SHF: Small: How Much Execution Time, Energy, And Power Does an Algorithm Need?

能效已经成为现代混合核心计算体系结构的首要设计约束。这项研究提出了执行算法所需的物理时间、能量和功率的新模型。这些模型旨在解决高性能计算(HPC)中的几个当代研究问题。例如，如果计算机系统可用的电力有限，那么应该如何在各种系统组件之间分配这些电力，以最快或最节能地执行给定的计算？或者，考虑到用户或系统明确的功率或能量限制，算法的设计有什么需要改变的吗？这种技术方法扩展了一个被称为能量屋顶的初步模型，首席调查员(PI)和他的团队作为先前项目的一部分开发了这个模型。该方法从表示算法的内在并发性和通信属性的算法分析的基本原理开始；从该原理出发，它使用由真实算法、软件和系统的行为直接告知的成本模型来导出时间、能量和功率模型。该项目考虑了对初步工作的几项关键增强，这将导致一系列模型的准确性和复杂性不断提高。这项研究将对艾级系统中的一系列重要设计问题产生广泛的影响。

Power efficiency has emerged as the overarching design constraint for modern hybrid-core computing architectures. This research advances new models of the physical time, energy, and power needed to execute an algorithm. Such models aim to address several contemporary research questions in high-performance computing (HPC). For instance, if there is a limited amount of power available to a computer system, how should that power be allocated among various system components to most quickly or most energy-efficiently execute a given computation? Or, does anything need to change in the design of algorithms, given a user's or a system's explicit power or energy constraints?The technical approach extends a preliminary model, referred to as the energy roofline, which the Principal Investigator (PI) and his team have developed as part of a prior project. This approach starts from first principles of algorithmic analysis that express the intrinsic concurrency and communication properties of an algorithm; and from that, it derives models of time, energy, and power using cost models informed directly by the behavior of real algorithms, software, and systems. The project considers several critical enhancements of the preliminary work, which is leading to a family of models of increasing accuracy and complexity. The research will have a broad impact on a wide range of important design issues in exascale systems.