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While #14 is a step in the right direction, the benchmark of 800ms for 100 repeated requests leaves me wanting more. We should add some timing logs to each function run in the test suite.
Off the top…
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## Overview
We also want to assess: Have we done everything on the frontend to make sure that this issue is not being caused by bugs or addressable performance bottlenecks? If there are significant b…
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BY far the two largest time/memory hogs are [`n2n_matrix`] and [`paths`] within [`Network.cost_matrix()`](https://github.com/jGaboardi/tigernet/blob/main/tigernet/tigernet.py#L679):
```python
# ca…
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Profile the code to find where bottlenecks are. Perhaps the way a model/formalism is defined and used?
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This issue (motivated by https://discourse.julialang.org/t/flux-vs-pytorch-cpu-performance/42667/25) is intended to be a high level overview of the common bottlenecks that show up in common models. Th…
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The WebUI probably needs some overhaul and investigation of performance bottlenecks.
I strongly assume that the issue is not hardware.
TODO:
- [ ] Find out where potential bottlenecks occur (proba…
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This would be useful to check at some point:
https://pypi.python.org/pypi/memory_profiler
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The story is created to identify bottlenecks to scale IMAGE server. Relevant information available in issue https://github.com/Shared-Reality-Lab/IMAGE-server/issues/804
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**Reason (Why?)**
The current architecture gets slow with increasing amount of trainings
**Solution (What?)**
- Analyze and monitor the performance of the web application
- Find bottlenecks
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Use the short listed tools to profile the wait free memory allocation code. List down the performance bottlenecks.