ParallelComputeLab is a CPU parallel computing, low-level optimization, SIMD vectorization, memory efficiency, and reproducible performance benchmarking framework in C++20.
The complete project implementation, test suite, benchmark suite, analysis scripts, and documentation reside in the ParallelComputeLab/ directory.
- Project Overview and Architecture
- Building and Compilation Guide
- Testing and Verification Guide
- Benchmarking Guide
- Performance Methodology
- Known Limitations
- Experimental Results
# Build
cmake -B build/release -S ParallelComputeLab -DCMAKE_BUILD_TYPE=Release
cmake --build build/release -j$(nproc)
# Test
ctest --test-dir build/release --output-on-failure
# Benchmark
python3 ParallelComputeLab/scripts/run_benchmarks.py \
--binary build/release/parallel_compute_benchmarks \
--output-dir ParallelComputeLab/results
# Analyze
python3 ParallelComputeLab/scripts/analyze_results.py \
ParallelComputeLab/results/raw_benchmark_results.json \
ParallelComputeLab/results