performance_test_execution_plan.md

Performance Test Execution Plan

Overview

This document outlines the plan for executing performance tests to validate half-precision support and overall system performance.

Test Categories

1. Half-Precision Performance Tests

• File: tests/half_precision_performance_tests.rs
• Purpose: Validate f16/bf16 performance improvements
• Metrics: Memory usage, processing speed, accuracy

2. Component Performance Tests

• CLIP Performance: tests/clip_text_encode_performance_test.rs
• KSampler Performance: tests/ksampler_performance_test.rs
• VAE Performance: tests/vae_performance_test.rs

3. System Performance Tests

• End-to-End Performance: Complete workflow performance
• Concurrent Performance: Multi-threaded processing
• Memory Performance: Memory usage and efficiency

Execution Strategy

Phase 1: Baseline Measurements

1. Run single-precision (f32) performance tests
2. Measure memory usage and processing speed
3. Establish performance baseline

Phase 2: Half-Precision Measurements

1. Run half-precision (f16/bf16) performance tests
2. Compare with baseline measurements
3. Validate performance improvements

Phase 3: Integration Measurements

1. Run end-to-end performance tests
2. Measure concurrent processing performance
3. Validate system-wide performance

Expected Results

Performance Improvements

• Memory Usage: 25-30% reduction with half-precision
• Processing Speed: 2-3x improvement over Python
• Throughput: Higher concurrent processing capability
• Latency: Reduced response times

Validation Criteria

• Memory Efficiency: Half-precision should use ~50% less memory
• Speed: Processing should be 2-3x faster than baseline
• Accuracy: No significant accuracy loss with half-precision
• Stability: No performance regressions

Execution Commands

Basic Performance Tests

# Run half-precision performance tests
cargo test --test half_precision_performance_tests

# Run component performance tests
cargo test --test clip_text_encode_performance_test
cargo test --test ksampler_performance_test
cargo test --test vae_performance_test

Benchmark Execution

# Run all benchmarks
cargo bench

# Run specific benchmarks
cargo bench --bench half_precision_bench
cargo bench --bench vae_bench

Performance Profiling

# Run with profiling
cargo test --test performance_profiling_test -- --nocapture

# Run with memory profiling
cargo test --test half_precision_performance_tests -- --nocapture

Environment Requirements

Minimum Requirements

• Rust 1.70+
• Cargo 1.70+
• 8GB RAM (for performance testing)
• 4GB disk space

Recommended Environment

• Docker container with full Rust toolchain
• Performance monitoring tools
• Memory profiling tools
• CPU profiling tools

Timeline

Immediate (Today)

• Set up performance testing environment
• Execute baseline measurements
• Run half-precision performance tests

Short-term (This Week)

• Complete all performance tests
• Analyze results and validate improvements
• Document performance characteristics

Long-term (Next Week)

• Set up continuous performance monitoring
• Implement performance regression testing
• Optimize based on results

Success Criteria

Performance Targets

• Memory Usage: 25-30% reduction with half-precision
• Processing Speed: 2-3x improvement over Python
• Throughput: Higher concurrent processing capability
• Latency: Reduced response times

Validation Requirements

• All performance tests pass
• Performance improvements are validated
• No regressions are introduced
• Results are documented and reproducible