Axiom is an open-source tensor library designed for performance and ease of use, providing a NumPy/PyTorch-like API to native C++. With advanced SIMD vectorization, BLAS acceleration, and support for Metal GPU, Axiom combines high-performance computing with an intuitive interface for Python developers, making it ideal for modern computational needs.
Axiom is a high-performance, open-source C++ tensor library designed to provide the simplicity of NumPy and PyTorch in native code. With cutting-edge features such as SIMD vectorization, BLAS acceleration, and Metal GPU support, Axiom ensures HPC-grade performance along with an intuitive API that aligns closely with what Python developers are familiar with.
Get a glimpse of Axiom’s intuitive syntax:
// NumPy: x = np.where(x > 0, x, 0)
auto x = Tensor::where(x > 0, x, 0);
// NumPy: y = x.reshape(2, -1).T
auto y = x.reshape({2, -1}).T();
// PyTorch: z = F.softmax(scores, dim=-1)
auto z = scores.softmax(-1);
For performance insights, Axiom has demonstrated over 3500+ GFLOPS on M4 Pro, substantially outperforming libraries like Eigen and PyTorch in benchmarks.
Axiom also integrates powerful features for complex tensor manipulations with functionalities such as:
Axiom is built for developers seeking the performance capabilities of C++ while enjoying the user-friendly experience of high-level tensor libraries. Explore Axiom’s Quick Start guide and Benchmarks section to see the library in action.
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