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+# TrigDx
+
+High‑performance C++ library offering multiple implementations of transcendental trigonometric functions (e.g., sin, cos, tan and their variants), designed for numerical, signal‑processing, and real‑time systems where trading a small loss of accuracy for significantly higher throughput on modern CPUs (scalar and SIMD) and NVIDIA GPUs is acceptable.
+
+## Why TrigDx?
+Many applications use the standard library implementations, which prioritise correctness but are not always optimal for throughput on vectorized or GPU hardware. TrigDx gives you multiple implementations so you can:
+
+- Replace `std::sin` / `std::cos` calls with faster approximations when a small, bounded reduction in accuracy is acceptable.
+- Use SIMD/vectorized implementations and compact lookup tables for high throughput lookups.
+- Run massively parallel kernels that take advantage of a GPU's _Special Function Units_ (SFUs).
+
+## Requirements
+- A C++ compiler with at least C++17 support (GCC, Clang)
+- CMake 3.15+
+- Optional: NVIDIA CUDA Toolkit 11+ to build GPU kernels
+- Optional: GoogleTest (for unit tests) and GoogleBenchmark (for microbenchmarks)
+
+## Building
+```bash
+git clone https://github.com/astron-rd/TrigDx.git
+cd TrigDx
+mkdir build && cd build
+
+# CPU-only:
+cmake -DCMAKE_BUILD_TYPE=Release -DTRIGDX_USE_XSIMD=ON ..
+cmake --build . -j
+
+# Enable CUDA (if available):
+cmake -DCMAKE_BUILD_TYPE=Release -DTRIGDX_USE_GPU=ON ..
+cmake --build . -j
+
+# Run tests:
+ctest --output-on-failure -j
+```
+
+Common CMake options:
+- `TRIGDX_USE_GPU=ON/OFF` — build GPU support.
+- `TRIGDX_BUILD_TESTS=ON/OFF` — build tests.
+- `TRIGDX_BUILD_BENCHMARKS=ON/OFF` — build benchmarks.
+- `TRIGDX_BUILD_PYTHON` — build Python interface.
+
+## Contributing
+- Fork → create a feature branch → open a PR.
+- Include unit tests for correctness‑sensitive changes and benchmark results for performance changes.
+- Follow project style (clang‑format) and run tests locally before submitting.
+
+## Reporting issues
+When opening an issue for incorrect results or performance regressions, please include:
+- Platform and CPU/GPU model.
+- Compiler and version with exact compile flags.
+- Small reproducer (input data and the TrigDx implementation used).
+  
+## License
+See the LICENSE file in the repository for licensing details.