Recent innovation in large language models (LLMs), and their myriad use cases have
rapidly driven up the compute demand for datacenter GPUs. Several cloud providers and …

To mitigate climate change, we must reduce carbon emissions from hyperscale cloud
computing. We find that cloud compute servers cause the majority of emissions in a general …

The rapid evolution and widespread adoption of generative large language models (LLMs)
have made them a pivotal workload in various applications. Today, LLM inference clusters …

Today's cloud platforms handle server hardware failures by shutting down the affected
server and only turning it back online once it has been repaired by a technician. At cloud …

Cloud providers typically use air-based solutions for cooling servers in datacenters.
However, increasing transistor counts and the end of Dennard scaling will result in chips …

The increasing carbon emissions from cloud computing requires new methods to reduce its
environmental impact. We explore extending data center server lifetimes to reduce …

Cloud providers, like Amazon and Microsoft, must guarantee high availability for a large
fraction of their workloads. For this reason, they build datacenters with redundant …

Operating server components beyond their voltage and power design limit (ie, overclocking)
enables improving performance and lowering cost for cloud workloads. However …

As modern server GPUs are increasingly power intensive, better power management
mechanisms can significantly reduce the power consumption, capital costs, and carbon …

Renewable energy is becoming an important power source for data centers, especially with
the zero-carbon waste pledges made by big cloud providers. However, one of the main …