Analog Devices becomes the latest semiconductor manufacturer to standardize on the increasingly pervasive Eclipse open-source IDE (integrated development environment) and extensible plug-in system with the CrossCore Embedded Studio software suite for C++ and assembly language-based software development, which the company officially unveiled last month at the DESIGN East conference. Particularly attentive readers may recall that this isn't the first time we've heard about CCES (CrossCore
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Texas Instruments recently stated that it intends to de-emphasize application processors for smartphones and tablets, and instead refocus its OMAP processors on embedded applications. And Qualcomm, which has been very successful lately in smartphone and tablet application processors, is dipping its toe in the embedded space as well.
These are very interesting developments to me, because for some time I've been thinking about the role of mobile application processors in embedded applications.
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Cost- and power consumption-sensitive digital signal processing applications tend to leverage fixed point processors, for a common fundamental reason: fixed-point processor cores are substantially less complex than their floating-point counterparts, leading to reductions in transistor count and silicon area. Yet fixed-point processing comes with trade-offs of its own; code development, for example, is complicated by the need to comprehend the potential for overflow, underflow and round-off
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In one of last month's InsideDSP articles, I wrote:
As FPGAs have evolved, the means by which engineers create FPGA designs have also evolved. In particular, design techniques employing increasingly higher levels of abstraction have been required to address the increasing chip capabilities. Initial FPGA design flows were schematic-based. These later gave way to HDLs (hardware description languages) such as VHDL and Verilog. And more recently, C-language-based high-level synthesis has
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Last year, I wrote about how gesture user interfaces are becoming mainstream. Today, with the IMS Touch Gesture Motion conference coming up next week in London, I thought I'd revisit that topic from a different angle.
Among my colleagues at BDTI, there's been a healthy debate going on about whether gesture user interfaces are a gimmick - essentially a solution looking for a problem - or something that really adds value. With tens of millions of Kinect devices sold, I think that Microsoft
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Qualcomm recently opened up the QDSP6 (aka "Hexagon") DSP core in its Snapdragon SoCs to programming access by its customers and software developer partners. Multimedia applications, for example, can benefit from leveraging QDSP6 processing resources, boosting overall performance, minimizing overall power consumption, and freeing up the CPU to tackle other tasks.
But it can take significant time and effort to get up to speed on a new architecture and make optimum use of its potential, no matter
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Over the past 25 years, programmable logic devices have grown in capacity and capability through lithography advancements and the integration of specialized functional blocks. First were dedicated memory arrays derived from the same SRAM used to build logic cells. Next came dedicated-function logic blocks such as multiply-accumulate units (MACs), to accelerate digital signal processing and other math-intensive algorithms, along with the integration of high-performance transceivers to speed
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Spansion is a name that's probably familiar to many of you, as a supplier of nonvolatile memories. You might be wondering, therefore, what the company's doing gracing the pages of InsideDSP. Well, hold that thought! Spansion was originally founded in 1993 as a joint venture of AMD and Fujitsu, and named FASL (Fujitsu AMD Semiconductor Limited). AMD took over full control of FASL in 2003, renamed it Spansion LLC in 2004 and spun it out as a standalone corporate entity at the end of 2005.
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Two years ago, I wrote about my growing interest in "embedded vision", the incorporation of computer vision capabilities into embedded systems, enabling those systems to extract meaning from image and video inputs. Though it's not usually spoken of as "digital signal processing," embedded vision typically uses algorithms familiar to digital signal processing engineers. These include algorithms to improve the quality of capture images (such as lens distortion correction, often performed using
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Remember that childhood game where you try to decide which famous person—or which book, or whatever—you’d like to have with you, if you were to be stranded on a desert island?
Well, choosing a processor is kind of like that. Except, with a processor, it’s not a game. Once you’ve chosen a processor, and designed your hardware and software around that processor, it becomes very expensive—and very time-consuming—to switch to another processor. So, you’re likely to be stuck with whatever choice
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