Energy optimisation opportunities
Digital signal processing (DSP) refers to a host of techniques used to improve digital signals for enhanced accuracy and reliability. The world is inherently analogue, but computers (actually, analogue-to-digital converters) digitise them to use them. DSP helps to distinguish between the signal and the noise. DSP applications are virtually limitless. They include digital wireless communication modems and smartphones, health monitoring and video and audio processing. Engineering systems are often designed to meet the worst case scenario and DSP is no exception. Processing precision is held at a very high level across all cases at the expense of energy efficiency. A novel practical framework for dynamically reducing precision when conditions are appropriate could have substantial impact on energy use and on waste. The EU-supported project OPPORTUNISTIC-DSP developed a scheme for applications requiring very high energy efficiency where maximum benefit might be achieved by lowering numerical precision when possible. Scientists identified a number of context-specific relaxed specifications, adapted computations for the specific context (operator, number and precision), and monitored execution conditions continuously to find opportunities for simplification. Changing the numerical precision at appropriate times has major impact in a highly dynamic computational scenario where the difference between worst case and typical case numerical precision can be enormous. When implemented on an advanced multiple input, multiple output receiver (the Long Term Evolution (LTE) developed by the Third Generation Partnership Project (3GPP)), the new approach achieved a 40 % reduction in energy consumption compared to the fixed precision implementation. While the concept is simple, its implementation is extremely tedious since it entails multiple finite precision refinements, which are very time-consuming optimization processes. Recognising this, the team developed three approaches to enable greater automation of the design process to minimise design complexity. Digital representations of the world have become the norm with computations routinely carried out quickly by DSP equipment and computers. OPPORTUNISTIC-DSP has made important progress toward algorithms and techniques that will facilitate smart reductions in precision through opportunistic approximations. These techniques were shown to significantly reduce energy consumption without degrading functionality and while being complementary to many other traditional energy-saving optimisation techniques. Thus, opportunistic DSP may be an important way to decrease computational load and simultaneously decrease electricity consumption and associated emissions.
