yse/easy_profiler
Easy Profiler
Easy Profiler is a performance profiling library for C++ applications designed to measure execution duration and identify bottlenecks. It provides a framework for instrumenting code blocks to track performance metrics, allowing for the analysis of thread activity and system behavior through detailed timeline visualization.
The library distinguishes itself by utilizing scope-based instrumentation to automatically track code lifecycles, minimizing manual overhead. It employs thread-local buffering and asynchronous data flushing to reduce synchronization contention, ensuring that performance data collection has minimal impact on the main execution thread.
Beyond basic timing, the toolset supports comprehensive observability by capturing runtime variables, system-level event hooks, and thread context switches. This allows for the correlation of application-specific data points with underlying hardware resource utilization. Collected metrics can be exported to local files for offline post-mortem review or streamed over a network for real-time monitoring and analysis.
Features
- Application Performance Profiling - Provides a C++ performance profiling library for measuring execution duration and identifying bottlenecks.
- Instrumentation Wrappers - Uses RAII-based scope instrumentation to automatically track code execution lifecycles without manual timing calls.
- Instrumentation Libraries - Instruments code blocks and functions to track performance with automatic scope-based lifecycle management.
- Thread Scheduling Monitors - Observes operating system thread scheduling events to identify performance bottlenecks caused by thread contention or excessive context switching.
- Performance Profiling - Instruments C++ code to measure execution duration, track thread activity, and visualize performance bottlenecks.
- Performance Analyzers - Exports execution logs and profiling snapshots to local files for deep inspection and post-mortem performance review.
- Binary Serialization Formats - Encodes profiling events into a compact binary format for efficient storage and network transmission.
- Thread Activity Analysis - Visualizes thread activity and system events to diagnose resource contention and performance issues.
- Real-Time Performance Profilers - Streams profiling data over a network to a remote interface for immediate feedback on application behavior and latency.
- Real-time Telemetry Streams - Streams captured performance data packets to a remote monitoring interface in real time for live analysis.
- Thread Scheduling Hooks - Intercepts OS-level thread scheduling and context switch events to correlate application performance with hardware resource usage.
- Remote Profiling Streams - Transmits performance metrics over a network connection to a remote interface for real-time monitoring.
- Runtime Variable Captures - Records the state of variables and arrays during execution to correlate performance metrics with specific application data points.
- Telemetry Flushing - Provides asynchronous background flushing of profiling data to ensure minimal performance impact on the main application thread.
- Sampling Event Buffers - Collects performance metrics in per-thread memory buffers to minimize synchronization contention during high-frequency logging.
- Dimensional Application Instrumentation - Provides a framework for instrumenting code to capture runtime variables and system events for performance analysis.
- Performance Event Trackers - Captures thread context-switch events and application-level metrics to provide insight into execution behavior and resource utilization.
- Execution Duration Tracking - Records the duration of specific code blocks to identify performance bottlenecks and latency.
- Execution Tracing - Records runtime variables and timeline bookmarks to correlate specific data points with performance metrics during execution.
- Performance Visualization - Generates graphical representations of execution timelines and thread activity for performance analysis.
- Profile Data Exporters - Saves collected profiling data to local files for offline review and post-mortem analysis.
- Real-time Performance Monitoring - Streams performance metrics over a network to observe application behavior and thread scheduling events in real time.
