While nearly all signal processing applications require some degree of software optimization, some applications require a sophisticated, multi-tiered optimization approach in order to meet their performance goals.
To obtain the most efficient code, DSP software must be optimized at four distinct levels. First, the software architecture and data flow must be designed to take maximum advantage of the processor’s resources. Second, the appropriate data types must be selected—too big and you’re
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ARM’s general-purpose processor cores have long been used alongside DSP processors in products like cell phones, where the ARM core typically handles tasks like packet processing, user interface, and overall control, and the DSP handles the computationally demanding signal processing. But as ARM has gradually upgraded its cores with DSP-oriented features, more chip and system designers are considering whether to use an ARM core as a DSP engine. The question is, how much signal processing
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On March 5, Stretch, Inc. announced its second-generation software configurable processor family, the S6000, and two initial chips. With this offering—its first since the appointment last year of a new CEO—Stretch is mainly targeting video surveillance, video broadcast, and WiMAX basestation applications.
The S6000, like the previous-generation S5000 family, is a RISC processor which incorporates a reconfigurable compute fabric within its datapath. The fabric (which Stretch calls ISEF)
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Last month BDTI published a white paper detailing the results of its analysis of Texas Instruments’ Digital Video Evaluation Module (DVEVM). The DVEVM is one component of TI's “DaVinci” digital video platform, which also includes video-oriented chips, off-the-shelf multimedia codec software, development tools, and APIs. BDTI's evaluation focuses on whether the DVEVM is straightforward to use, how well it supports application prototyping, and whether it provides system designers with enough
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These days, there are so many start-ups developing programmable processors that it feels like we’re back in the “bubble” years, when anyone with a remotely viable processor design could secure venture funding. A pivotal question for the current crop of start-ups is whether to offer their processors as flexible, general-purpose chips, or as highly specialized, application-specific solutions. Should it be a jack-of-all-trades, or a master of one?
If the processor is complex or the programming
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This month BDTI and silicon intellectual property licensor ARC International announced completion of BDTI Solution Certification™ of the H.264 video decode performance of the ARC Video Subsystem. The ARC Video Subsystem, the first product to be certified under BDTI’s Solution Certification Service, is a programmable subsystem capable of supporting multiple video standards. In certifying the solution, BDTI has independently verified its performance using proprietary BDTI bitstreams and
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Stream Processors, Inc. (SPI) this week unveiled its data-parallel processor architecture and announced two chips based on the architecture. According to SPI, its architecture is optimized for compute-intensive embedded applications which exhibit a high degree of data parallelism, such as video and imaging. SPI believes that cost-performance and developer productivity advantages will enable its chips to compete successfully against FPGAs, high-end DSPs, and ASICs in these applications.
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Algorithms are the essence of digital signal processing; they are the mathematical “recipes” that transform signals in useful ways. Companies developing new DSP algorithms, or considering purchasing or licensing algorithms, often need to assess whether the algorithm will fit within their processing budget–and thereby within their cost and power consumption targets.
But estimating an algorithm’s processing load can be difficult if the algorithm has not already been carefully mapped onto
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At the Consumer Electronics Show last month I was struck (not for the first time) by the number of consumer electronics products that rely on digital signal processing—at this point, nearly all of them. In fact, so many of today's products incorporate digital signal processing-based functions that it's tempting to start viewing these functions as commodities.
But in most cases, DSP functions aren't going to become commodities anytime soon. They may be ubiquitous, but they're not
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Measuring the performance of real-time digital signal processing code is essential. But whether you're using a simulator or hardware, it can be a headache to get accurate, repeatable performance measurements. In this article we'll cover some of the common pitfalls you might encounter, and present some techniques for working around them.
Why Measure?
Digital signal processing applications typically have tight speed and cost constraints, and may also have challenging real-time deadlines. In
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