CRI: IAD Resources for Branch Prediction Research

CRI：用于分支预测研究的 IAD 资源

• 批准号: 0751138
• 负责人: Daniel Jimenez
• 金额: $ 23.37万
• 依托单位: University of Texas at San Antonio
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0751138&HistoricalAwards=false
• 关键词: CRI; IAD; Resources; Branch; Prediction

The proposed infrastructure acquisition and development will provide computing resources to enhance the ability of faculty and students in the PI's department to do computationally instensive research projects. A cluster of 32 computers will provide high throughput for tasks arising from compiler and computer architecture research done on in the area of branch prediction. Accurate branch prediction enables a processor to anticipate and respond to future events in order to improve performance while keeping energy consumption due to wrong-path speculation low. The infrastructure will allow the performance and energy of programs running on multicore processors to be measured and enable the modeling of compiler, processor microarchitecture and various branch predictor schemes which can best respond to changes occuring in program execution.

拟议的基础架构采购和开发将提供计算资源，以增强PI部门中教职员工和学生进行计算集成研究项目的能力。 一组32台计算机将为由分支预测领域进行的编译器和计算机架构研究提供的任务提供高吞吐量。 准确的分支预测使处理器能够预测并响应未来的事件，以提高性能，同时由于错误路径推测较低而保持能源消耗。 该基础架构将允许测量多发处理器上运行的程序的性能和能量，并启用编译器，处理器微体系结构和各种分支预测器方案的建模，这些方案可以最好地响应程序执行中发生的变化。