ACCROSS: Approximate Computing aCROs the System Stack

计算系统已经达到了一个点，在计算性能和效率方面的重大改进已经变得非常难以实现。主要原因是由于登纳德缩放法的终止，功率（密度）和效率受到限制。同时也增加了对可靠性的担忧。近似计算权衡精度与功率、能量、存储、带宽或性能，可以应用于硬件、软件和算法。它承诺通过提供额外的、可调整的设计和运行时参数来找到帕累托最优解，从而重新获得高效的计算。然而，它的应用领域仍然相当有限，需要大量扩展应用范围，包括不一定具有固有容错性的应用程序。cross项目的目标是通过一种跨层分析和优化方法来解决这一挑战，该方法考虑了从应用程序到硬件的系统堆栈的几个层（尽管不是全部）。在更高的层次上，cross涵盖了对来自不同计算问题类的应用程序的分析，这些应用程序适合充当主流近似计算的推动者。这包括开发新的方法来分析应用中的近似潜力，使现有的应用适应近似，以及量化和利用效率收益。此外，将提供在不同系统层组合合适的近似技术的新方法，以最大限度地提高运行时在性能和能量方面的效率。此外，将开发新的误差度量和轻量级运行时精度监测方法，以确保目标应用程序的近似计算的适应性。在较低的抽象层次上，cross涵盖了对缩小设计余量的影响的系统评估，这将导致近似的行为和提高的效率。将提供连接硬件和软件的新模型，使设计人员能够准确地量化误差和效率权衡及其对整个系统堆栈的近似计算的影响。

Computing systems have reached a point where significant improvements in computational performance and efficiency have become very hard to achieve. The main reason are power (density) and efficiency limitations due to the discontinuation of Dennard Scaling. as well as increased reliability concerns.Approximate Computing trades off precision against power, energy, storage, bandwidth or performance, and can be applied to hardware, software and algorithms. It promises to re-gain efficient computing by providing additional, adjustable design and runtime parameters to find pareto-optimal solutions. However, its application domain 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 targets to tackle this challenge with a cross-layer approach to analysis and optimization, which considers the several layers (though not all) of 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 are suited to 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 and exploitation of efficiency gains. Moreover, new methods for combining suitable approximation techniques at various system layers will be provided to maximize efficiency during runtime with respect to performance and energy. Furthermore, new error metrics and methods for lightweight runtime monitoring of accuracy will be developed to ensure the amenability of approximate computing of the targeted applications. At the lower abstraction levels, ACCROSS covers the systematic evaluation of the impact of narrowing design margins which will lead to approximate behavior and increased efficiency. New models linking hardware and software will be provided, enabling designers to accurately quantify the error and efficiency tradeoff and its impact of approximation computing across the system stack.