Approximate Computing

Approximate Computing Circuits for Energy-Efficient Signal Processing

Maintaining the notion that a computer always produces a perfect result is often unnecessarily expensive. In many application domains, such as digital signal processing (DSP), inherent notions of signal quality set, for example, by quantization and compression artifacts allow for small additional reductions in output quality to be traded off for significant energy gains. WNCG Prof. Andreas Gerstlauer and students, in collaboration with UT Austin Electrical and Computer Engineering Prof. Michael Orshansky focus on hardware approximations at the basic circuit and logic levels.

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