Machine Learning Primer -- Part III: Advanced Topics
Claudius Gros, WS 2024/25
Institut für theoretische Physik
Goethe-University Frankfurt a.M.
ML Trends / Scaling / Varia
efficient learning
[
Cornell
]
Blog:
towards data science
Efficient Inference in Deep Learning - Where is the Problem?
(2020, by Amnon Geifman)
Petaflops: $10^{15}$ floating point operations per seconds
CPU: $\sim 0.1\cdot 10^{12}$
GPU: $\sim (1\!-\!10)\cdot 10^{12}$
$\mathrm{day}\ \hat{=}\ 86.4\cdot10^3\,\mathrm{sec}$
Moore's law
: performance of hardware doubles every 1.8-2 years
ML requirements
: doubling every 3-4 months
performance
Blog:
Medium
Computational Complexity of Deep Learning: Solution Approaches
(2021, by Vijay S. Agneeswaran)
performance as a function of resources (time, data, complexity)
ImageNet-1k
complexity: # of model parameters
complexity barrier
old/new ML: hard/soft