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CuPy is a part of the NumPy ecosystem array libraries [7] and is widely adopted to utilize GPU with Python, [8] especially in high-performance computing environments such as Summit, [9] Perlmutter, [10] EULER, [11] and ABCI. [12] CuPy is a NumFOCUS sponsored project. [13]
TensorFlow is available on 64-bit Linux, macOS, Windows, and mobile computing platforms including Android and iOS. [citation needed] Its flexible architecture allows for easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices.
The Linux Desktop Testing Project (LDTP) is a testing tool that uses computer assistive technology [7] to automate graphical user interface (GUI) testing. [8] The GUI functionality of an application can be tested in Linux , macOS , Windows , Solaris , FreeBSD , and embedded system environments. [ 9 ]
[45] [46] The USB, PCI-e, and M.2 products function as add-ons to existing computer systems, and support Debian-based Linux systems on x86-64 and ARM64 hosts (including Raspberry Pi). The machine learning runtime used to execute models on the Edge TPU is based on TensorFlow Lite . [ 47 ]
PyTorch is a machine learning library based on the Torch library, [4] [5] [6] used for applications such as computer vision and natural language processing, [7] originally developed by Meta AI and now part of the Linux Foundation umbrella.
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The Linux Test Project (usually referred to as LTP) is a body of regression and conformance tests designed to confirm the behaviour of the Linux kernel as well as glibc. [ 1 ] The LTP is a joint project started by SGI , developed and maintained by IBM , Cisco , Fujitsu , SUSE , Red Hat and others.
Unit testing framework with automatic test registration. Supports theories and parameterized tests. Each test is run in its own process, so signals and crashes can be reported. Can output to multiple formats, like the TAP format or JUnit XML. Supports Linux, macOS, FreeBSD, Windows. CU [50] 3-clause BSD