Parallel Program Profiler for Bottleneck Detection
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Solution Overview
Problem
Identifying performance bottlenecks and algorithm deficiencies in parallel programs is challenging due to the complexity of data collection and analysis, especially when compared to serial programs.
Innovation Solution
A parallel program profiler that dynamically allocates program portions to software and hardware units of execution, aggregates execution information, and generates performance indicators to optimize execution, including data collection, aggregation, and display logic for user interfaces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If profiler infrastructures are used to collect statistics about program execution, then performance information can be gathered, but it becomes difficult to locate performance bottlenecks in parallel programs due to the increased dimensions of data to collect
Solution Approach 1:
The patent segments the complex parallel program execution data into hierarchical levels: individual task statistics, thread statistics, and overall program statistics. This segmentation allows the profiler to manage and analyze data at appropriate granularities, making bottleneck detection feasible despite the high dimensionality of parallel execution data.
Solution Approach 2:
The patent introduces an intermediary profiling layer that sits between the parallel program execution and the analysis tools. This intermediary collects, aggregates, and organizes execution statistics from multiple parallel threads and tasks, transforming raw high-dimensional data into structured performance information that can be effectively analyzed to locate bottlenecks.
2Productivity
If parallel processing is used to speed up complex simulations, then computation time is reduced, but it becomes difficult to detect performance problems due to multiple dimensions of execution data
Solution Approach 1:
The patent implements feedback mechanisms where execution statistics are continuously collected from parallel tasks and threads, aggregated into meaningful performance metrics, and fed back to the user through visual displays. This feedback loop enables real-time or post-execution analysis of performance problems without affecting the parallel computation speed during execution.
Solution Approach 2:
The patent transforms the multi-dimensional parallel execution data into visual representations that add a new dimension of understanding. By displaying performance data in visual formats (such as graphs, charts, or annotated code views), the system converts complex multi-dimensional execution statistics into intuitive visual information that makes performance problems detectable despite the underlying complexity.
Data Source
AI summary
A device receives information generated by execution of a parallel program, aggregates the received information, generates one or more performance indicators for the parallel program on one of a line or function basis and based on the aggregated information, and provides the one or more performance indicators to a user.