Note: This note delves deeper into performance evaluation and provides a comprehensive review of performance metrics for common components of a modern computational software system.

The performance of a computational software system is quantitatively defined by its ability to optimize resource utilization—such as CPU cycles, memory bandwidth, I/O throughput, and network latency—while minimizing execution time, maximizing throughput, maintaining scalability under variable workloads, and ensuring deterministic responsiveness within specified operational constraints.

Strategy: Study the foundational components of computational systems (hardware, operating systems, algorithms, data structures, etc.) to fully exploit them in the development of High-Performance Systems (HPS) built on top of these foundations.

QA:

• What is the latency of a DB Read?
• What is the latency of a DB Write?

Recommendations for Improvement

• Start with a clear, formalized definition of software performance metrics relevant to computational systems.
• Introduce foundational concepts like time complexity, throughput, latency, efficiency, and scalability with measurable definitions.
• Discuss methodology: benchmarking, profiling, instrumentation, measurement tools, and analysis.
• Organize content logically, moving from theory → measurement → optimization → case studies.
• Integrate frameworks and tools with explanations of when and how they impact performance.
• Focus references with commentary on their relevance and insights.
• Address common performance issues with examples of detection and resolution.
• Remove unrelated or marginal topics or create separate sections clearly marked as supplementary.

Index