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The Nvidia CUDA Compiler (NVCC) translates code written in CUDA, a C++-like language, into PTX instructions (an assembly language), and the graphics driver contains a compiler which translates PTX instructions into executable binary code, [2] which can run on the processing cores of Nvidia graphics processing units (GPUs).
CUDA 9.0–9.2 comes with these other components: CUTLASS 1.0 – custom linear algebra algorithms, NVIDIA Video Decoder was deprecated in CUDA 9.2; it is now available in NVIDIA Video Codec SDK; CUDA 10 comes with these other components: nvJPEG – Hybrid (CPU and GPU) JPEG processing; CUDA 11.0–11.8 comes with these other components: [20 ...
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.
Nvidia's Tegra K1 (codenamed "Logan") features ARM Cortex-A15 cores in a 4+1 configuration similar to Tegra 4, or Nvidia's 64-bit Project Denver dual-core processor as well as a Kepler graphics processing unit with support for Direct3D 12, OpenGL ES 3.1, CUDA 6.5, OpenGL 4.4/OpenGL 4.5, and Vulkan.
CUDA cores: up to 16; Standard Memory configurations: 512 MB of DDR2, 256 MB of DDR3, 512 MB of DDR3; Memory Interface Width: Up to 64-bit; Hardware Video Decode Acceleration: Yes, 4th Generation PureVideo; nVidia CUDA Technology: Yes; Certified for Windows 7: Yes; Microsoft DirectX: 10.1; OpenGL: 3.3; Audio: HDA; Maximum digital resolution ...
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. It is accompanied by NVENC for video encoding in Nvidia's Video Codec SDK. [2]
In Windows ,the last driver to fully support CUDA with 64-Bit Compute Capability 3.5 for Kepler in Windows 7 and Windows 8.1 64-bit is 388.71, tested with latest CUDA-Z and GPU-Z, after that driver, the 64-Bit CUDA support becomes broken for GeForce 700 series GK110 with Kepler architecture.
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]