Slack: A New Performance Metric for Parallel Programs
نویسندگان
چکیده
Critical Path Profiling is a technique that provides guidance to help programmers try to improve the running time of their program. However, Critical Path Profiling provides only an upper bound estimate of the improvement possible in a parallel program execution. In this paper, we present a new metric, called Slack , to complement Critical Path and provide additional information to parallel programmers about the potential impact of making improvements along the critical path.
منابع مشابه
Distance: a New Metric for Controlling Granularity for Parallel Execution Distance: a New Metric for Controlling Granularity for Parallel Execution
Granularity control is a method to improve parallel execution performance by limiting excessive parallelism. The general idea is that if the gain obtained by executing a task in parallel is less than the overheads required to support parallel execution, then the task is better executed sequentially. Traditionally, in logic programming task size is estimated from the sequential time-complexity o...
متن کاملPrecise Dynamic Analysis for Slack Elasticity: Adding Buffering without Adding Bugs
Increasing the amount of buffering for MPI sends is an effective way to improve the performance of MPI programs. However, for programs containing non-deterministic operations, this can result in new deadlocks or other safety assertion violations. Previous work did not provide any characterization of the space of slack elastic programs: those for which buffering can be safely added. In this pape...
متن کاملSlack-Based Measurement with Rough Data
Rough data envelopment analysis (RDEA) evaluates the performance of the decision making units (DMUs) under rough uncertainty assumption. In this paper, new discussion regarding RDEA is extended. The RSBM model is proposed by integrating SBM model and rough set theory. The process of reaching solution is presented and this model is applied to efficiency evaluation of the DMUs with uncertain ...
متن کاملDistance: A New Metric for Controlling Granularity for Parallel Execution
Granularity control is a method to improve parallel execution performance by limiting excessive parallelism. The general idea is that if the gain obtained by executing a task in parallel is less than the overheads required to support parallel execution, then the task is better executed sequentially. Traditionally, in logic programming, task size is estimated from the sequential time-complexity ...
متن کاملNear-Critical Path Analysis of Program Activity Graphs
Program activity graphs can be constructed from timestamped traces of appropriate execution events. Information about the activities on the k longest execution paths is useful in the analysis of parallel program performance. In this paper, four algorithms for finding the near–critical paths of program activity graphs are presented and compared, including an efficient new algorithm that utilizes...
متن کامل