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Xilinx Inc. today introduced the architecture for a new Extensible Processing Platform they claim will deliver unrivaled levels of system performance, flexibility and integration to developers of a wide variety of embedded systems. The ARM Cortex-A9 MPCore processor-based platform enables system architects and embedded software developers to apply a combination of serial and parallel processing to address the challenges they face in designing today's embedded systems, which must meet ever-growing demands to perform highly complex functions. The Xilinx Extensible Processing Platform offers embedded systems designers a processor-centric design and development approach for achieving the compute and processing horsepower required to drive tasks involving high-speed access to real-time inputs, high-performance processing and complex digital signal processing - or any combination thereof - needed to meet their application-specific requirements, including lower cost and power.

National Instruments has released a vision module for the PXI platform that provides a high-performance parallel processing architecture for hardware-defined timing, control and image pre-processing. The NI 1483 Camera Link adapter module, in combination with an NI FlexRIO field-programmable gate array (FPGA) board, offers a solution for embedding vision and control algorithms directly on FPGAs which are used to process and analyse an image in real time with little to no CPU intervention. The FPGAs can be used to perform operations by pixel, line and region of interest. They can implement many image processing algorithms that are inherently parallel, including fast Fourier transforms (FFTs), thresholding and filtering.

This book is intended for those who work in or provide components for industries that use digital signal processing (DSP). There is a wide variety of industries that utilize this technology. While the engineers who implement applications using DSP must be very familiar with the technology, there are many others who can benefit from a basic knowledge of its' fundamental principals, which is the goal of this book—to provide a basic tutorial on DSP.

Verification of algorithm-intensive systems is a long, costly process. Studies show that the majority of flaws in embedded systems are introduced at the specification stage, but are not detected until late in the development process. These flaws are the dominant cause of project delays and a major contributor to engineering costs. For algorithm-intensive systems —including systems with communications, audio, video, imaging, and navigation functions— these delays and costs are exploding as system complexity increases. It doesn't have to be this way. Many designers of algorithm-intensive systems already have the tools they need to get verification under control. Engineers can use these same tools to build system models that help them find and correct problems earlier in the development process. This can not only reduce verification time, but also improves the performance of their designs. In this article, we'll explain three practical approaches to early verification that make this possible. First, let's examine why the current algorithm verification process is inefficient and error-prone. In a typical workflow, designs start with algorithm developers, who pass the design to hardware and software teams using specification documents.

Based on recent technological developments, high-performance floating-point signal processing can, for the very first time, be easily achieved using FPGAs. To date, virtually all FPGA-based signal processing has been implemented using fixed-point operations. This article describes how floating-point technology in FPGAs is not only practical today, but that the processing rates of one trillion floating-point operations per second (teraFLOPS) are feasible and can be implemented on a single FPGA die.

Although signal processing is usually associated with digital signal processors, it is becoming increasingly evident that FPGAs are taking over as the platform of choice in the implementation of high-performance, high-precision signal processing. For many such applications, the choice generally boils down to using either a single FPGA, a FPGA with an associated DSP processor or a farm of DSP processors.

In then the past few years we have seen multiprocessing systems become more mainstream, in fact most modern personal computer CPUs now feature symmetric multiprocessing systems (SMP), where multiple instantiations of the same processor share the processing burden of the applications running on the PC. While SMPs are quite common today, we typically have not seen a shift towards multiprocessing in embedded computing. However, a new type of embedded design technique gives engineers the freedom to intelligently distribute processing functions across a digital subsystem. This article will look at an example of the distributed processing technique using Cypress Semiconductor's PSoC 3 and PSoC 5 architectures, which consist of a main CPU (in this case an 8051 or ARM Cortex M3), a DMA engine, and array of Universal Digital Blocks (UDB).

How's this for a wedge issue on a slow news week? When Xilinx announced earlier this year that it was changing one of its foundry suppliers from UMC to TSMC for the 28-nm node, it seemed like a blow to differentiation—at least from a process technology standpoint—between Xilinx and Altera, which has been using TSMC for years. But while Xilinx chose to go with TSMC's high-performance/low power process, Altera said this week it is going with TSMC's high-performance process. Altera maintains that customers in the high end communications equipment market are much more concerned about performance than power. Luanne Schirrmeister, senior director of product marketing at Altera, put it this way: "In communications infrastructure, nothing is battery powered. Everything is plugged into a wall."

Let’s face it. Most of the gear you use at work or play has multicore processors in it. Your laptop has them (the CPU itself has two cores, and the dedicated graphics processor has many more). That game console in the living room has still more, and even a high-end smartphone typically has a CPU and graphics core on a single chip. Out of sight but definitely not out of mind–particularly if they cease working–are the servers and high-throughput network routers, all which have numerous multicore processors in them. The multiple cores in these devices work in concert to provide quick responses to user queries or to manage the smooth flow of data throughout the office.

By using a simple value process it is possible to speed up the analysis and help identify the best approach to take when developing a constant current regulation scheme for automotive interior LED lighting systems. Various approaches exist to address this particular design challenge that may result in a slowdown of the design process while engineering analysis can be performed to consider the advantages and disadvantages of the different options.

It is no secret that field-programmable gate arrays (FPGAs) are getting bigger and more complex all the time. The fabrication process creates smaller transistors and makes more dense chips packing more digital processing per nanometer. Engineers love to see advancement because it means they can do more with modern silicon, and many times NI LabVIEW FPGA Module technology helps by abstracting the complexity to a higher level so that engineers can more smoothly take advantage of these improvements.  Unfortunately, there is one issue with FPGAs that continues to be a time sink and only gets worse with denser FPGAs: compilation time.

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

The ARM Cortex™-M4 processor is the latest embedded processor by ARM specifically developed to address digital signal control markets that demand an efficient, easy-to-use blend of control and signal processing capabilities. The combination of high-efficiency signal processing functionality with the low-power, low cost and ease-of-use benefits of the Cortex-M family of processors is designed to satisfy the emerging category of flexible solutions specifically targeting the motor control, automotive, power management, embedded audio and industrial automation markets. The Cortex-M4 processor features extended single-cycle multiply-accumulate (MAC) instructions, optimized SIMD arithmetic, saturating arithmetic instructions and an optional single precision Floating Point Unit (FPU). These features build upon the innovative technology that characterizes the ARM Cortex-M series processors…

DSP core licensor Ceva Inc. is due to unveil a software-programmable multimedia video processor architecture at the Mobile World Congress in Barcelona next week. The multicore architecture, called MM3000, which comes complete with C compilers, power management provision and an RTOS/multithreading scheduler is intended to be able to process any and all video codecs up to the highest resolutions and frame rates currently available as well as future codecs for things like 3-D video.

4 January 2010—Though flexible devices such as roll-up displays have been promised for several years, their commercialization has been stalled by a missing ingredient: a flexible form of flash memory. But researchers at the University of Tokyo have recently developed an organic, floating-gate nonvolatile memory that behaves like flash memory, which may solve that problem. While silicon-based flash memory is fine for the mass data storage found in cellphones, digital music players, and thumb drives, fabricating it requires high processing temperatures, thus ruling out its production on flexible substrates like plastic. Organic semiconductors, however, can be processed at temperatures well below the melting point of most plastics. What's more, "the cost of flash memory is too high to use in applications that require large arrays of memory," says Tsuyoshi Sekitani, an assistant professor in the University of Tokyo's department of electrical and electronic engineering and one of the researchers who developed the new memory. "But we can print our organic memory on flexible substrates and over large areas using inkjet printers. So costs will be low."

A little more than a week after long-simmering programmable logic startup Tabula Inc. emerged from stealth mode, Tier Logic Inc. stepped into the light Wednesday (March 10), offering the first details about its technology, which employs a novel processing change to build FPGA and ASIC products on a single die. Like Tabula, Tier Logic's technology depends on a three-dimensional structure. But while Tabula uses rapid reconfiguration to, in the words of that firm's executives, treat time as the third dimension, Tier Logic's approach separates user circuits and configuration circuits into 3-D stacked layers, creating what the company calls the world's first monolithic 3-D FPGA.

While the new multicore system on chip (SoC) signal-processing architecture announced by Texas Instruments this week at Mobile World Congress hits all the right notes with respect to what's needed in next-generation basestation designs, it rings a bit hollow given how sketchy the architectural details remain when contrasted with more 'real' announcements from the likes of Freescale. For sure, the requirements of next-generation basestations will push all architectures to their limits and beyond. Balancing lower power and lower cost with increasingly parallel, math-intensive processing to meet multiuser demands for high-data-rate data in 3GPP Long Term Evolution (LTE) Release 8 all-IP networks is not going to be easy, especially with the introduction of MIMO, beam forming, OFDMA and many other enhancements engineered to maximize spectral efficiency.