Principle:Unstructured IO Unstructured Benchmark Execution
| Knowledge Sources | |
|---|---|
| Domains | Performance, Benchmarking, CI_CD |
| Last Updated | 2026-02-12 00:00 GMT |
Overview
A benchmarking process that measures average partition execution time across multiple iterations to track performance regressions and compare strategies.
Description
Benchmark execution provides repeatable timing measurements for the partition pipeline. It runs the partition function multiple times on standard benchmark documents, computes average execution time, and records results in CSV format for comparison across code versions, hardware, and strategies.
The benchmarking system includes:
- Warmup runs to prime caches and JIT compilation
- Multiple iterations for statistical stability
- Automatic strategy detection for hi_res documents
- Special handling for slow files (reduced iteration count)
- System information capture (GPU, CPU) for result context
- Optional S3 publishing for CI/CD integration
Usage
Use this principle when you need to quantify partition performance for comparison or regression detection. Run benchmarks after optimization changes to verify improvements, as part of CI to detect regressions, or when evaluating different strategies or hardware configurations.
Theoretical Basis
Reliable benchmarking methodology:
# Abstract benchmark execution
def benchmark(filename, strategy, iterations=3):
# 1. Warmup - prime caches
partition(filename, strategy=strategy)
# 2. Timed iterations
times = []
for i in range(iterations):
start = time.time()
partition(filename, strategy=strategy)
elapsed = time.time() - start
times.append(elapsed)
# 3. Compute average
avg_time = sum(times) / len(times)
return avg_time
Key considerations:
- Warmup: First run is excluded to avoid measuring import/initialization overhead
- Iteration count: Default 2-3 iterations; reduced to 1 for very large documents
- Determinism:
OMP_THREAD_LIMIT=1for reproducible results across runs - Context: System specs (CPU, GPU via nvidia-smi) recorded alongside timing data