fundamentals of software optimization - data, code and conversation

2022-04-282022-05-01

Fundamentals of Software Performance Analysis Part III — Optimizing Memory Allocation Performance

This is the third post in a three-post series covering the fundamentals of software performance analysis. You can find the introduction here. You can find Part II here. You can find the companion GitHub repository here.

Part II covered the process of using a profiler (VisualVM) to identify “hot spots” where programs spend time and then optimizing program code to improve program wall clock performance.

This post will cover the process of using a profiler to identify memory allocation hot spots and then optimizing program code to improve memory allocation performance. It might be useful to refer back to Part II if you need a refresher on how to use VisualVM or the optimization workflow.

2022-04-242022-05-01

Fundamentals of Software Optimization Part II — Optimizing Wall Clock Performance

This is the second post in a three-post series covering the fundamentals of software optimization. You can find the introduction here. You can find Part I here. You can find Part III here. You can find the companion GitHub repository here.

Part I covered the development of the benchmark, which is the “meter stick” for measuring performance, and established baseline performance using the benchmark.

This post will cover the high-level optimization process, including how to use profile software performance using VisualVM to identify “hot spots” in the code, make code changes to improve hot spot performance, and evaluate performance changes using a benchmark.

2022-04-162022-04-28

Fundamentals of Software Optimization Part I — Benchmarking

This is the first post in a three-post series covering the fundamentals of software optimization. You can find the introduction here. You can find Part II here. You can find the companion GitHub repository here.

The introduction motivated why software optimization is a problem that matters, reflected on the fundamental connection between the scientific method and software performance analysis, and documented the (informal) optimization goal for this series: to optimize the production workflow’s wall clock performance and memory usage performance “a lot.”

This post will cover the theory and practice of designing, building, and running a benchmark to measure program performance using JMH and establishing the benchmark’s baseline performance measurements.