The following code is what I used to test the performance:All the three segments generate a uniformly random 1000*2000 matrix in double precision 400 times. The timing differences are striking. On my Mac,
I'm trying to spin up an nvidia-docker (2.0) container in Ubuntu 16.04 running Conda with a few python libraries (GPU-enabled tensorflow, opencv, and gdal) and their various dependencies.
Google colab brings TPUs in the Runtime Accelerator. I found an example, How to use TPU in Official Tensorflow github. But the example not worked on google-colaboratory. It stuck on following line:
The NVidia GP100 has 30 TPC circuits and 240 "texture units". Do the TPCs and texture units get used by TensorFlow, or are these disposable bits of silicon for machine learning?
I have a game with the following rules:User is given fruit prices and has a chance to buy or sell items in their fruit basket every turn.