Hot Carbon focuses on understanding and addressing the negative environmental impacts of computing's success and computing's proliferation. The objective of the workshop is to foster insights and discussions as well as a growing community that focuses on sustainability of computer systems. We expect this includes innovative approaches to how we build, deploy, operate, and retire our creations, but perhaps even more. For example, software-driven hardware obsolescence that increases E-waste and embodied carbon suggests we must challenge computing's endemic upgrade and throwaway practices, and mindset.
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The Case of Unsustainable CPU Affinity
CPU affinity reduces data copies and improves data locality and has become a prevalent technique for high-performance programs in datacenters. This paper explores the tension between CPU affinity and sustainability. In particular, affinity settings ...
carbond: An Operating-System Daemon for Carbon Awareness
To reduce the carbon footprint of software, it is imperative that systems first become aware of their footprint. Despite various proposals to make software carbon aware via application-level development kits, we believe awareness of and adjustment to ...
Carbon-Aware Memory Placement
The carbon footprint of software activities is determined by embodied and operational emissions of hardware resources. This paper presents cMemento, a concept that enables operating systems to make carbon-aware memory placement decisions.
Main ...
EnergAt: Fine-Grained Energy Attribution for Multi-Tenancy
In the post-Moore's Law era, relying solely on hardware advancements for automatic performance gains is no longer feasible without increased energy consumption, due to the end of Dennard scaling. Consequently, computing accounts for an increasing ...
Towards Application Centric Carbon Emission Management
Reducing the carbon emission of computing systems has become a first-order optimization goal distinct from optimizing for performance or energy consumption. Carbon emissions are due to application execution on a target system (operational emissions) ...
Bringing Carbon Awareness to Multi-cloud Application Delivery
- Diptyaroop Maji,
- Ben Pfaff,
- Vipin P R,
- Rajagopal Sreenivasan,
- Victor Firoiu,
- Sreeram Iyer,
- Colleen Josephson,
- Zhelong Pan,
- Ramesh K Sitaraman
Data centers consume roughly 1--2% of the world's electricity, with the majority of it attributed to compute, making the computing industry a substantial source of greenhouse gas emissions. Resources in data centers typically focus on providing high ...
Myths and Misconceptions Around Reducing Carbon Embedded in Cloud Platforms
- Jialun Lyu,
- Jaylen Wang,
- Kali Frost,
- Chaojie Zhang,
- Celine Irvene,
- Esha Choukse,
- Rodrigo Fonseca,
- Ricardo Bianchini,
- Fiodar Kazhamiaka,
- Daniel S. Berger
Major cloud providers have stated public plans to lower their carbon emissions. Historically, this has meant focusing on emissions from producing the electricity consumed by datacenters. While work and challenges remain on this avenue, research and ...
Peeling Back the Carbon Curtain: Carbon Optimization Challenges in Cloud Computing
The increasing carbon emissions from cloud computing requires new methods to reduce its environmental impact. We explore extending data center server lifetimes to reduce embodied carbon emissions (from hardware manufacturing), rather than operational (...
Towards Carbon Footprint Management in Hybrid Multicloud
Enterprises today aspire to optimize the operating costs and carbon footprint (CFP) of their IT operations jointly without compromising their business imperatives. This has given rise to a hybrid approach in which enterprises retain the dynamic choice ...
An Agile Pathway Towards Carbon-aware Clouds
Climate change is a pressing threat to planetary well-being that can be addressed only by rapid near-term actions across all sectors. Yet, the cloud computing sector, with its increasingly large carbon footprint, has initiated only modest efforts to ...
Reducing the Carbon Impact of Generative AI Inference (today and in 2035)
Generative AI, exemplified in ChatGPT, Dall-E 2, and Stable Diffusion, are exciting new applications consuming growing quantities of computing. We study the compute, energy, and carbon impacts of generative AI inference. Using ChatGPT as an exemplar, ...
Carbon-Efficient Neural Architecture Search
This work presents a novel approach to neural architecture search (NAS) that aims to reduce energy costs and increase carbon efficiency during the model design process. The proposed framework, called carbon-efficient NAS (CE-NAS), consists of NAS ...
Towards a Methodology and Framework for AI Sustainability Metrics
- Tamar Eilam,
- Pedro Bello-Maldonado,
- Bishwaranjan Bhattacharjee,
- Carlos Costa,
- Eun Kyung Lee,
- Asser Tantawi
Recently, we are witnessing truly groundbreaking achievements using AI models, such as the much talked about generative large language models, the broader area of foundation models, and the wide range of applications with a tremendous potential to ...
Toward a Life Cycle Assessment for the Carbon Footprint of Data
The growing data economy features a complex ecosystem of organizations, individuals, and devices. With digital data exchange between entities becoming ubiquitous in modern society, there is a need for carbon cost estimates that span the entire life ...
On the Promise and Pitfalls of Optimizing Embodied Carbon
To halt further climate change, computing, along with the rest of society, must reduce, and eventually eliminate, its carbon emissions. Recently, many researchers have focused on estimating and optimizing computing's embodied carbon, i.e., from ...
Carbon-Efficient Design Optimization for Computing Systems
- Mariam Elgamal,
- Doug Carmean,
- Elnaz Ansari,
- Okay Zed,
- Ramesh Peri,
- Srilatha Manne,
- Udit Gupta,
- Gu-Yeon Wei,
- David Brooks,
- Gage Hills,
- Carole-Jean Wu
The world's push toward an environmentally sustainable society is highly dependent on the semiconductor industry, due to carbon footprints of global-scale sources such as computing systems for virtual and extended reality applications (VR and XR). ...
Does rate adaptation at daily timescales make sense?
Today, networking hardware is not fast enough to save energy with rate adaptation. Or is it? While we are not (yet) able to turn on and off line cards in milliseconds, we can do so a couple of times per day. The question is, does it make sense to save ...
Transient Internet of Things: Redesigning the Lifetime of Electronics for a More Sustainable Networked Environment
Mark Weiser predicted in 1991 that computing would lead to individuals interacting with countless computing devices, seamlessly integrating them into their daily lives until they disappear into the background [42]. However, achieving this seamless ...
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-...
When Does Saving Power Save the Planet?
The computing industry accounts for 2% of the world's emissions. Power-efficient computing is a frequent topic of research, but saving power does not always save the environment. Jevons' paradox states that resource savings from increases in ...
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