DSP Video Processing Without DSP Programming via Open Source APIs
By Rishi Bhattacharya
November 6, 2006
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Digital signal processors (DSPs) offer outstanding multimedia performance, typically requiring just 40% to 50% as many cycles as a general purpose processor (GPP) core to run a codec (encoders/decoders). They also offer far greater flexibility and reconfigurability than application specific integrated circuits (ASICs). Yet up to now, it has been necessary to learn proprietary languages to take advantage of the benefits of DSPs in digital video applications. Now, the need to learn these proprietary DSP languages is being eliminated by the emergence of application programming interfaces (APIs) that make it possible to easily leverage DSPs from applications running on the GPP.
Open-source multimedia frameworks, which typically run under the Linux operating system on the GPP, are an ideal target for these APIs. The computational burden of video codecs can be offloaded by leveraging the APIs, which abstract many of the complexities of DSP programming. This approach only requires programmers to have basic knowledge of the DSP, and eliminates the need to write code to stitch together DSP functions with those that run on the GPP. These advantages, plus the ability to utilize the many capabilities offered by free open source plug-ins and frameworks, can substantially reduce time to market for new video products.
Codec Hardware Alternatives
Developers have several alternatives in selecting hardware platforms to run the codec algorithms that compress a digital stream for transmission or storage and decompress it for viewing and editing. ASICs offer high performance and low power consumption in digital video applications because the hardware is designed specifically for the applications. The disadvantage of an ASIC is that non-recurring expenses are high and it can also be very expensive to implement changes, such as to accommodate evolving codec standards. GPP cores, on the other, have a comparatively low NRE and can be fairly easily re-programmed to address change, but their performance is low for digital video because they are relatively inefficient at performing computationally intensive signal processing applications.
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