If you're a regular reader of this column, you know that I'm enthusiastic about the potential of "embedded vision" – the widespread, practical use of computer vision in embedded systems, mobile devices, PCs, and the cloud. Processors and sensors with sufficient performance for sophisticated computer vision are now available at price, size, and power consumption levels appropriate for many markets, including cost-sensitive consumer products and energy-sipping portable devices. This is ushering in an era of machines that "see and understand".

Let’s face it: Applications are getting more complicated.  Chips are getting more complicated.  And engineering teams are generally getting smaller, not larger.  As a result, it’s incumbent on chip vendors to provide robust, easy-to-use development kits.  Design engineers rely on these kits to quickly evaluate chips and prototype key portions of their systems.

Back in October 2011, InsideDSP covered both recently introduced and pending CPU-plus-GPU products from AMD, along with the cores that they were based on. At the time, AMD referred to CPU-plus-GPU integration as "Fusion"; the company has subsequently renamed such products as APUs (Accelerated Processing Units).

By now, most people who work with processors—whether in data centers, PCs, mobile devices, or embedded systems—understand that parallel processing is the way to get both high compute performance and good energy efficiency for most applications. And most of these people also realize that programming parallel processors is challenging. There are many different types of parallel processors, including CPUs with single-instruction/multiple data capabilities, multi-core CPUs, DSPs, GPUs and FPGAs, among others.

Semiconductor memory is increasing in capacity and becoming more cost-effective all the time. Yet, plenty of deeply embedded applications still exist for which every spare byte of RAM or flash memory is a precious commodity, especially those leveraging on-SoC storage versus discrete components. Tack on a performance-constrained DSP, intentionally speed-hampered to minimize power consumption, and a limited-capacity battery coupled with a multi-day or -week operating life expectation, and you've got a particularly challenging design on your hands.

Those of you familiar with Analog Devices' longstanding presence in the DSP market, via the company's Blackfin, SHARC and TigerSHARC product lines, can be forgiven for assuming that SigmaDSP is yet another family of gene

Investment in a particular technology segment, not only by small startups but also by established suppliers, tends to be a dependable indication that the application has large business potential and lengthy staying power. Consider embedded vision, the use of computer vision techniques to extract meaning from visual inputs in embedded systems, mobile devices, PCs and the cloud. BDTI, accurately predicting that embedded vision would rapidly become an important market, founded the Embedded Vision Alliance in May 2011.

It's a very interesting time in embedded processors.

For decades, embedded processors have continued to deliver more performance and more features, at ever-lower prices and power consumption levels. Today, embedded systems designers are leveraging these processors to create an incredibly diverse range of innovative products. Some of these products, like the Nest thermostat and the G-Box MX2 set-top box, target high-volume markets.

As applications become more complex, and processors become more powerful, system developers increasingly rely on off-the-shelf software components to enable rapid and efficient application development. This is particularly true in digital signal processing, where application developers expect to have access to libraries of optimized building-block functions to speed their work.

Instruction set flexibility can go a long way toward extending the usable life of a processor architecture. Sooner or later, however, instruction set enhancements to an existing architecture foundation run out of steam, and a more fundamental evolution is necessary.