plasma-umass/coz
Coz
Coz is a suite of profiling tools for C++ applications designed to identify performance bottlenecks through causal analysis and execution tracking. It functions as a performance profiler that tracks operation timing and execution frequency to determine critical paths within a system.
The tool distinguishes itself through a causal profiling engine and an optimization simulation engine. These capabilities allow for the prediction of how hypothetical code improvements would impact overall system throughput and latency by simulating the effects of speedups without requiring the software to be rewritten and retested. Additionally, it includes an AI-powered profiling assistant that uses language models to suggest optimal locations for performance measurement points and recommend concrete code optimizations.
The system covers broad capability areas including latency and throughput measurement, source code instrumentation, and profile data filtering. It provides a web-based visualizer to render causal profile data and analyze speedup slopes in a browser.
The toolkit includes utilities for build system integration to link external projects with the profiling library and binary.
Features
- Causal Profiling Instrumentation - Implements macro-based source instrumentation to capture execution frequency and timing for causal bottleneck analysis.
- Performance Profilers - Measures how specific code sections affect overall system throughput and latency to identify impactful bottlenecks.
- AI-Powered Code Analysis Tools - Uses language models to analyze profiling results and source code to recommend concrete code optimizations.
- Code Throughput Measurement - Tracks the frequency of visits to specific progress points to determine the overall rate of work completion.
- Optimization Simulators - Predicts the impact of hypothetical code improvements on system speed without needing to rewrite and retest the software.
- Request Latency Measurement - Calculates average transaction delays by measuring the time elapsed between paired start and end points in the source code.
- Optimization Effect Simulation - Predicts the impact of hypothetical code improvements on throughput and latency by simulating speedups without requiring software rewrites.
- Event Latency Measurements - Tracks the time between paired start and end points to evaluate and reduce average event duration.
- Causal Performance Simulators - Implements a causal profiling engine to predict the impact of hypothetical code improvements on system throughput.
- Causal Profiling Tools - Identifies bottlenecks by simulating the effect of code optimizations on throughput and latency.
- Causal-Slope Analysis Tools - Identifies performance bottlenecks by calculating the causal slope of speedups in specific code sections.
- Optimization Simulation Engines - Predicts the impact of hypothetical code improvements by slowing down other system components proportionally.
- Performance Profilers - Provides a profiling system for C++ applications that tracks execution frequency and operation timing.
- Software Bottleneck Identification - Analyzes execution data and source code to determine which parts of a program limit overall performance.
- Instrumentation Placement Agents - Analyzes source code with an AI agent to propose the most effective locations for performance measurement points.
- Profiling Assistants - Provides an instrumentation system using language models to suggest measurement points and concrete code optimizations.
- Throughput and ETA Monitors - Tracks the frequency of visits to specific progress points to determine the overall rate of work completion.
- Function Auto-Instrumentation Macros - Utilizes macros to instrument source code for capturing execution frequency and timing data.
- Transactional Latency Tracking - Measures event duration by recording timestamps at designated start and end points in the source code.
- AI-Assisted Instrumentation - Uses automated agents to identify and insert performance measurement points for more accurate profiling.
- Instrumentation Suggestions - Uses a language model to analyze source code and propose the optimal locations for performance measurement points.
- Profiling Data Visualizations - Provides a web-based visualizer to render captured performance data and analyze speedup slopes.
Star history
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