## Introduction
### Energy Demand of Applications
<hr/>


- Total compute energy approaches world's energy production

  --> Drastic improvements in energy efficiency needed

<div class="flex justify-center">
<img src="/world_energy.svg">
</div>

<Footnotes separator>
  <Footnote>
  SRC. „Decadal Plan for Semiconductors“, Januar 2021. https://www.src.org/about/decadal-plan/.
  </Footnote>
</Footnotes>

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- compute 2x every two years
- energy production 2% per year

- to meet future compute demands, drastic improvements in energy efficiency
-->

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## Introduction
### Memory Bound Workloads
<hr/>

- AI applications become increasingly memory-bound

  --> Instead of bringing the data to the processing, bring the processing to the data

<br>

<div class="flex justify-center">
<img src="/gpt.svg">
</div>

<Footnotes separator>
  <Footnote>
  Ivo Bolsens. „Scalable AI Architectures for Edge and Cloud“, 2023.
  </Footnote>
</Footnotes>

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- Emerging AI applications become increasingly memory-bound
- Roofline model
- Not limited by compute power but by memory
- researchers begin to consider PIM to circumvent memory bottleneck

- (drastically more parameters in GPT-3, operational intensity goes down)
-->
