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Introduction: The proliferation of multicore processors and the desire to consolidate applications and functionality will push the embedded industry into embracing virtualization in much the same way it has been embraced in the server and compute-centric markets. However, there are many paths to virtualization for embedded systems. After a tour of those options and their pros and cons, Freescale Semiconductor’s Syed Shah shows why the bare metal hypervisor-based approach, coupled with hardware virtualization assists in the core, the memory subsystem and the I/O, offers the best performance.

Scientists at the Johns Hopkins University Applied Physics Laboratory (APL) were awarded no less than $34.5 million by the Defense Advanced Research Projects Agency (DARPA) to continue their outstanding work in the field of prosthetic limb testing, which has seen them come up with the most advanced model yet. Their Modular Prosthetic Limb (MPL) system is just about ready to be tested on human subjects, as it has proved successful with monkeys. Basically, the prosthetic arm is controlled by the brain through micro-arrays that are implanted (gently) in the head. They record brain signals and send the commands to the computer software that controls the arm. To be honest, it will be interesting to see just how these hair-chips are attached to the brain, but the APL say clinical tests have shown the devices to be entirely harmless. The monkeys didn’t mind them too much, at least.

Dave Megginson (who drove the development of the SAX API that will be familiar to many XML developers who use Java) recently wrote Java is dead. Java stood out as a programming language (though not as a platform) in that Sun had refused to standardize it through an independent and reputable standards organization (a lot of the hard work had been done in one attempt to put it through ECMA and one to put it through ISO, both times Sun pulled out and eventually made their highly unsatisfactory JCP Java Community Process system.) Without the ability to alter Java significantly in ways that might go against their druthers, Java suffered two major forks (Microsoft's J++ then its C#, and IBM's SWT) where significant players disagreed with a major component (the graphics library). Java succeeded in middleware, and but failed to take advantage of the rise of browsers on the deskop: their HTML parser was great for the middle 1990s but was deliberately neglected to the point of being unusable: it is hard not to see this as a deliberate attempt by Sun to leave the browser market to its friends and enemies. I really liked Java, and bet my company on it (in a sense): I would not do that today.

Embedded systems designers deserve better than the feature-lacking point-tools available today. Embedded designs should be more than a collection of microcontrollers and discrete components, pulled together by board design tools and software development environments that are not aware of each other presence, let alone integrated together. Programmable devices are not new. Embedded software is older than most of us! And a lot of embedded design is highly focused on specific interaction between the software and peripherals. So why do we still not have tools that bring all this together and make our lives easier and more productive?

Oracle made a big noise in the Linux community yesterday by announcing its own spin on the Linux kernel on top if its so-called Unbreakable Linux. Oracle presented the announcement as offering a "modern" Linux kernel on top of its own clone of Red Hat. Underneath the hype, what's Oracle really offering, and what does it mean for Linux? For years, Oracle has ridden Red Hat's coattails and tried to present it as a good thing to its customers. Oracle rebrands Red Hat Enterprise Linux (RHEL), slaps its own support package on it, and lets Red Hat do all the heavy development lifting while it tries to poach Red Hat's customers. All perfectly legal according to the licenses that RHEL is shipped under, but a bit skeezy nonetheless. Or perhaps parasitic might be a better word.

IBM's light-powered links overcome the greatest speed bump in supercomputing: interconnect bandwidth

The latest episode of the Robots Podcast looks at the following scenario: Imagine being able to throw a hand-full of smart matter in a tank full of liquid and then pulling out a ready-to-use wrench once the matter has assembled. This is the vision of this episode's guests Michael Tolley and Jonas Neubert from the Computational Synthesis Laboratory run by Hod Lipson at Cornell University, NY. Tolley and Neubert give an introduction into Programmable Matter and then present their research on stochastic assembly of matter in fluid, including both simulation (see video above) and real-world implementation. Read on or tune in!

Usually developers consider Java as a programming language, but Java is a complete operating enviornment including some parts belong to OS. If you have experience of porting Java runtime to embedded system. You will find that RTOS is not a necessary requirement for porting Java.

Most multiprocessing systems can be classified as either symmetric multiprocessing (SMP) or asymmetric multiprocessing (AMP). AMP involves the use of interprocessor communication to combine the efforts of multiple processors, each with its own local operating system and hardware resources. Also, AMP involves less OS overhead for each individual processor and a more traditional execution environment for applications. AMP seems like distributed system. The number of peripherals that are supported in today's multicore processors is quickly increasing. Symmetric-multiprocessing (SMP) software is expected to be quickly available to support these peripherals. Basically any OS can be ported to a SMP platform, but the developers must take care of following issues for SMP OS. - Handling of task priority or implicit synchronization - Spinlocks and synchronization - Synchronization between tasks sharing memory - Synchronization between tasks and ISRs sharing memory - Synchronization between ISRs sharing memory

CPU clock speeds have remained essentially constant over the last several years, resulting in the number of CPU's used in high-end systems rapidly increasing to keep up with the performance boosts expected by Moore's law. System size on the Top500 list has changed rapidly, and, in November 2009, the top ten systems averaged 134,893 cores, with five systems larger than 100,000 cores. This rapid increase of system size and the associated increase in the number of compute elements used in a single user job increase the urgency of dealing with system characteristics that impede application scalability.

To paraphrase helicopter pioneer Igor Sikorsky: If you're in trouble, an airplane can fly over and drop flowers, but a helicopter can save your life. It can deftly maneuver through tight spots and alight in remote places. It can float next to a mountain to search for the lost. And the best sound a wounded soldier can hear is that telltale rotor beat, just minutes before being evacuated to a hospital. When roads are impassable, bridges have been destroyed, and the electricity has been knocked out, helicopters can still deliver supplies and rescue people.

An innovatice camera system could in future enhance security in public areas and buildings. Smart Eyes works just like the human eye. The system analyzes the recorded data in real time and then immediately flags up salient features and unusual scenes.  »Goal, goal, goal!« fans in the stadium are absolutely ecstatic, the uproar is enormous. So it‘s hardly surprising that the security personnel fail to spot a brawl going on between a few spectators. Separating jubilant fans from scuffling hooligans is virtually impossible in such a situation. Special surveillance cameras that immediately spot anything untoward and identify anything out of the ordinary could provide a solution. Researchers from the Fraunhofer Institute for Applied Information Technology FIT in Sankt Augustin have now developed such a device as part of the EU project »SEARISE – Smart Eyes: Attending and Recognizing Instances of Salient Events«. The automatic camera system is designed to replicate human-like capabilities in identifying and processing moving images.

This is a site for all things about amateur Unmanned Aerial Vehicles (UAVs). Use the tabs and drop-down menus above to navigate the site. These are our Arduino-based open source autopilot projects: * ArduPilot, a low-cost autopilot system for planes. * ArduCopter, a fully-autonomous quadcopter system (heli autopilot coming soon). * BlimpDuino, an autonomous blimp with both infrared and ultrasonic guidance.

Japan’s National Institute of Advanced Industrial Science and Technology (AIST) has detailed the software used to make their robot dance (see some nice photos over at Pink Tentacle) in a recent press release.  The software, dubbed Choreonoid (Choreography and Humanoid), is similar to conventional computer animation software.  Users create key poses and the software automatically interpolates the motion between them.  What makes the software unique is that it also corrects the poses if they are mechanically unstable, such as modifying the position of the feet and waist, allowing anyone to create motions compatible with the ZMP balancing method.  This is especially important for robots like the HRP-4C, where complicated motions could easily cause it to fall over.

South Korean researchers have recently made a flexible nonvolatile memory based on memristors—fundamental electronic circuit elements discovered in 2008—using thin graphene oxide films. Memristors promise a new type of dense, cheap, and low-power memory and have typically been made using metal oxide thin films. The new graphene oxide devices should be cheaper and simpler to fabricate—they could be printed on rolls of plastic sheets and used in plastic RFID tags or in the wearable electronics of the future. "We think graphene oxide can be a good candidate for next-generation memory," says Sung-Yool Choi, who leads flexible devices research at the Electronics and Telecommunications Research Institute in Daejeon, South Korea. Choi and his colleagues reported their device last week in Nano Letters.

A little over a mile from the Wolfram Research Europe Ltd. office, where I work, lies Blenheim Palace, which has a rather nice hedge maze. As I was walking around it on the weekend, I remembered a map solving example by Peter Overmann using new image processing features in an upcoming version of Mathematica. I was excited to apply the idea to this real-world example. Once back at my computer, I started by using Bing Maps to get the aerial photo (data created by Intermap, NAVTEQ, and Getmapping plc).

With the consumer demand for richer content and its resultant , increasing high data bandwidth continuing to drive communications systems, coding for error control has become extraordinarily important. One way to improve the bit error rate (BER), while maintaining high data reliability, is to use an error correction technique like the Viterbi algorithm. Originally conceived by Andrew Viterbi as an error-correction scheme for noisy digital communication, the Viterbi algorithm provides an efficient method for forward error correction (FEC) that improves channel reliability. Today, it is used in many digital communications systems in applications as diverse as CDMA and GSM digital cellular, dial-up modems, satellite, deep-space communications and 802.11 wireless LANs. It is also commonly used in speech recognition, keyword spotting and computational linguistics.

Opus is Octasic's high-performing, ultra low-power, asynchronous DSP technology optimized for basestations, video processing and media gateway solutions. Asynchronous designs deliver similar computing performance to synchronous designs, but use less silicon and less power. No clock tree No state-elements Less sensitive to process and temperature variations

Ever since graphene was first produced in a lab at the University of Manchester in 2004, researchers around the world have been fascinated with its potential in electronics applications. Graphene possessed all the benefits of carbon nanotubes (CNTs), namely its charged-carrier mobility, but it didn’t have any of the down sides, such as CNTs’ need for different processing techniques than silicon and the intrinsic difficulty of creating interconnects for CNTs. But all was not easy for applying graphene to electronics applications. One of the fundamental problems for graphene was its lack of a band gap, which left it with a very low on-off ratio measured at about 10 as compared to in the 100s for silicon. Now this fundamental hurdle has been overcome. Based on research led by Phaedon Avouris at IBM’s IBM T.J. Watson Research Center, Yorktown Heights, New York, IBM is reporting that they have created a significant band gap in graphene.

Even in sleep, the human body is rarely still—and within it, there is the constant motion of the contents of our cells and the proteins within. Until now, scientists have had to estimate the speed of complex but common actions such as protein folding (which turns an unorganized polypeptide strand into a complex and useful three-dimensional protein). They could watch the action unfold, so to speak, in a test tube but weren’t sure how close the pace conformed to real life. A group of researchers at the University of Illinois at Urbana–Champaign, however, have developed a system to move the observation out of in vitro and into in vivo.