Paper-notes

An updated look at the total electricity consumption and associated GHG emissions for the ICT sector in 2020. Paper notes on Malmodin et al. (2023).

Will we ever be able to accurately assess the carbon footprint of IT? Could a relational footprint methodology be more useful? Paper notes on Pasek et al (2023).

Notes on the paper Khan et al (2018) RAPL in Action: Experiences in Using RAPL for Power Measurements. Advantages and limitations of the Running Average Power Limit (RAPL) interface.

Removing the aggregation spine resulted in 5x higher speed and capacity, and 41% reduction in power.

This is a good paper that makes valid points about the possibilities of migrating flexible IT workloads, however it makes classic assumptions I see in most papers that discuss this topic.

Which languages are the fastest and most energy efficient? The simple answer is: C, C++, Rust. The accurate answer is: it depends.

The methodology is invalid, which the authors acknowledge but ignore. This means the results of this article aren’t particularly useful.

Data centers are not 100% efficient, so they generate waste heat, which causes anthroprogenic heat flux, and can therefore be linked to global warming. But how much? And should we be concerned?

What will drive computer performance after Moore’s law? Will programmers need to focus on performance or can ARM chips and the cloud save us?

My notes on the paper: Heptonstall, P.J. & Gross, R.J.K. (2021) A systematic review of the costs and impacts of integrating variable renewables into power grids. Nature Energy. 6 (1), 72–83.