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CUDA provides both a low level API (CUDA Driver API, non single-source) and a higher level API (CUDA Runtime API, single-source). The initial CUDA SDK was made public on 15 February 2007, for Microsoft Windows and Linux. Mac OS X support was later added in version 2.0, [18] which supersedes the beta released February 14, 2008. [19]
CUDA code runs on both the central processing unit (CPU) and graphics processing unit (GPU). NVCC separates these two parts and sends host code (the part of code which will be run on the CPU) to a C compiler like GNU Compiler Collection (GCC) or Intel C++ Compiler (ICC) or Microsoft Visual C++ Compiler, and sends the device code (the part which will run on the GPU) to the GPU.
Supported API version TDP (Watts) Comments Core Shader Memory Pixel (GP/s) Texture (GT/s) Size Bandwidth Bus type Bus width Single precision Direct3D OpenGL OpenCL CUDA; GeForce 8100 mGPU [44] 2008 MCP78 TSMC 80 nm Unknown Unknown PCIe 2.0 x16 500 1200 400 (system memory) 8:8:4 2 4 Up to 512 from system memory 6.4 12.8
The computations are offloaded to the GPUs through either the low-level or the high-level API introduced with CUDA. CUDA is only available for Nvidia's graphics products. Nvidia OptiX is part of Nvidia GameWorks. OptiX is a high-level, or "to-the-algorithm" API, meaning that it is designed to encapsulate the entire algorithm of which ray ...
Nvidia NVDEC (formerly known as NVCUVID [1]) is a feature in its graphics cards that performs video decoding, offloading this compute-intensive task from the CPU. [2] NVDEC is a successor of PureVideo and is available in Kepler and later Nvidia GPUs.
CUDA support ROCm support [1] Automatic differentiation [2] Has pretrained models Recurrent nets Convolutional nets RBM/DBNs Parallel execution (multi node) Actively developed BigDL: Jason Dai (Intel) 2016 Apache 2.0: Yes Apache Spark Scala Scala, Python No No Yes Yes Yes Yes Caffe: Berkeley Vision and Learning Center 2013 BSD: Yes Linux, macOS ...
Quantum chemistry computer programs are used in computational chemistry to implement the methods of quantum chemistry.Most include the Hartree–Fock (HF) and some post-Hartree–Fock methods.
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]