Performance Counter Sampling via Nyquist Reconstruction
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Solution Overview
Problem
The limited number of performance counter registers (PCRs) in microprocessors restricts the simultaneous measurement of performance counter events (PCEs), leading to cyclical data collection, increased processing burden, and potential self-biasing of performance monitoring, which limits the accuracy and completeness of performance data.
Innovation Solution
Determining the Nyquist sampling frequency for each PCE and scheduling measurements to ensure sampling rates meet or exceed this frequency, combined with signal reconstruction algorithms like the Voronoi-Allebach, Marvasti, or adaptive weights algorithms to reconstruct essentially complete signals from sampled data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the number of performance counter registers is increased to measure more events simultaneously, then measurement completeness is improved, but device complexity and cost increase
Solution Approach 1:
The system implements periodic sampling of performance counter events at Nyquist rates, cycling through available registers in a systematic pattern. This periodic measurement approach allows complete reconstruction of event signals over time without requiring all counters to operate simultaneously, thus maintaining data completeness while using limited hardware resources.
Solution Approach 2:
The system changes the temporal sampling parameters (sampling rate, cycle duration) to match the frequency characteristics of different performance events. By adjusting sampling parameters according to event frequencies and applying reconstruction algorithms, the system recovers complete event information from subsampled data, effectively increasing measurement capacity without adding physical counters.
2Measurement precision
If performance counter events are measured at high sampling rates to capture complete signals, then measurement precision is improved, but processing burden and self-biasing increase
Solution Approach 1:
The system measures only a subset of performance events at any given time, cycling through different event subsets in successive periods. By measuring fewer events simultaneously at Nyquist rates rather than all events continuously, the processing burden per sample is reduced while complete signal reconstruction is achieved through temporal multiplexing and reconstruction algorithms.
3Productivity
If multiple performance counter events are measured simultaneously using available registers, then data collection speed is improved, but measurement accuracy deteriorates due to self-biasing
Solution Approach 1:
The system pre-determines optimal sampling schedules and register allocation patterns before measurement begins. By planning the measurement sequence in advance to ensure Nyquist-rate sampling of each event, the system achieves accurate reconstruction without the need for high simultaneous measurement rates, thereby avoiding self-biasing effects.
Data Source
AI summary
A Nyquist sampling frequency is determined for performance counter events to be measured. Based on the Nyquist sampling frequencies, a schedule for measuring the performance counter events is determined. The performance counter event measurements are then conducted in accordance with the schedule, whereby the measurements yield a set of sample data for each performance counter event. A signal reconstruction algorithm is applied to the set of sample data for each performance counter event to reconstruct an essentially complete signal for each performance counter event. The essentially complete signal for each performance counter event is then used to improve either a design or a utilization of either a microprocessor or an application to be executed on the microprocessor.