Diagnosing Parallel and Distributed Software Performance Problems

在找到简单的方法来诊断和纠正性能问题之前，并行和分布式计算不会进入计算的主流。该奖项支持开发一种系统，在给定从多个程序执行观察中收集的监控数据的情况下，该系统将从性能指标的曲线图追溯到应修改以改进该指标的进程和源代码部分。回溯是可能的，因为系统的所有部分、源代码、监视数据、性能指标图以及经验模型和理论模型都使用公共状态表示法。该系统实现了三种新颖的功能。首先，它允许对来自少量程序执行的监控数据进行可视化编辑，以定义聚合状态和可以表示所有观察到的程序执行的聚合状态转移率矩阵。其次，它从经验模型而不是从监控数据生成性能度量图，以准确预测程序行为中的不连续性。第三，它生成了程序行为的理论模型，该模型将程序行为映射到多维笛卡尔空间。该系统已应用于一个TCP/IP协议的实现和一个并行离散事件仿真系统。成功诊断这些大型系统中的性能问题可能会改变程序员设计并行和分布式软件的方式。

Parallel and distributed computing will not enter the mainstream of computing until simple means are found to diagnose and correct performance problems. This award supports development of a system which, given monitored data collected from multiple program execution observations, will trace back from a graph of a performance metric to the processes and portions of source code that should be modified to improve the metric. The trace back is possible because all parts of the system, the source code, monitored data, graphs of performance metrics, and empirical and theoretical models, use a common state representation. The system performs three novel functions. First, it allows visual editing of monitored data from a small number of program executions to define aggregate states and an aggregate state transition rate matrix that can represent all observed program executions. Second, it generates graphs of performance metrics from the empirical model, rather than from the monitored data, to accurately predict discontinuities in program behavior. Third, it generates a theoretical model of program behavior that maps program behavior to a multidimensional Cartesian space. The system is applied to a TCP/IP protocol implementation and a parallel discrete event simulation system. Success in diagnosing performance problems in these large systems could change the way programmers design parallel and distributed software.