Digital signal processor

Digital signal processor
Name	Digital signal processor
Common manufacturers	Texas Instruments, Analog Devices, NXP Semiconductors
Related	Microcontroller, Graphics processing unit, Field-programmable gate array

Digital signal processor. A specialized microprocessor architecture optimized for the mathematical manipulation of digitized signals. These processors are engineered to execute algorithms fundamental to digital signal processing with high efficiency, such as fast Fourier transforms and finite impulse response filtering. Their design prioritizes real-time performance in embedded systems across telecommunications, audio, and control applications.

Overview

The core function is to perform high-speed, repetitive numerical computations on streams of data representing real-world phenomena like sound, images, and sensor readings. This contrasts with general-purpose central processing units, which are designed for broader computational tasks. The architecture typically incorporates specialized hardware for rapid multiply-accumulate operations, a cornerstone of many signal processing algorithms. Key performance metrics include million instructions per second and benchmark (computing) scores for specific functions like Viterbi decoder algorithms.

Architecture

Architecturally, these processors feature a Harvard architecture or modified Harvard architecture, allowing simultaneous instruction and data fetches for increased throughput. They often include multiple data paths and arithmetic logic units to support single instruction, multiple data operations. Dedicated hardware accelerators for functions like convolution or discrete cosine transform are common in modern designs. Companies like Intel with its Intel MCS-96 lineage and IBM with its Cell (microprocessor) have contributed influential architectural concepts. Memory architectures are tuned for data flow, frequently employing direct memory access controllers to minimize central processing unit overhead.

Applications

These processors are ubiquitous in modern technology, forming the computational heart of mobile phone modems for handling Code-division multiple access and Long-Term Evolution standards. In consumer electronics, they enable noise-cancelling headphones, digital audio workstations, and image processing in digital camera systems from companies like Canon Inc.. Industrial and automotive applications include adaptive cruise control, vibration analysis, and real-time monitoring in systems from Siemens and Bosch (company). They are also critical in medical imaging devices like magnetic resonance imaging machines and ultrasound equipment.

Programming

Programming is often done in C (programming language) or C++, with critical loops sometimes optimized in assembly language to exploit architectural features. Development environments and toolchains are provided by vendors such as Texas Instruments with its Code Composer Studio and Analog Devices with its VisualDSP++ suite. Algorithms are frequently implemented using libraries optimized for the target hardware, including those for audio codec standards like MP3 and Advanced Audio Coding. The Embedded Systems Conference often features sessions on programming techniques and optimization strategies for these platforms.

History

The genesis of the field is often traced to the theoretical work of Claude Shannon and the development of the fast Fourier transform by James Cooley and John Tukey. The first single-chip processor is widely considered to be the Intel 2920, introduced in 1979. The 1980s saw rapid commercialization with seminal devices like the Texas Instruments TMS32010, which found early use in modems and military systems. The evolution has been driven by demands from the Bell System, the Compact Disc format, and later, the explosive growth of wireless network standards championed by the Institute of Electrical and Electronics Engineers.

Comparison with other processors

Compared to a general-purpose central processing unit from Advanced Micro Devices or Intel, these processors excel at deterministic, repetitive math on data streams but are less efficient at running complex operating systems like Microsoft Windows. Unlike graphics processing units from Nvidia or AMD, which are optimized for massive parallelism on large data sets, they are tailored for lower-latency, real-time processing with lower power consumption. They also differ from field-programmable gate arrays from Xilinx, which offer higher throughput for fixed algorithms but with greater design complexity and less programming flexibility.

Category:Digital signal processing Category:Microprocessors Category:Embedded systems