> > VUDA only takes kernels in SPIR-V format. VUDA does not provide any support for compiling CUDA C kernels directly to SPIR-V (yet). However, it does not know or care how the SPIR-V source was created - may it be GLSL, HLSL, OpenCL.

So the answer is no, it can't be used with kernels that use cublas or cudnn, which excludes almost all ML use-cases.

The Vulkan spec does not enforce strict IEEE 754 floating point semantics, so perfect compatibility with CUDA is impossible.

https://registry.khronos.org/vulkan/specs/1.3-khr-extensions...

However, the deep learning field does currently not pay much attention to reproducibility, so this might not be a big issue.