Data Speculation for Instruction-Level Parallel Processing Systems

指令级并行处理系统的数据推测

• 批准号: 9629948
• 负责人: Wen-mei Hwu
• 金额: $ 10.93万
• 依托单位: University of Illinois at Urbana-Champaign
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1996
• 资助国家: 美国
• 起止时间: 1996-09-01 至 1998-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9629948&HistoricalAwards=false
• 关键词: Data; Speculation; Instruction; Level; Parallel

Data speculation refers to the execution of instructions before it has been determined that the data being used is valid. Data speculation depends on dynamic memory disambiguation to determine if the data was valid, and forces recovery code to execute if the data was invalid. A data speculation compiler generates recovery code to handle the situation where such execution violates a memory dependence. This project examines data speculation techniques, and attempts to understand how to utilize them more effectively. The issues addressed are (1) using data speculation with predication, (2) improving the scheduling algorithms used with it, and (3) using static analysis to help determine when it should be applied. This work will be done using the Memory Conflict Buffer (MCB) technique for dynamic disambiguation. The concepts will be developed so they are applicable to other forms of dynamic memory disambiguation. ***

数据推测是指在确定所使用的数据有效之前执行指令。数据推测依赖于动态内存歧义消除来确定数据是否有效，并在数据无效时强制执行恢复代码。数据推测编译器生成恢复代码以处理这种执行违反存储器依赖的情况。本项目研究数据推测技术，并试图了解如何更有效地利用它们。解决的问题是(1)使用带有预测的数据推测，(2)改进与其一起使用的调度算法，以及(3)使用静态分析来帮助确定何时应该应用它。这项工作将使用内存冲突缓冲区(MCB)技术进行动态歧义消除。这些概念将被开发，以便它们适用于其他形式的动态记忆歧义消除。***