ISSN 1000-1239 CN 11-1777/TP

• 综述 •

### 算礼：探索计算系统的可分析抽象

1. (计算机体系结构国家重点实验室(中国科学院计算技术研究所) 北京 100190) (中国科学院大学 北京 100049) (zxu@ict.ac.cn)
• 出版日期: 2020-05-01
• 基金资助:
国家重点研发计划项目(2016YFB1000200)；国家自然科学基金重点项目(61532016)；中国科学院网络计算创新研究院物端计算系统项目

### Computation Protocols: Analyzable Abstractions for Computing Systems

Xu Zhiwei, Wang Yifan, Zhao Yongwei, Li Chundian

1. (State Key Laboratory of Computer Architecture (Institute of Computing Technology, Chinese Academy of Sciences), Beijing 100190) (University of Chinese Academy of Sciences, Beijing 100049)
• Online: 2020-05-01
• Supported by:
This work was supported by the National Key Research and Development Program of China (2016YFB1000200), the Key Program of the National Natural Science Foundation of China (61532016), and the Things Computing System Project of CAS Network Computing Innovation Institute.

Abstract: Computing systems research is entering an era of diversity. At the same time, systems research still mainly follows the prototype development and benchmark evaluation approach, making the research cost too high to address the diversity challenge. This dilemma calls for new analyzable abstractions of computing systems. When researching a new system, we can use its abstraction to analyze its characteristics to filter out inappropriate candidate systems before costly prototyping and benchmarking. We already have such a concept for computer applications, called algorithm. Before an algorithm’s implementation and benchmark evaluation, we can usually analyze its main properties, such as time complexity and space complexity. In this paper, we summarize seven advantages of the algorithm concept and propose a preliminary counterpart for computing systems, called computation protocol. Learning from six historical lessons from systems research, we discuss a general definition, a black-box representation, and a white-box representation of the computation protocol concept. We use preliminary examples to point out that computation protocol thinking may be helpful to propose computing systems conjecture, analyze new parallel computing model, extend existing systems architecture, and inspire new system evaluation method.