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The end of Dennard scaling and the slowing of Moore's Law has put the energy use of datacenters on an unsustainable path. Datacenters are already a significant fraction of worldwide electricity use, with application demand scaling at a rapid rate. We argue that substantial reductions in the carbon intensity of datacenter computing are possible with a software-centric approach: by making energy and carbon visible to application developers on a fine-grained basis, by modifying system APIs to make it possible to make informed trade offs between performance and carbon emissions, and by raising the level of application programming to allow for flexible use of more energy efficient means of compute and storage. We also lay out a research agenda for systems software to reduce the carbon footprint of datacenter computing.
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The War of the Efficiencies: Understanding the Tension between Carbon and Energy Optimization
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 ofthe electricity as constant, which was mostly true fora 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 ofeither perfor- mance or energy efficiency. In this paper, we discuss the trade-offs between energy efficiency and carbon efficiency in exploiting com- puting's flexibility and show that blindly optimizing for energy efficiency is not always the right approach.
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- PAR ID:
- 10433375
- Date Published:
- Journal Name:
- ACM Workshop on Hot Topics in Sustainable Computing
- Page Range / eLocation ID:
- 1-7
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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