Cloud platforms have been focusing on reducing their carbon emissions by shifting
workloads across time and locations to when and where low-carbon energy is available …

Cloud platforms have been focusing on reducing their carbon emissions by shifting
workloads across time and locations to when and where low-carbon energy is available …

In a demand response scenario, coordinating multiple data centers with an electricity load
aggregator provides opportunities to minimize electricity cost and absorb the volatility in the …

In elastic cloud service systems, it is a challenge to evaluate and match the fluctuating
resource demand of workloads. Existing studies typically monitor workload characteristics …

High-Performance Computing (HPC) centers demand a lot of power, and continue to grow
through the Exascale era. This work establishes the need for a multi-tiered, feedback-driven …

Cloud platforms commonly exploit workload temporal flexibility to reduce their carbon
emissions. They suspend/resume workload execution for when and where the energy is …

The era of AI is witnessing a significant increase in energy consumption and carbon
emissions from the execution of large language models (LLMs). Due to memory and …

The evolving energy landscape has propelled energy communities to the forefront of
modern energy management. However, existing research has yet to explore the potential …

Data center demand is projected to increase dramatically over the coming decades, creating
concerns about their carbon footprint and motivating the design of methods that can scale …

Power consumption of data centers is rapidly becoming more prominent as the demand for
computation increases. Next-generation systems are expected to require significantly more …