How to make TensorFlow models run faster on GPUs

[@rtesr7358]

Thank you, It would be a great help if you can share the Jupyter notebook with the profiler configurations.

[@acasualdatascientist54]

I second this

[@retfordb]

is there any support for utilizing pre-compiled kernels for larger shapes through multiple invocations while compiling a new kernel in the background? Or any other kind of intelligence around dynamic recompilation?

[@biygi9178]

ផផ

[@bensouthall2612]

Is that pseudocode of the Add function a real language? Or just an example?

[@TeoZarkopafilis]

Are the slides available?

[@mathieswedler]

I tried running my model with jit compile=True, I got constantly 100% GPU utilization and the terminal stated the graph is using XLA. However, training was faster (and around 80% GPU utilization) WITHOUT XLA. How is that possible? What did I do wrong?

[@kyrgyzsanjar]

did you figure out the reason?

[@trihasta4229]

var=i.0

[@WillFalcon]

Я тоже по-английски умею говорить, но нахера ты это выложил?