Cost-Efficient Overclocking in Immersion-Cooled Datacenters

Jalili, Majid; Manousakis, Ioannis; Goiri, Íñigo; Misra, Pulkit A.; Raniwala, Ashish; Alissa, Husam A.; Ramakrishnan, Bharath; Tuma, Phillip E.; Belady, Christian; Fontoura, Marcus; Bianchini, Ricardo

doi:10.1109/isca52012.2021.00055

Cited by 32 publications

(9 citation statements)

References 42 publications

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“…To the best of our knowledge, we are the first to theoretically analyze and formulate the profit of warm water cooling, and adopt it into edge datacenters with strict requirements and critical challenges. Immersion cooling: Nowadays, immersion cooling has emerged as an efficient water cooling technique to hold a higher power density [2,38]. Sugon has exhibited its newly designed two-phase immersion cooling server at Supercomputing 2018 [43].…”

Section: Related Workmentioning

confidence: 99%

CoolEdge: hotspot-relievable warm water cooling for energy-efficient edge datacenters

Pei

Chen

Zhang

et al. 2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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As the computing frontier drifts to the edge, edge datacenters play a crucial role in supporting various real-time applications. Different from cloud datacenters, the requirements of proximity to end-users, high density, and heterogeneity, present new challenges to cool the edge datacenters efficiently. Although warm water cooling has become a promising cooling technique for this infrastructure, the one-size-fits-all cooling control would lower the cooling efficiency considerably because of the severe thermal imbalance across servers, hardware, and even inside one hardware component in an edge datacenter. In this work, we propose CoolEdge, a hotspot-relievable warm water cooling system for improving the cooling efficiency and saving costs of edge datacenters. Specifically, through the elaborate design of water circulations, CoolEdge can dynamically adjust the water temperature and flow rate for each heterogeneous hardware component to eliminate the hardwarelevel hotspots. By redesigning cold plates, CoolEdge can quickly disperse the chip-level hotspots without manual intervention. We further quantify the power saving achieved by the warm water

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Section: Related Workmentioning

confidence: 99%

CoolEdge: hotspot-relievable warm water cooling for energy-efficient edge datacenters

Pei

Chen

Zhang

et al. 2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

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“…The commonly used dielectric fluids have a much higher heat capacity than air [10], [24]. Most liquids used in immersion cooling are white mineral oil, engineered electric fluids, and other oils [16], [24]. There are two types of liquid immersion cooling: single-phase and two-phase, Fig.…”

Section: Immersion Coolingmentioning

confidence: 99%

“…The higher number of maintenance requests associated with immersion cooling impose additional operating costs. In addition, higher failure rates can degrade the components' lifetime, but immersion cooling can compensate for this degradation with lower junction temperatures [16]. Besides the number of maintenance requests, the maintenance procedure is more challenging with immersion cooling.…”

Section: System Maintenancementioning

confidence: 99%

“…But why it is not deployed in today's typical data centers? Maintenance and reliability, and specifically the lack of practical information on these aspects, are the primary concerns for adapting immersion cooling technologies [15], [16], [17], [18], [19], [20]. Increased number of IT equipment failures, liquid leakage, and liquid evaporation are the main challenges associated with its maintenance procedure, which also impose additional operational costs.…”

Section: Introductionmentioning

confidence: 99%

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Enough Hot Air: The Role of Immersion Cooling

Haghshenas¹,

Setz²,

Bloch³

et al. 2022

Preprint

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Air cooling is the traditional solution to chill servers in data centers. However, the continuous increase in global data center energy consumption combined with the increase of the racks' power dissipation calls for the use of more efficient alternatives. Immersion cooling is one such alternative. In this paper, we quantitatively examine and compare air cooling and immersion cooling solutions. The examined characteristics include power usage efficiency (PUE), computing and power density, cost, and maintenance overheads. A direct comparison shows a reduction of about 50% in energy consumption and a reduction of about two-thirds of the occupied space, by using immersion cooling. In addition, the higher heat capacity of used liquids in immersion cooling compared to air allows for much higher rack power densities. Moreover, immersion cooling requires less capital and operational expenditures. However, challenging maintenance procedures together with the increased number of IT failures are the main downsides. By selecting immersion cooling, cloud providers must trade-off the decrease in energy and cost and the increase in power density with its higher maintenance and reliability concerns. Finally, we argue that retrofitting an air-cooled data center with immersion cooling will result in high costs and is generally not recommended.

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“…CPU overclocking presents opportunities for substantial performance improvements on some workloads [17]. However, overclocking significantly increases power consumption and can shorten hardware lifetimes.…”

Section: Cpu Overclockingmentioning

confidence: 99%

SOL: safe on-node learning in cloud platforms

Wang

Crankshaw

Yadwadkar

et al. 2022

Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems

Self Cite

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Cloud platforms run many software agents on each server node. These agents manage all aspects of node operation, and in some cases frequently collect data and make decisions. Unfortunately, their behavior is typically based on pre-defined static heuristics or offline analysis; they do not leverage on-node machine learning (ML). In this paper, we first characterize the spectrum of node agents in Azure, and identify the classes of agents that are most likely to benefit from on-node ML. We then propose SOL, an extensible framework for designing ML-based agents that are safe and robust to the range of failure conditions that occur in production. SOL provides a simple API to agent developers and manages the scheduling and running of the agent-specific functions they write. We illustrate the use of SOL by implementing three ML-based agents that manage CPU cores, node power, and memory placement. Our experiments show that (1) ML substantially improves our agents, and (2) SOL ensures that agents operate safely under a variety of failure conditions. We conclude that ML-based agents show significant potential and that SOL can help build them. CCS CONCEPTS• Computer systems organization → Other architectures; Cloud computing; • Software and its engineering → Software creation and management.

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Cost-Efficient Overclocking in Immersion-Cooled Datacenters

Cited by 32 publications

References 42 publications

CoolEdge: hotspot-relievable warm water cooling for energy-efficient edge datacenters

CoolEdge: hotspot-relievable warm water cooling for energy-efficient edge datacenters

Enough Hot Air: The Role of Immersion Cooling

SOL: safe on-node learning in cloud platforms

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