SHF: EAGER: FIESTA: A Sound Multi-Program Workload Methodology

多程序执行，即多个独立应用程序的并发执行，将在有效开发未来多核系统的潜力方面发挥重要作用。研究人员使用多程序工作负载来评估多程序执行各个方面的建议设计和策略。不幸的是，目前使用的固定工作负荷和可变工作负荷多程序工作负荷方法是不健全的，并导致不正确的结果。因此，所提出的研究的目的是调查一个新的多程序的工作量建设计划，称为FIESTA（固定指令与平等STAndalone运行时间），其中应用程序的样本选择，使个别应用程序有平等的运行时间时，单独执行。然后将样本混合并匹配以形成多程序工作负载，但在每个实验中使用相同的样本。本研究将探讨与FIESTA相关的两个问题：应用程序样本的生成和多线程环境的扩展。FIESTA的工作量应该产生内部一致和合理的结果。当新的工具、基准和方法被引入和分发时，计算机体系结构研究激增。引入SimPoints等高效采样和模拟技术后，单程序实验评估的质量和深度得到了提高。FIESTA应该为多程序执行研究和教育提供同样的动力，同时成为单线程和多线程程序采样的标准方法。

Multi-program execution, the concurrent execution of multiple independent applications, will play an important role in efficiently exploiting the potential of future multi-core systems. Researchers use multi-program workloads to evaluate proposed designs and policies for various aspects of multi-program execution. Unfortunately, the fixed workload and variable workload multi-program workload methodologies used today are unsound and lead to incorrect results. Therefore, the proposed research is aimed at investigating a new multi-program workload construction scheme, called FIESTA (Fixed Instruction with Equal STAndalone runtimes), in which application samples are chosen so that individual application have equal runtimes when executing alone. Samples are then mixed and matched to form multi-program workloads, but the same samples are used in every experiment. The research will investigate two issues related to FIESTA: Generation of application samples and Extension to multi-threaded environments. FIESTA workloads should produce results that are internally consistent and plausible.Computer architecture research surges when new tools, benchmarks, and methodologies are introduced and distributed. The quality and depth of single-program experimental evaluation improved when efficient sampling and simulation techniques like SimPoints were introduced. FIESTA should provide the same impetus for multi-program execution research and education, while becoming the standard methodology for sampling both single-threaded and multi-threaded programs.