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[needs update] Python programmers can use the cuNumeric library to accelerate applications on Nvidia GPUs. In addition to libraries, compiler directives, CUDA C/C++ and CUDA Fortran, the CUDA platform supports other computational interfaces, including the Khronos Group 's OpenCL , [ 11 ] Microsoft's DirectCompute , OpenGL Compute Shader and C++ ...
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3]
Numba can compile Python functions to GPU code. Initially two backends are available: NVIDIA CUDA, see numba.readthedocs.io /en /stable /cuda /index.html; AMD ROCm HSA, see numba.pydata.org /numba-doc /dev /roc; Since release 0.56.4, [3] AMD ROCm HSA has been officially moved to unmaintained status and a separate repository stub has been ...
JAX is python library that provides a machine learning framework for transforming numerical functions developed by Google with some contributions from Nvidia. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).
Nvidia APEX technology is a multi-platform scalable dynamics framework build around the PhysX SDK. It was first introduced in Mafia II in August 2010. [28] Nvidia's APEX comprises the following modules: APEX Destruction, APEX Clothing, APEX Particles, APEX Turbulence, APEX ForceField and formerly APEX Vegetation which was suspended in 2011. [29 ...
On November 12, 2012, at the SC12 conference, a draft of the OpenACC version 2.0 specification was presented. [8] New suggested capabilities include new controls over data movement (such as better handling of unstructured data and improvements in support for non-contiguous memory), and support for explicit function calls and separate ...
Nvidia's CUDA is closed-source, whereas AMD ROCm is open source. There is open-source software built on top of the closed-source CUDA, for instance RAPIDS . CUDA is able to run on consumer GPUs, whereas ROCm support is mostly offered for professional hardware such as AMD Instinct and AMD Radeon Pro .
Scala, Python No No Yes Yes Yes Yes Caffe: Berkeley Vision and Learning Center 2013 BSD: Yes Linux, macOS, Windows [3] C++: Python, MATLAB, C++: Yes Under development [4] Yes No Yes Yes [5] Yes Yes No ? No [6] Chainer: Preferred Networks 2015 BSD: Yes Linux, macOS: Python: Python: No No Yes No Yes Yes Yes Yes No Yes No [7] Deeplearning4j