ACCROSS: Approximate Computing aCROss the System Stack
Computer systems have reached a point where significant improvements in computational performance and energy efficiency have become very hard to achieve. The main reason is a power and efficiency wall CMOS technology is facing. Physical limitations such as high power densities and a variety of reliability degradations now enforce larger design margins which reduce efficiency.
Approximate Computing trades off precision against power, energy, storage, bandwidth or performance, and can be applied to hardware, software and algorithms. It enables much more efficient computing by providing additional, adjustable design and runtime parameters to find Pareto optimal solutions. However, its application is still rather limited and a significant extension of the scope of applications is required, including applications that are not necessarily inherently error-tolerant.
The ACCROSS project will tackle this challenge with a cross-layer approach to analysis and optimization, which considers the system stack from the application down to the hardware. At the higher levels, ACCROSS covers the analysis of applications from different computational problem classes, which will act as enablers for mainstream approximate computing. This includes the development of new methods for the analysis of approximation potentials in applications, the adaptation of existing applications to approximation and the quantification of efficiency gains. Moreover, new methods for combining suitable approximation techniques at different system layers during runtime will be provided to maximize efficiency with respect to performance and energy. New error metrics and methods for lightweight runtime monitoring of accuracy will be developed to ensure the usefulness of the targeted applications. At the lower levels, ACCROSS covers the systematic evaluation of the impact of removing design margins which will lead to approximate behavior and improved efficiency. Abstract but accurate models linking the hardware and software will be provided, enabling designers to accurately quantify the error and efficiency impact of approximation across the system stack.