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This research aims to develop a profiling system that continuously collects performance data to identify issues in multiprocessor environments.

Continuous profiling

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This research aims to develop a profiling system that continuously collects performance data to identify issues in multiprocessor environments.
Developed a sampling-based profiling system running continuously on production systems.
Collected over 5200 samples/sec. per 333MHz processor with minimal overhead (1-3% slowdown).
Provided analysis tools to evaluate performance issues at the instruction level, focusing on stalls and their causes.
Achieved high-frequency data collection while maintaining low operational impact.
Identified performance bottlenecks related to cache misses, branch mispredictions, and functional unit contention.
Enabled precise accounting of time spent on specific instructions, facilitating targeted performance optimizations.

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Randomized trial shows improved performance insights in multiprocessor systems, indicating potential for optimization.

Anderson et al. (1997) studied this question.

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