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I have a deep learning algorithm using CUDA. I have an RTX3060 graphics card, but only 13% is used when running code. What should I do to make my code run faster and use my graphics card at full performance?
I did the nvidia's cuda driver installations properly
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What are the advantages of using convolutional neural network 2D + recurrent neural network instead of CNN 3D or other approaches for egocentric dynamic gestures recognition? Which approach may be considered the best and why?
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There are jobs running on the GPU, and if I run another code on top of it, the code stops at the point of cudaDeviceSynchronize(). Why does this happen?
Currently only one process is allowed to use a GPU at a given point in time. There is no fairness nor quantum to kill a ''job'' in case it runs for hours in a GPU. The basic usage is first come first serve.
But you may use the CUDA Multi-Process Service (MPS). It basically allows multiple processes to share a single gpu
https://docs.nvidia.com/deploy/pdf/CUDA_Multi_Process_Service_Overview.pdf
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I am new to CUDA and going to buy a GPU that will be sufficient for my needs without spending much. I will be working on an application that will require graphics rendering as well as other general purpose computations.
What should be my primary consideration while buying ?
No. of SMs
No. of CUDA Cores
Core/Shader/Memory Clock
Memory Size
Memory Bus width
How do the above mentioned specifications affect CUDA performance?
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I want my software to be GPL (put source code along with your files when you sell it)
but still anyone who (uses, update,sell, derivate) it. gives us credit (for making the core)
The GPL ensures you still get credit. Modifiers are required to retain your copyright statements.
http://www.gnu.org/licenses/gpl-faq.html#IWantCredit
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has anyone done this yet? please show me some good tutorials on building websites with databases using ACCESS 2010
you can build a website using it: http://www.youtube.com/watch?v=AU4mH0jPntI