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QUESTION
I'm reading this tutorial about code vectorization using Intel Advisor. In particular in this page they suggest to:
Build the target sample application in release mode ... compiler options: -O2 -g
And following:
...To build your own applications to produce the most accurate and complete Vectorization Advisor analysis results, build an optimized binary in release mode using the following settings.
ANSWER
Answered 2017-Feb-02 at 21:02The relevant entry point to fresh Intel Advisor tutorials is Getting Started, where you can pick and choose appropriate sub-tutorials. Vectorization Advisor sub-tutorial for Linux can be found here. It precisely says that:
-qopt-report=5 : necessary for version 15.0 of the Intel compiler; unnecessary for version 16.0 and higher
With regards to -vec, -simd, -openmp, the tutorial slightly confuses flags needed for proper Advisor functioning (-g, -O2, optionally -opt-report) vs. flags needed for "proper" Compiler functioning ( -vec, -simd and -openmp). The later ones are just flags controlling compiler's vector code generation, they have nothing to do with Advisor profiling capabilities so you may or may not use them.
To give you deeper understanding: there is an important feature in Advisor, which is called Intel Advisor Survey "Compiler Integration". This feature leverages the data relatively similar but not identical to opt-report. In order to make this feature working you need
- Using Intel Coimpiler 14.x beta, 15.x, 16.x or 17.x
- -g (enable debug info) and -O2 or higher (enable some optimization)
- Optional (for Intel Compiler 15.x only) -qopt-report5
All other features in Intel Advisor work equally well regardless of Compiler version (item 1 above) or opt-report and versions (item 3 above) , but they all still require -g (part of option 2 above). -O2 is not needed for some features, but it is typically useless to deal with -O0 or -O1 compiled binaries when analyzing performance aspects.
QUESTION
I am following the 60-minute blitz on PyTorch but have a question about conversion of a numpy array to a tensor. Tutorial example here.
This piece of code:
...ANSWER
Answered 2019-Mar-07 at 09:34My take on this :
When you do
QUESTION
I'm trying to learn Pytorch, but whenever I seem to try any online tutorial (https://pytorch.org/tutorials/beginner/blitz/tensor_tutorial.html#sphx-glr-beginner-blitz-tensor-tutorial-py), I get errors when trying to run certain functions, but only in Jupyter Notebook.
When running
...ANSWER
Answered 2019-Jan-21 at 02:44Ok, so the fix for me was to either update pytorch through conda using the following command
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