NVIDIA on Tuesday released CUDA 13.3 as another significant advancement for their unified GPU programming stack for NVIDIA hardware.
For those wanting to tap the power of CUDA from the Python programming language, CUDA 13.3 marks the CUDA Python 1.0 milestone as a stable, supported means of being able to leverage CUDA in Python apps for AI, data science, scientific computing, and related uses.
For C++ fans, CUDA 13.3 brings CUDA Tile for C++ in bringing the
In addition to these programming enhancements, CUDA 13.3 also introduces the CompileIQ compiler auto-tuning framework that can provide up to 15% speed-ups on kernels like GEMM and attention.
CUDA 13.3 also brings a Numba CUDA MLIR back-end , various math library updates, C++23 support in the NVCC and NVRTC code, mmap() support, and other improvements.
More details on this CUDA 13.3 feature update via the
For those wanting to tap the power of CUDA from the Python programming language, CUDA 13.3 marks the CUDA Python 1.0 milestone as a stable, supported means of being able to leverage CUDA in Python apps for AI, data science, scientific computing, and related uses.
For C++ fans, CUDA 13.3 brings CUDA Tile for C++ in bringing the
CUDA Tileprogramming model to the C++ world.In addition to these programming enhancements, CUDA 13.3 also introduces the CompileIQ compiler auto-tuning framework that can provide up to 15% speed-ups on kernels like GEMM and attention.
CUDA 13.3 also brings a Numba CUDA MLIR back-end , various math library updates, C++23 support in the NVCC and NVRTC code, mmap() support, and other improvements.
More details on this CUDA 13.3 feature update via the