Blinding Speed

At its heart, digital signal processing is highly numerical and very repetitive. As each new piece of signal data arrives, it must be multiplied, summed, and otherwise transformed according to complex formulas. What makes this such a keen technological challenge is the speed requirement. DSP systems must work in real time, capturing and processing information as it happens. Like a worker on a fast-moving assembly line, Analog-to-Digital converters and DSPs must keep up with the work flow. If they fall behind, information is lost and the signal gets distorted.

The Analog-to-Digital converter, for instance, must take its signal samples often enough to catch all the relevant fluctuations. If the ADC is too slow, it misses some of the action. Imagine trying to film a football game with a movie camera running at one frame per minute. The film would be incoherent, missing entire plays in the intervals between frames. The DSP, too, must keep pace, churning out calculations as fast as the signal data is received from the ADC. The pace gets progressively more demanding as the signal gets faster. Stereo equipment handles sound signals of up to 20 kilohertz (20,000 cycles per second, the upper limit of human hearing), requiring a DSP to perform hundreds of millions of operations per second. Other signals, such as satellite transmissions, are even faster, reaching up into the Gigahertz (billions of cycles per second) range.

DsPs versus Microprocessors

DSPs differ from microprocessors in a number of ways. Microprocessors are typically built for a range of general purpose functions, and normally run large blocks of software, such as operating systems like Windows or UNIX. Although today's microprocessors, including the popular and well-known Pentium family, are extremely fast-as fast or faster than some DSPs-they are still not often called upon to perform real-time computation or signal processing.

Usually, their bulk processing power is directed more at handling many tasks at once, and controlling huge amounts of memory and data, and controlling a wide variety of computer peripherals (disk drive, modem, video display, etc). However, microprocessors such as Pentiums are notorious for their size, cost, and power consumption to achieve their muscular performance, whereas DSPs are more dedicated, racing through a smaller range of functions at lightning speed, yet less costly and requiring much less space (size) and power consumption to achieve their purpose.

DSPs are often used in "embedded systems", where they are accompanied by all necessary software (stored in onchip ROM or offchip EEPROM), built deep into a piece of equipment, and dedicated to a group of related tasks. In computer systems, DSPs may be employed as attached processors, assisting a general purpose host microprocessor.

Different dsPs For Different Jobs

One way to classify DSP devices and applications is by their dynamic range. The dynamic range is the spread of numbers, from small to large, that must be processed in the course of an application. It takes a certain range of values, for instance, to describe the entire waveform of a particular signal, from deepest valley to highest peak. The range may get even wider as calculations are performed, generating larger and smaller numbers through multiplication and division. The DSP device must have the capacity to handle the numbers so generated. If it doesn't, the numbers may "overflow," producing invalid results. The processor's capacity is a function of its data width (i.e. the number of bits it manipulates) and the type of arithmetic it performs (i.e., fixed or floating point).

A 32-bit processor has a wider dynamic range than a 24-bit processor, which has a wider range than 16-bit processor. And floating-point chips have wider ranges than fixed-point devices. Each type of processor is suited for a particular range of applications. 16-bit fixed-point DSPs such as typically used for voice-grade and telecom systems (such as cell-phones), since they work with a relatively narrow range of sound frequencies. On the other hand, hi-fidelity stereo sound has a wider range, calling for a 16-bit ADC or 24-bit ADC, and a 24-bit fixed-point DSP like the Motorola DSP563xx series. In this case, the ADC's 16-bit or 24-bit width is needed to capture the complete high-fidelity signal (i.e. much better than a phone); the DSP thus must be 24 bits to accommodate the larger values resulting when the signal data is manipulated.) Applications requiring still greater dynamic range include image processing, 3-D graphics, and scientific and research simulations; such applications typically a 32-bit floating-point processor.