CuPy (https://docs.cupy.dev/en/stable/index.html) is a numpy-compatible array library that uses CUDA for improved performance. What this means is that CuPy arrays live on and are computed on the GPU. It should be theoretically possible to share a CUDA buffer (or however CuPy stores the array data) with OpenGL and therefore VisPy.
This would allow for some really unique workflows where users could do very complex calculations in-GPU with CuPy and visualize them "instantly" without having to copy data back and forth between GPU and CPU memory.
CuPy (https://docs.cupy.dev/en/stable/index.html) is a numpy-compatible array library that uses CUDA for improved performance. What this means is that CuPy arrays live on and are computed on the GPU. It should be theoretically possible to share a CUDA buffer (or however CuPy stores the array data) with OpenGL and therefore VisPy.
This would allow for some really unique workflows where users could do very complex calculations in-GPU with CuPy and visualize them "instantly" without having to copy data back and forth between GPU and CPU memory.