How does it help with memory management?

It offers patterns for identifying high heap usage using Massif and Heaptrack, along with optimization strategies to reduce unnecessary allocations and cloning.

Does it provide guidance on Profile-Guided Optimization (PGO)?

Yes, it includes a step-by-step workflow for instrumenting builds, collecting profiles, and performing optimized release builds using PGO.

Can this skill help with asynchronous Rust performance?

Yes, it specifically includes patterns for using tokio-console to monitor and analyze asynchronous tasks and runtime behavior.

Which tools are supported for Rust profiling?

This skill provides implementation patterns for Criterion (benchmarking), Flamegraph (CPU usage), Valgrind/Heaptrack (memory), and cargo-bloat (binary size).

Performance Analysis & Optimization (Rust)

Name: Performance Analysis & Optimization (Rust)
Author: ShunsukeHayashi

byShunsukeHayashi

•

Analytics & Monitoring

Analyzes and optimizes Rust application performance through CPU profiling, benchmarking, and memory usage tracking.

About

This skill provides specialized guidance for identifying and resolving performance bottlenecks in Rust applications. It offers structured implementation patterns for CPU profiling, memory leak detection, and high-fidelity benchmarking using industry-standard tools like Criterion, Flamegraph, and Valgrind. By following this skill's optimization strategies—ranging from algorithmic improvements to Profile-Guided Optimization (PGO)—developers can significantly reduce latency, minimize memory footprints, and improve binary efficiency in production environments.

Key Features

High-precision benchmarking with Criterion and black_box testing
Asynchronous task monitoring and debugging with tokio-console
7 GitHub stars
CPU profiling and flamegraph generation for bottleneck identification
Comprehensive memory analysis using Valgrind, Massif, and Heaptrack
Binary size reduction and symbol analysis via cargo-bloat

Use Cases

Identifying and fixing high CPU usage in complex Rust algorithms
Benchmarking performance improvements before and after code refactoring
Diagnosing memory leaks and optimizing heap allocation in long-running services

About

Key Features

High-precision benchmarking with Criterion and black_box testing
Asynchronous task monitoring and debugging with tokio-console
7 GitHub stars
CPU profiling and flamegraph generation for bottleneck identification
Comprehensive memory analysis using Valgrind, Massif, and Heaptrack
Binary size reduction and symbol analysis via cargo-bloat

Use Cases

Identifying and fixing high CPU usage in complex Rust algorithms
Benchmarking performance improvements before and after code refactoring
Diagnosing memory leaks and optimizing heap allocation in long-running services