The War of the Efficiencies: Understanding the Tension between Carbon and Energy Optimization

TL;DR

This paper explores the conflicting goals of energy efficiency and carbon reduction in data center operations, emphasizing that optimizing solely for energy efficiency may not minimize carbon emissions due to the variable carbon intensity of the electric grid.

Contribution

It highlights the need to consider carbon intensity variations in optimizing data center workloads, challenging the traditional focus on energy efficiency alone.

Findings

Energy-efficient operations may increase carbon emissions when grid carbon intensity varies.

Workload flexibility can reduce carbon emissions but may impact performance or energy efficiency.

Blindly optimizing for energy efficiency is not always optimal for carbon reduction.

Abstract

Major innovations in computing have been driven by scaling up computing infrastructure, while aggressively optimizing operating costs. The result is a network of worldwide datacenters that consume a large amount of energy, mostly in an energy-efficient manner. Since the electric grid powering these datacenters provided a simple and opaque abstraction of an unlimited and reliable power supply, the computing industry remained largely oblivious to the carbon intensity of the electricity it uses. Much like the rest of the society, it generally treated the carbon intensity of the electricity as constant, which was mostly true for a fossil fuel-driven grid. As a result, the cost-driven objective of increasing energy-efficiency -- by doing more work per unit of energy -- has generally been viewed as the most carbon-efficient approach. However, as the electric grid is increasingly powered by clean energy and is exposing its time-varying carbon intensity, the most energy-efficient operation is no longer necessarily the most carbon-efficient operation. There has been a recent focus on exploiting the flexibility of computing's workloads -- along temporal, spatial, and resource dimensions -- to reduce carbon emissions, which comes at the cost of either performance or energy efficiency. In this paper, we discuss the trade-offs between energy efficiency and carbon efficiency in exploiting computing's flexibility and show that blindly optimizing for energy efficiency is not always the right approach.