A Case for Specialized Processors for Scale-Out Workloads

Emerging scale-out workloads need extensive amounts of computational resources. However, datacenters using modern server hardware face physical constraints in space and power, limiting further expansion and requiring improvements in the computational density per server and in the per-operation energy. Continuing to improve the computational resources of the cloud while staying within physical constraints mandates optimizing server efficiency. In this work, we demonstrate that modern server processors are highly inefficient for running cloud workloads. To address this problem, we investigate the microarchitectural behavior of scale-out workloads and present opportunities to enable specialized processor designs that closely match the needs of the cloud.

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Al Mutaz Adileh, Anastasia Ailamaki, Mohammad Alisafaee, Babak Falsafi, Michael Ferdman, Ilknur Cansu Kaynak, Yusuf Onur Koçberber, Adrian Daniel Popescu, Stavros Volos
Ieee Computer Soc, 2014
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https://infoscience.epfl.ch/record/199758?ln=fr

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Clearing the Clouds: A Study of Emerging Workloads on Modern Hardware

Al Mutaz Adileh, Anastasia Ailamaki, Mohammad Alisafaee, Babak Falsafi, Michael Ferdman, Ilknur Cansu Kaynak, Yusuf Onur Koçberber, Adrian Daniel Popescu, Stavros Volos

Emerging scale-out cloud applications need extensive amounts of computational resources. However, data centers using modern server hardware face physical constraints in space and power, limiting further expansion and calling for improvements in the computational density per server and in the per-operation energy use. Therefore, continuing to improve the computational resources of the cloud while staying within physical constraints mandates optimizing server efficiency to ensure that server hardware closely matches the needs of scale-out cloud applications. We use performance counters on modern servers to study a wide range of cloud applications, finding that today’s predominant processor architecture is inefficient for running these workloads. We find that inefficiency comes from the mismatch between the application needs and modern processors, particularly in the organization of instruction and data memory systems and the processor core architecture. Moreover, while today’s predominant architectures are inefficient when executing scale-out cloud applications, we find that the current hardware trends further exacerbate the mismatch. In this work, we identify the key micro-architectural needs of cloud applications, calling for a change in the trajectory of server processors that would lead to improved computational density and power efficiency in data centers.

2011

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Clearing the Clouds: A Study of Emerging Scale-out Workloads on Modern Hardware

Al Mutaz Adileh, Anastasia Ailamaki, Mohammad Alisafaee, Babak Falsafi, Michael Ferdman, Ilknur Cansu Kaynak, Yusuf Onur Koçberber, Adrian Daniel Popescu, Stavros Volos

Emerging scale-out workloads require extensive amounts of computational resources. However, data centers using modern server hardware face physical constraints in space and power, limiting further expansion and calling for improvements in the computational density per server and in the per-operation energy. Continuing to improve the computational resources of the cloud while staying within physical constraints mandates optimizing server efficiency to ensure that server hardware closely matches the needs of scale-out workloads. We use performance counters on modern servers to study a wide range of scale-out workloads, finding that today’s predominant processor micro-architecture is inefficient for running these workloads. We find that inefficiency comes from the mismatch between the workload needs and modern processors, particularly in the organization of instruction and data memory systems and the processor core micro-architecture. Moreover, while today’s predominant micro-architecture is inefficient when executing scale-out workloads, we find that continuing the current trends will further exacerbate the inefficiency in the future. In this work, we identify the key micro-architectural needs of scale-out workloads, calling for a change in the trajectory of server processors that would lead to improved computational density and power efficiency in data centers.

2012

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Quantifying the Mismatch between Emerging Scale-Out Applications and Modern Processors

Al Mutaz Adileh, Anastasia Ailamaki, Mohammad Alisafaee, Babak Falsafi, Michael Ferdman, Dorde Jevdic, Ilknur Cansu Kaynak, Yusuf Onur Koçberber, Adrian Daniel Popescu, Stavros Volos

Emerging scale-out workloads require extensive amounts of computational resources. However, data centers using modern server hardware face physical constraints in space and power, limiting further expansion and calling for improvements in the computational density per server and in the per-operation energy. Continuing to improve the computational resources of the cloud while staying within physical constraints mandates optimizing server efficiency to ensure that server hardware closely matches the needs of scale-out workloads. In this work, we introduce CloudSuite, a benchmark suite of emerging scale-out workloads. We use performance counters on modern servers to study scale-out workloads, finding that today’s predominant processor microarchitecture is inefficient for running these workloads. We find that inefficiency comes from the mismatch between the workload needs and modern processors, particularly in the organization of instruction and data memory systems and the processor core microarchitecture. Moreover, while today’s predominant microarchitecture is inefficient when executing scale-out workloads, we find that continuing the current trends will further exacerbate the inefficiency in the future. In this work, we identify the key microarchitectural needs of scale-out workloads, calling for a change in the trajectory of server processors that would lead to improved computational density and power efficiency in data centers.

Association for Computing Machinery2012

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