nvtop | GPUs process monitoring for AMD , Intel and NVIDIA | GPU library

by Syllo C Version: 3.0.2 License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | nvtop Summary

nvtop is a C library typically used in Hardware, GPU applications. nvtop has no bugs, it has no vulnerabilities and it has medium support. However nvtop has a Non-SPDX License. You can download it from GitHub.

Nvtop stands for NVidia TOP, a (h)top like task monitor for NVIDIA GPUs. It can handle multiple GPUs and print information about them in a htop familiar way.

Support

Quality

Security

License

Reuse

Support

nvtop has a medium active ecosystem.

It has 5369 star(s) with 216 fork(s). There are 73 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 30 open issues and 143 have been closed. On average issues are closed in 78 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of nvtop is 3.0.2

Quality

nvtop has 0 bugs and 0 code smells.

Security

nvtop has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

nvtop code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

nvtop has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

nvtop releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

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nvtop Key Features

No Key Features are available at this moment for nvtop.

nvtop Examples and Code Snippets

No Code Snippets are available at this moment for nvtop.

Community Discussions

Trending Discussions on nvtop

Cupy freeing unified memory

QUESTION

Cupy freeing unified memory

Asked 2020-Sep-23 at 03:04

I have a problem with freeing allocated memory in cupy. Due to memory constraints, I want to use unified memory. When I create a variable that will be allocated to the unified memory and want to free it, it is labelled as being freed and that the pool is now empty, to be used again, but when I take a look at a resource monitor, the memory is still not freed. When I create another variable it also adds to memory (I thought that perhaps the memory labelled as taken would be reused as is mentioned in the documentation but that is not the case.)

Here is a little program to test this with added sleep to be able to see the memory change in a resource monitor.

...

ANSWER

Answered 2020-Sep-23 at 03:04

From a now moderator deleted answer, this appears to be a bug in CuPy. A developer has raised a ticket on the github site, and a patch has been proposed (as at 2020-9-22).

In the short term, you will have to accept this as a problem and wait until a fix appears in a future release. If this is critical, then consider pulling the current development branch from github and building your own package. There is no user code workaround which can solve this.

Source https://stackoverflow.com/questions/63998616

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install nvtop

NVTOP has a builtin setup utility that provides a way to specialize the interface to your needs. Simply press ``F2`` and select the options that are the best for you.
Two libraries are required in order for NVTOP to display GPU information:.
The NVIDIA Management Library (NVML) which comes with the GPU driver.
This queries the GPU for information.
The ncurses library driving the user interface.
This makes the screen look beautiful.
If you use conda as environment manager and encounter an error while building nvtop, try conda deactivate before invoking cmake.
Release: Binary without debug information
RelWithDebInfo: Binary with debug information
Debug: Compile with warning flags and address/undefined sanitizers enabled (for development purposes)

Support

The NVML library does not support some of the queries for GPUs coming before the Kepler microarchitecture. Anything starting at GeForce 600, GeForce 800M and successor should work fine. For more information about supported GPUs please take a look at the [NVML documentation](http://docs.nvidia.com/deploy/nvml-api/nvml-api-reference.html#nvml-api-reference).

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