be much more of a detailed description of Simics and how it works and why it works the way it works.
The September 2013 issue of the Intel Technology Journal (which actually arrived in December) is all about Simics. Daniel Aarno of Intel and I served as the content architects for the issue, which meant that we managed to contributed articles from various sources, and wrote an introductory article about Simics and its usage in general. It has taken a while to get this journal issue out, and now that it is done it feels just great! I am very happy about the quality of all the ten contributed articles, and reading the final versions of them actually taught me some new things you could do with Simics! I already wrote about the issue in a Wind River blog post, so in this my personal blog I want to be a little bit more, well, personal.
On the Wind River blog network, I have a short posting about network simulation with Simics. It points to the network demo video that we put up on Youtube a few weeks ago, along with some explanations of what is shown in the video. In short, we show a simple example of a network being simulated in Simics, along with some examples of what you can do with it.
As an old embedded systems and real-time guy, I have always worked with computer systems that are in some way tied to their environment. Simics has often been used to model such computer systems, inside of customer organizations. Which makes it a bit hard to show… however, recently I have cooked up a demo showing Simics simulating a computer system alongside a physical system.
I just put out a post on the Wind River blog, pointing to both a video of my own “water heater” demo and some other Youtube videos showing Simics integrated with simulations of the real world. A screenshot of my setup in action is shown on the side of this post.
There is a new post at my Wind River blog, featuring a recently-posted video demo of device and systems modeling with Simics. In this video demo, we show an outline of the modeling flow used with Simics 4.8, using only the Eclipse interface. It is actually quite new that we can do this much modeling from within Eclipse; recent efforts in improving the Simics user experience are starting to pay off. As part of the product design team, it feels good to see how even quite small features can really improve the usability of the product.
It is also my first blog post on the recently renovated Wind River blog network. I like the new look of the corporate blog, even if I will have to go back and adjust some older blog images to account for the change from a dark to a light background.
Schlock Mercenary is a very funny web (and print) comic that I discovered earlier this year via a list at ArsTechnica. In reading up on back issues and back stories, I came across a nice little gem about simulation.
Carbon Design Systems keeps putting out interesting blog posts at a good pace. Bill Neifert at recently put up a blog post about the various of speed/accuracy tradeoffs you can make when building virtual platforms. The main message of the blog is that you should use a mix of fast models (TLM + JIT, like the ARM Fast Models) and cycle-accurate generated-from-RTL models (like the models generated by Carbon’s tools). By switching between the levels of abstraction when you need to go fast or go deep, you get something that is pretty much the best of both worlds (I already blogged about the change between abstraction before). It makes perfect sense, and I am all with him. There are dragons in the middle land.
However, I do not quite agree with Bill about the absolute uselessness of the intermediate types of models, like SystemC TLM-2.0 AT. Basically, what is traditionally called “cycle accurate modeling” (while not derived from RTL).
I recently read the classic book The Soul of a New Machine by Tracy Kidder. Even though it describes the project to build a machine that was launched more than 30 years ago, the story is still fresh and familiar. Corporate intrigue, managing difficult people, clever engineering, high pressure, all familiar ingredients in computing today just as it was back then. With my interesting in computer history and simulation, I was delighted to actually find a simulator in the story too! It was a cycle-accurate simulator of the design, programmed in 1979.
Carbon Design Systems have been on a veritable blogging spree recently, pushing out a large number of posts around various topics. Maybe a bit brief for my taste in most cases (I have a tendency to throw out 1000+ word pseudo-articles when I take the time to write a blog), but sometimes very interesting nevertheless. I particularly liked a few posts on cache analysis, as they presented some good insight into not-quite-expected processor and cache behaviors.
Carbon Design Systems have been quite busy lately with a flurry of blog posts about various aspects of virtual prototype technology. Mostly good stuff, and I tend to agree with their push that a good approach is to mix fast timing-simplified models with RTL-derived cycle-accurate models. There are exceptions to this, in particular exploratoty architecture and design where AT-style models are needed. Recently, they posted about their new Swap ‘n’ Play technology, which is a old proven idea that has now been reimplemented using ARM fast simulators and Carbon-generated ARM processor models.
On my Wind River blog, I just posted a fairly long post about simulation abstraction levels. It was inspired by a cool article in ArsTechnica about Nintendo emulators, and the costs and benefits of being ever more faithful to the hardware.
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.
There is a new post at my Wind River blog, about hypersimulation in virtual platforms and how it lets virtual time fly much faster than real time. It was the result of simple mistake of leaving Simics running in the background as I did other work on my machine.
I just read an interview with Steve Furber, the original ARM designer, in the May 2011 issue of the Communications of the ACM. It is a good read about the early days of the home computing revolution in the UK. He not only designed the ARM processor, but also the BBC Micro and some other early machines.
There is a new post at my Wind River blog, about how you build virtual platforms with Simics. The post is more about the methodology than the nature of models, cycle accuracy, endianness, and all the other details of virtual platform modeling. I have written about modeling methodology on this blog too, and in particular I would recommend looking at “Two perspectives on modeling“.
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.
Since I have a certain interest in debugging, I was happy find the article “Guidelines for SystemC – Debugger Integration” at the usually interesting Design and Reuse website. However, I must say that it was pretty disappointing.
There is a new post at my Wind River blog, about some computing history. Wind River turns thirty this year, Simics twenty, and simulation for debug (and probably debug in general) turns sixty. Computing has come a long way.
There is a new post at my Wind River blog, about the testing on an integrated software stack in simulation. I base the discussion on the very interesting report about the Toyota “unintended acceleration” problems and the deep investigation into the control software of the affected vehicles performed by a NASA team (!). The report covers a lot of different tools, but also notes that about the only thing not done was to integrate the complete software stack in simulation.
James Aldis of TI has published an article in the EEtimes about how Texas Instruments uses SystemC in the modeling of their OMAP2 platform. SystemC is used for early architecture modeling and performance analysis, but not really for a virtual platform that can actually run software. The article offers a good insight into the virtual platform use of hardware designers, which is significantly different from the virtual platform use of software designers.
Continue reading “EETimes: James Aldis on Performance Modeling”
I am just finishing off reading the chapters of the Processor and System-on-Chip Simulation book (where I was part of contributing a chapter), and just read through the chapter about the Tensilica instruction-set simulator (ISS) solutions written by Grant Martin, Nenad Nedeljkovic and David Heine. They have a slightly different architecture from most other ISS solutions, since that they have an inherently variable target in the configurable and extensible Tensilica cores. However, the more interesting part of the chapter was the discussion on system modeling beyond the core. In particular, how they deal with interrupts to the core in the context of a temporally decoupled simulation.
I previously blogged about the HAVEGE algorithm that is billed as extracting randomness from microarchitectural variations in modern processors. Since it was supposed to rely on hardware timing variations, I wondered what would happen if I ran it on Simics that does not model the processor pipeline, caches, and branch predictor. Wouldn’t that make the randomness of HAVEGE go away?