navatala-gpu 0.1.3

Multi-backend GPU kernels and Python bindings

navatala_gpu

Generated Python bindings and runtime facade for Navatala GPU operations.

Scope

• This package contains Python modules, a nanobind extension scaffold, machine-readable API metadata, and smoke tests for the curated public surface.
• The package links against the public Navatala GPU C ABI exposed by navatala/navatala_ffi.h.
• Raw kernel wrappers under navatala_gpu.kernels are an internal/advanced surface; most users should prefer the curated modules such as navatala_gpu.runtime and navatala_gpu.linalg.

Build

The default package build uses the bundled public runtime in stub mode, so pip install . works on hosts without GPU SDKs. Advanced users may link against an already-built runtime by passing the public runtime include directory and shared library:

cmake -S . -B build \
  -DNAVATALA_FFI_INCLUDE_DIR=/path/to/gpu_runtime/include \
  -DNAVATALA_FFI_LIBRARY=/path/to/libgpu_runtime.so
cmake --build build -j

For Python packaging, use a build frontend compatible with scikit-build-core.

Python Usage

import navatala_gpu

caps = navatala_gpu.get_capabilities()
assert "extension_loaded" in caps
assert isinstance(navatala_gpu.supports("axpy", backend="opencl", dtype="float32"), bool)

Runtime Notes

• import navatala_gpu is designed to be safe on hosts without GPU drivers.
• Backend availability is reported through navatala_gpu.get_capabilities() and navatala_gpu.supports(...).
• NumPy interop uses explicit host/device copies through Tensor.from_numpy(...) and Tensor.to_numpy(...).
• DLPack interop is zero-copy only where the runtime can prove backend compatibility.

Manifest id: pyabi6-2675513039