Efficient Implementation of the Smalltalk-80 System

L. Peter Deutsch, Allan M. Schiffman, 1984, POPL

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Allan M. Schiffman Fairchild Laboratory for Artificial Intelligence Research

摘要

Smalltalk-80*编程语言包括动态存储分配、完全向上的 funargs 和通用多态过程；Smalltalk-80程序系统具有交互式执行、增量编译以及实现可移植性。这些现代程序系统的特性即使单独来看，也是最难以高效实现的特性之一。一个新的Smalltalk-80系统实现运行在基于小型微处理器的计算机上，在保持与现有实现完全（对象代码）兼容的同时，达到了高性能。本文讨论了项目过程中开发出的最重要的优化技术，其中许多技术适用于其他语言。其核心思想是以多种形式表示某些运行时状态（包括代码和数据），并在需要时在这些形式之间进行转换。

*Smalltalk-80是Xerox Corporation的商标。

Allan M. Schiffman Fairchild Laboratory for Artificial Intelligence Research

ABSTRACT

The Smalltalk-80* programming language includes dynamic storage allocation, full upward funargs, and universally polymorphic procedures; the Smalltalk-80 programming system features interactive execution with incremental compilation, and implementation portability. These features of modern programming systems are among the most difficult to implement efficiently, even individually. A new implementation of the Smalltalk-80 system, hosted on a small microprocessor-based computer, achieves high performance while retaining complete (object code) compatibility with existing implementations. This paper discusses the most significant optimization techniques developed over the course of the project, many of which are applicable to other languages. The key idea is to represent certain runtime state (both code and data) in more than one form, and to convert between forms when needed.

*Smalltalk-80 is a trademark of the Xerox Corporation.

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Background

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Special Difficulties

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Implementation Outline

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Code Translation

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Performance Issues

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Dynamic Translation

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Mapping State at Runtime

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Multiple Representations of Contexts

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In-line Caching of Method Addresses

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Experiments

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Context Representations

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In-line Cache and Linked Sends

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Dynamic Code Translation

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Conclusions and Related Work

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Acknowledgments

References

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Read off the page by a vision model reading the page images using olmOCR-2-7B-1025-FP8. Translated into 中文 by gpt-5, against glossary version 6. Translated from the English.

Read off the page by a vision model reading the page images using olmOCR-2-7B-1025-FP8.