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nvitop is an interactive NVIDIA device and process monitoring tool. It has a colorful and informative interface that continuously updates the status of the devices and processes. As a resource monitor, it includes many features and options, such as tree-view, environment variable viewing, process filtering, process metrics monitoring, etc. Beyond that, the package also ships a CUDA device selection tool nvisel for deep learning researchers.

...It provides real-time insights into key system metrics such as temperatures, fan speeds, voltages, load percentages, and clock speeds by reading directly from sensors embedded in CPUs, GPUs, motherboards, and storage devices. The tool supports a wide range of sensor hardware found on modern systems, including Intel and AMD processors, NVIDIA and AMD graphics cards, SMART temperature sensors on storage drives, and many motherboard monitoring chips. Users can view monitored data directly within the application, as customizable desktop gadgets, or through a system tray interface, making it easy to keep an eye on system health at a glance. OpenHardwareMonitor runs without the need for a traditional installation (it can be run portably) and on systems configured with the appropriate runtime (e.g., .NET or Mono).

...To date tensorflow comes in two different packages, namely tensorflow and tensorflow-gpu, whether you want to install the framework with CPU-only or GPU support, respectively. NVIDIA Drivers and CuDNN must be installed and configured before hand. Please refer to the official Tensorflow documentation for further details. Since version 0.9 Theano introduced the libgpuarray in the stable release (it was previously only available in the development version). The goal of libgpuarray is (from the documentation) make a common GPU ndarray (n dimensions array) that can be reused by all projects that is as future proof as possible, while keeping it easy to use for simple need/quick test. ...

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