Completed clean root directory structure: - Root now contains only: .git, .env, docs/, orig/ - Moved all remaining files and directories to orig/: - Config files (.claude, .dockerignore, .drone.yml, etc.) - All .env variants (except active .env) - Git config (.gitconfig, .github, .gitignore, etc.) - Tool configs (.golangci.yml, .revive.toml, etc.) - Documentation (*.md files, @prompts) - Build files (Dockerfiles, Makefile, go.mod, go.sum) - Docker compose files - All source directories (scripts, tests, tools, etc.) - Runtime directories (logs, monitoring, reports) - Dependency files (node_modules, lib, cache) - Special files (--delete) - Removed empty runtime directories (bin/, data/) V2 structure is now clean: - docs/planning/ - V2 planning documents - orig/ - Complete V1 codebase preserved - .env - Active environment config (not in git) 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
27 lines
1.2 KiB
Markdown
27 lines
1.2 KiB
Markdown
# Mathematical Algorithm Optimization
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Optimize the following mathematical algorithm for performance while maintaining precision: $ARGUMENTS
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## Optimization Focus:
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1. Reduce memory allocations in hot paths (Target: 20-33% reduction like in successful implementations)
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2. Minimize computational overhead
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3. Improve cache efficiency
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4. Leverage concurrency where appropriate
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5. Implement caching strategies for expensive computations (Reference: SqrtPriceX96ToPriceCached achieved 24% performance improvement)
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## Profiling Approach:
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- Use `go tool pprof` to identify bottlenecks
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- Create benchmarks to measure improvements (Reference: Before/after comparison like 1406 ns/op → 1060 ns/op)
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- Validate precision is maintained after optimization
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- Test with realistic data sets
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## Optimization Strategies (Based on Successful Implementations):
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- Precompute expensive constants that are used repeatedly
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- Consider object pooling for frequently created mathematical objects
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- Minimize garbage collection pressure
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- Use lookup tables for repeated calculations
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## Constraints:
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- Do not compromise mathematical precision
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- Maintain code readability and maintainability
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- Follow Go best practices for concurrency and error handling |