The paper introduces the TAU (Tuning and Analysis Utilities) parallel performance system, designed to address the growing complexity of parallel and distributed systems. TAU aims to provide robust performance capabilities and support high-level performance problem-solving through flexible and portable instrumentation and measurement methods. The system is organized into three layers: instrumentation, measurement, and analysis. The instrumentation layer allows users to define performance events at various levels of program code representation, while the measurement layer supports profiling and tracing with multiple data sources. The analysis and visualization layer provides tools for managing and visualizing performance data. TAU supports various instrumentation methods, including source-based, preprocessor-based, compiler-based, wrapper library-based, binary, interpreter-based, component-based, and virtual machine-based instrumentation. The paper also discusses the measurement system, which abstracts timer and hardware counter interfaces and supports multiple performance data sources. TAU's profiling capabilities include flat profiling and callpath profiling, with efficient runtime infrastructure for both. The paper concludes by highlighting TAU's flexibility and portability, making it suitable for a wide range of parallel computing environments.The paper introduces the TAU (Tuning and Analysis Utilities) parallel performance system, designed to address the growing complexity of parallel and distributed systems. TAU aims to provide robust performance capabilities and support high-level performance problem-solving through flexible and portable instrumentation and measurement methods. The system is organized into three layers: instrumentation, measurement, and analysis. The instrumentation layer allows users to define performance events at various levels of program code representation, while the measurement layer supports profiling and tracing with multiple data sources. The analysis and visualization layer provides tools for managing and visualizing performance data. TAU supports various instrumentation methods, including source-based, preprocessor-based, compiler-based, wrapper library-based, binary, interpreter-based, component-based, and virtual machine-based instrumentation. The paper also discusses the measurement system, which abstracts timer and hardware counter interfaces and supports multiple performance data sources. TAU's profiling capabilities include flat profiling and callpath profiling, with efficient runtime infrastructure for both. The paper concludes by highlighting TAU's flexibility and portability, making it suitable for a wide range of parallel computing environments.