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

功率效率已经成为现代混合核计算架构的首要设计约束。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，如果计算机系统的可用功率有限，那么应该如何在不同的系统组件之间分配功率，以最快速或最节能地执行给定的计算？或者，在给定用户或系统明确的功率或能量限制的情况下，算法设计是否需要改变？技术方法扩展了一个初步模型，称为能源屋顶线，这是首席研究员（PI）和他的团队作为先前项目的一部分开发的。这种方法从表达算法固有的并发性和通信特性的算法分析的第一原理开始；在此基础上，它根据实际算法、软件和系统的行为直接提供的成本模型，推导出时间、能源和电力的模型。该项目考虑了初步工作的几个关键改进，这将导致一系列精度和复杂性不断提高的模型。该研究将对百亿亿次系统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.