Ultra High-Performance SIMD AVX2 Assisted Search Engine for Python
Project description
Why XCrossfire?
Searching very large unsorted datasets efficiently is a common systems programming challenge.
XCrossfire explores a hardware-aware approach that focuses on:
- Efficient CPU utilization
- SIMD vector processing
- Low-overhead native execution
- Python/C++ interoperability
- Zero-copy style memory interaction where applicable
The goal is to improve practical execution performance while keeping the original dataset unchanged.
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Features
- Native C++ search engine
- Python bindings
- AVX2 SIMD acceleration
- Multi-threaded execution
- Large dataset support
- Low memory overhead
- Benchmark framework included
- Open-source implementation
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