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DSPs

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Originally published in Queue vol. 2, no. 1
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William J. Dally, Ujval J. Kapasi, Brucek Khailany, Jung Ho Ahn, Abhishek Das - Stream Processors: Progammability and Efficiency
Many signal processing applications require both efficiency and programmability. Baseband signal processing in 3G cellular base stations, for example, requires hundreds of GOPS (giga, or billions, of operations per second) with a power budget of a few watts, an efficiency of about 100 GOPS/W (GOPS per watt), or 10 pJ/op (picoJoules per operation). At the same time programmability is needed to follow evolving standards, to support multiple air interfaces, and to dynamically provision processing resources over different air interfaces. Digital television, surveillance video processing, automated optical inspection, and mobile cameras, camcorders, and 3G cellular handsets have similar needs.


W. Patrick Hays - DSPs: Back to the Future
From the dawn of the DSP (digital signal processor), an old quote still echoes: "Oh, no! We'll have to use state-of-the-art 5µm NMOS!" The speaker's name is lost in the fog of history, as are many things from the ancient days of 5µm chip design. This quote refers to the first Bell Labs DSP whose mask set in fact underwent a 10 percent linear lithographic shrink to 4.5µm NMOS (N-channel metal oxide semiconductor) channel length and taped out in late 1979 with an aggressive full-custom circuit design.


Homayoun Shahri - On Mapping Alogrithms to DSP Architectures
Our complex world is characterized by representation, transmission, and storage of information - and information is mostly processed in digital form. With the advent of DSPs (digital signal processors), engineers are able to implement complex algorithms with relative ease. Today we find DSPs all around us - in cars, digital cameras, MP3 and DVD players, modems, and so forth. Their widespread use and deployment in complex systems has triggered a revolution in DSP architectures, which in turn has enabled engineers to implement algorithms of ever-increasing complexity.



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