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research article

A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services

Putnam, Andrew
•
Caulfield, Adrian M.
•
Chung, Eric S.
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2016
Communications Of The ACM

Datacenter workloads demand high computational capabilities, flexibility, power efficiency, and low cost. It is challenging to improve all of these factors simultaneously. To advance datacenter capabilities beyond what commodity server designs can provide, we designed and built a composable, reconfigurable hardware fabric based on field programmable gate arrays (FPGA). Each server in the fabric contains one FPGA, and all FPGAs within a 48-server rack are interconnected over a low-latency, high-bandwidth network. We describe a medium-scale deployment of this fabric on a bed of 1632 servers, and measure its effectiveness in accelerating the ranking component of the Bing web search engine. We describe the requirements and architecture of the system, detail the critical engineering challenges and solutions needed to make the system robust in the presence of failures, and measure the performance, power, and resilience of the system. Under high load, the large-scale reconfigurable fabric improves the ranking throughput of each server by 95% at a desirable latency distribution or reduces tail latency by 29% at a fixed throughput. In other words, the reconfigurable fabric enables the same throughput using only half the number of servers.

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Type
research article
DOI
10.1145/2996868
Web of Science ID

WOS:000387897700030

Author(s)
Putnam, Andrew
Caulfield, Adrian M.
Chung, Eric S.
Chiou, Derek
Constantinides, Kypros
Demme, John
Esmaeilzadeh, Hadi
Fowers, Jeremy
Gopal, Gopi Prashanth
Gray, Jan
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Date Issued

2016

Publisher

Assoc Computing Machinery

Published in
Communications Of The ACM
Volume

59

Issue

11

Start page

114

End page

122

Subjects

data center

•

FPGA

•

search enginee

•

reconfigurable computing

•

accelerator

Editorial or Peer reviewed

REVIEWED

Written at

OTHER

EPFL units
VLSC  
Available on Infoscience
January 24, 2017
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/133696
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