Research Initiation Award: Adaptive Tracing for Optimal Parallel and Sequential Program Debugging

最优跟踪重放的自适应策略 并行和顺序程序的调试将是 开发 随着并行机变得越来越大， 处理器的速度越来越快， 正在阻止复杂的基于痕迹的 调试所需的工具。 我们的目标是减轻 这个问题是双重的。 首先，我们将探讨 理论上的下限必须追溯到提供 执行重播。 我们将调查哪些信息， 共享内存引用或局部变量访问需要 跟踪以在有界的 时间量。 通过限制重放时间，我们提供了一个固定的 调试查询的响应时间，即使是大规模或 长期运行的程序。 第二，我们将开发最佳或 接近最优的策略， 调试 我们的算法做出运行时跟踪决策， 适应接下来的执行，并保持 最小的轨迹。***

Adaptive strategies for the optimal trace-and-replay debugging of parallel and sequential programs will be developed. As parallel machines become larger and processors become faster, the increasing tracing bottleneck is preventing the development of sophisticated trace-based tools necessary for debugging. Our objectives to alleviate this problem are twofold. First, we will explore the theoretical lower bounds on what must be traced to provide execution replay. We will investigate which messages, shared-memory references, or local variable accesses need be traced to replay any part of the execution in a bounded amount of time. By bounding replay time, we provide a fixed response time to debugging queries, even for large-scale or long-running programs. Second, we will develop optimal or near-optimal strategies that adapt to the execution being debugged. Our algorithms make run-time tracing decisions to adapt to what the execution will be doing next, and keep traces optimally small. ***