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An interactive NVIDIA-GPU process viewer and beyond
...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 also provides handy APIs that allow developers to write their own monitoring tools.
...This allows the program to be used with other command line tools such as youtube-dl.
The source code is open and available here. It may be compiled using the contrib library provided along with Qt6, MSVC 2019 and NVIDIA cuda development library.
The project is implemented as part of the CS-110 operating system course at IIIT Bangalore 2013. Aodv protocol is implemented on GPU using CUDA 4.0. A significant gain in execution time is observed when compared to CPU. Thus a simulator which uses GPU can be built on similar lines of NS2 if all the protocols can be parallelized and implemented on GPU.
Guide:
Prof Shrisha Rao
srao@iiitb.ac.in
Prof Poonacha P G
poonacha.pg@iiitb.ac.in
Students:
Abhilash C S
abhilash.gowder@iiitb.org
Abhishek Varshney
abhishek.varshney@iiitb.org
Dilip S
dilip.s@iiitb.org
Navik Yogesh Laljibhai
navik.yogeshlaljibhai@iiitb.org
Pradyot H Adavi
pradyot.h.adavi@iiitb.org
The project is implemented as part of the CS-110 operating system course at IIIT Bangalore 2013. Aodv protocol is implemented on GPU using CUDA 4.0. A significant gain in execution time is observed when compared to CPU. Thus a simulator which uses GPU can be built on similar lines of NS2 if all the protocols can be parallelized and implemented on GPU.
Guide:
Prof Shrisha Rao srao@iiitb.ac.in
Prof Poonacha P G poonacha.pg@iiitb.ac.in
Students:
Abhilash C S abhilash.gowder@iiitb.org
Abhishek Varshney abhishek.varshney@iiitb.org
Dilip S dilip.s@iiitb.org
Navik Yogesh Laljibhai navik.yogeshlaljibhai@iiitb.org
Pradyot H Adavi pradyot.h.adavi@iiitb.org
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