M10 Performance

作者 actionbook5c40d3ad7851無授權條款1.5K 個星標收錄於 2026年10月8日更新於 2026年10月8日儲存庫6 週前更新

CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试

僅含說明Software Development

AI 產生的概覽

指導 Rust 效能最佳化：先量測瓶頸，再選擇資料結構、記憶體配置與快取策略。

功能: 此技能提供一套效能最佳化決策框架，核心是先做效能分析再改程式碼。它把減少配置、提升快取區域性、平行化、避免複製與減少間接尋址等目標，對應到具體的實作選擇。內容還包括效能分析與基準測試工具、最佳化優先順序、常用技巧與反模式，並指向所有權、並行與資源管理等相關技能。
適用情境: 當程式碼執行過慢，需要判斷該最佳化什麼以及最佳化是否值得時使用。適用於效能分析、基準測試以及記憶體配置或快取調校，尤其是 Rust 專案。
執行需求: 不附帶任何指令碼或工具，僅為說明性內容。文中提到的工具（cargo bench、criterion、perf、flamegraph、heaptrack、valgrind）皆為選用，使用時需環境中已安裝。

Performance Optimization

Layer 2: Design Choices

Core Question

What's the bottleneck, and is optimization worth it?

Before optimizing:

Have you measured? (Don't guess)
What's the acceptable performance?
Will optimization add complexity?

Performance Decision → Implementation

Goal	Design Choice	Implementation
Reduce allocations	Pre-allocate, reuse	`with_capacity`, object pools
Improve cache	Contiguous data	`Vec`, `SmallVec`
Parallelize	Data parallelism	`rayon`, threads
Avoid copies	Zero-copy	References, `Cow<T>`
Reduce indirection	Inline data	`smallvec`, arrays

Thinking Prompt

Before optimizing:

Have you measured?
- Profile first → flamegraph, perf
- Benchmark → criterion, cargo bench
- Identify actual hotspots
What's the priority?
- Algorithm (10x-1000x improvement)
- Data structure (2x-10x)
- Allocation (2x-5x)
- Cache (1.5x-3x)
What's the trade-off?
- Complexity vs speed
- Memory vs CPU
- Latency vs throughput

Trace Up ↑

To domain constraints (Layer 3):

"How fast does this need to be?"    ↑ Ask: What's the performance SLA?    ↑ Check: domain-* (latency requirements)    ↑ Check: Business requirements (acceptable response time)

"How fast does this need to be?"    ↑ Ask: What's the performance SLA?    ↑ Check: domain-* (latency requirements)    ↑ Check: Business requirements (acceptable response time)

Trace Down ↓

To implementation (Layer 1):

"Need to reduce allocations"    ↓ m01-ownership: Use references, avoid clone    ↓ m02-resource: Pre-allocate with_capacity
"Need to parallelize"    ↓ m07-concurrency: Choose rayon or threads    ↓ m07-concurrency: Consider async for I/O-bound
"Need cache efficiency"    ↓ Data layout: Prefer Vec over HashMap when possible    ↓ Access patterns: Sequential over random access

"Need to reduce allocations"    ↓ m01-ownership: Use references, avoid clone    ↓ m02-resource: Pre-allocate with_capacity
"Need to parallelize"    ↓ m07-concurrency: Choose rayon or threads    ↓ m07-concurrency: Consider async for I/O-bound
"Need cache efficiency"    ↓ Data layout: Prefer Vec over HashMap when possible    ↓ Access patterns: Sequential over random access

Quick Reference

Optimization Priority

1. Algorithm choice     (10x - 1000x)2. Data structure       (2x - 10x)3. Allocation reduction (2x - 5x)4. Cache optimization   (1.5x - 3x)5. SIMD/Parallelism     (2x - 8x)

1. Algorithm choice     (10x - 1000x)2. Data structure       (2x - 10x)3. Allocation reduction (2x - 5x)4. Cache optimization   (1.5x - 3x)5. SIMD/Parallelism     (2x - 8x)

Common Techniques

Technique	When	How
Pre-allocation	Known size	`Vec::with_capacity(n)`
Avoid cloning	Hot paths	Use references or `Cow<T>`
Batch operations	Many small ops	Collect then process
SmallVec	Usually small	`smallvec::SmallVec<[T; N]>`
Inline buffers	Fixed-size data	Arrays over Vec

Common Mistakes

Mistake	Why Wrong	Better
Optimize without profiling	Wrong target	Profile first
Benchmark in debug mode	Meaningless	Always `--release`
Use LinkedList	Cache unfriendly	`Vec` or `VecDeque`
Hidden `.clone()`	Unnecessary allocs	Use references
Premature optimization	Wasted effort	Make it work first

Anti-Patterns

Anti-Pattern	Why Bad	Better
Clone to avoid lifetimes	Performance cost	Proper ownership
Box everything	Indirection cost	Stack when possible
HashMap for small sets	Overhead	Vec with linear search
String concat in loop	O(n^2)	`String::with_capacity` or `format!`

Related Skills

來源與署名

來源：actionbook/rust-skills位於skills/m10-performance提交5c40d3a

授權條款：無授權條款

內容歸原作者所有。SourceWeft 從公開儲存庫中收錄這些內容。

檢舉或申請下架

Question	Trace To	Ask
Latency requirements	domain-*	What's acceptable response time?
Throughput needs	domain-*	How many requests per second?
Memory constraints	domain-*	What's the memory budget?

Tool	Purpose
`cargo bench`	Micro-benchmarks
`criterion`	Statistical benchmarks
`perf` / `flamegraph`	CPU profiling
`heaptrack`	Allocation tracking
`valgrind` / `cachegrind`	Cache analysis

M10 Performance

Performance Optimization

Core Question

Performance Decision → Implementation

Thinking Prompt

Trace Up ↑

Trace Down ↓

Quick Reference

Optimization Priority

Common Techniques

Common Mistakes

Anti-Patterns

Related Skills

來源與署名

更多來自 actionbook/rust-skills 的技能

Rust Trait Explorer

Rust Symbol Analyzer

Rust Skill Creator

Rust Router

Rust Refactor Helper

Rust Daily

更多Software Development技能

Playground

M5 Onboard

Cardputer Buddy

Web Design Guidelines

Vercel React Native Skills

Vercel React Best Practices

When	See
Reducing clones	m01-ownership
Concurrency options	m07-concurrency
Smart pointer choice	m02-resource
Domain requirements	domain-*