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authorNikhil Raj <nikhil.raj@arm.com>2021-11-12 11:43:58 +0000
committerDavid Monahan <David.Monahan@arm.com>2021-11-12 14:31:20 +0000
commitd55ebd6972c6c6719d20a988aef665f4f281cdaf (patch)
treee7c58b0b490c9e88c0734db4c10aafa04d860b40 /README.md
parent45c250a5d6e1669d2670282a55b48b3d727e381b (diff)
downloadarmnn-d55ebd6972c6c6719d20a988aef665f4f281cdaf.tar.gz
Update the graph path in Readme and update project number in doxyfile
* Move all the image files used in doxygen to docs/ * Have a single path for all images in Doxyfile * Update project number to 21.11 in Doxyfile Signed-off-by: Nikhil Raj <nikhil.raj@arm.com> Change-Id: Ic9102d36b69a8261caf8e55da645463540e0b9f3
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@@ -27,7 +27,7 @@ hardware you want to execute it on. This results in a great boost of execution s
network can be executed depends on the operations it contains and the available hardware. Below you can see the speedup
we've been experiencing in our experiments with a few common networks.
-\image html docs/PerformanceChart.odt
+\image html PerformanceChart.png
Arm NN is written using portable C++14 and the build system uses [CMake](https://cmake.org/), therefore it is possible
to build for a wide variety of target platforms, from a wide variety of host environments.