This article provides a comprehensive survey of techniques for approximate computing (AC), which trades off computation quality with effort to address the growing performance demands and limited resource budgets in modern systems. The authors discuss strategies for identifying approximable program portions, monitoring output quality, and using AC in various processing units and memory technologies. They classify these techniques based on key characteristics to highlight their similarities and differences. The article aims to provide insights into the working of AC techniques and inspire further research to make AC a mainstream computing approach in future systems. The scope of the article includes architecture, programming, and system-level ACTs, with a focus on trade-offs between result quality/accuracy and efficiency. Challenges such as limited application domain, correctness issues, and overheads are also discussed. The article concludes with a discussion on future challenges and potential directions for research.This article provides a comprehensive survey of techniques for approximate computing (AC), which trades off computation quality with effort to address the growing performance demands and limited resource budgets in modern systems. The authors discuss strategies for identifying approximable program portions, monitoring output quality, and using AC in various processing units and memory technologies. They classify these techniques based on key characteristics to highlight their similarities and differences. The article aims to provide insights into the working of AC techniques and inspire further research to make AC a mainstream computing approach in future systems. The scope of the article includes architecture, programming, and system-level ACTs, with a focus on trade-offs between result quality/accuracy and efficiency. Challenges such as limited application domain, correctness issues, and overheads are also discussed. The article concludes with a discussion on future challenges and potential directions for research.