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The above options provide the complete CUDA Toolkit for application development. Runtime components for deploying CUDA-based applications are available in ready-to-use containers from NVIDIA GPU Cloud. Installing the CUDA Toolkit. Watch this short video about how to install the CUDA Toolkit.

CUDA was developed with several design goals in mind: • Provide a small set of extensions to standard programming languages, like C, that enable a straightforward implementation of parallel algorithms. With CUDA C/C++, programmers can focus on the task of parallelization of the algorithms rather than spending time on their implementation. • Support heterogeneous computation where applications use both the CPU and GPU. Serial portions of applications are run on the CPU, and parallel portions are offloaded to the GPU. As such, CUDA can be incrementally applied to existing applications. The CPU and GPU are treated as separate devices that have their own memory spaces. This configuration also allows simultaneous computation on the CPU and GPU without contention for memory resources.

CUDA-capable GPUs have hundreds of cores that can collectively run thousands of computing threads. These cores have shared resources including a register file and a shared memory. The on-chip shared memory allows parallel tasks running on these cores to share data without sending it over the system memory bus. This guide will show you how to install and check the correct operation of the CUDA development tools. The NVIDIA CUDA Toolkit is available at no cost from the main page. The installer is available in two formats: • Network Installer: A minimal installer which later downloads packages required for installation. Only the packages selected during the selection phase of the installer are downloaded.

This installer is useful for users who want to minimize download time. • Full Installer: An installer which contains all the components of the CUDA Toolkit and does not require any further download. This installer is useful for systems which lack network access. Both installers install the driver and tools needed to create, build and run a CUDA application as well as libraries, header files, CUDA samples source code, and other resources.

The download can be verified by comparing the with that of the downloaded file. If either of the checksums differ, the downloaded file is corrupt and needs to be downloaded again. Choose which packages you wish to install. The packages are: • CUDA Driver: This will install /Library/Frameworks/CUDA.framework and the UNIX-compatibility stub /usr/local/cuda/lib/libcuda.dylib that refers to it. • CUDA Toolkit: The CUDA Toolkit supplements the CUDA Driver with compilers and additional libraries and header files that are installed into /Developer/NVIDIA/CUDA- 10.0 by default. Symlinks are created in /usr/local/cuda/ pointing to their respective files in /Developer/NVIDIA/CUDA- 10.0/. Previous installations of the toolkit will be moved to /Developer/NVIDIA/CUDA-#.# to better support side-by-side installations.