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Abstract
Energy consumption and total cost of ownership are daunting
challenges for Datacenters, because they scale disproportionately
with performance. Datacenters running financial
analytics may incur extremely high operational costs in order
to meet performance and latency requirements of their
hosted applications. Recently, ARM-based microservers have
emerged as a viable alternative to high-end servers, promising
scalable performance via scale-out approaches and low
energy consumption.
In this paper, we investigate the viability of ARM-based
microservers for option pricing, using the Monte Carlo and
Binomial Tree kernels. We compare an ARM-based microserver
against a state-of-the-art x86 server. We define
application-related but platform-independent energy and performance
metrics to compare those platforms fairly in the
context of datacenters for financial analytics and give insight
on the particular requirements of option pricing.
Our experiments show that through scaling out energyefficient
compute nodes within a 2U rack-mounted unit, an
ARM-based microserver consumes as little as about 60% of
the energy per option pricing compared to an x86 server,
despite having significantly slower cores. We also find that
the ARM microserver scales enough to meet a high fraction
of market throughput demand, while consuming up to 30%
less energy than an Intel server
Original language | English |
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Title of host publication | Proceedings of WHPCF’14: 7th Workshop on High Performance Computational Finance |
Place of Publication | New York |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 29-36 |
Number of pages | 8 |
ISBN (Electronic) | 9781479970278 |
DOIs | |
Publication status | Published - 16 Nov 2014 |
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Dive into the research topics of 'On the Viability of Microservers for Financial Analytics'. Together they form a unique fingerprint.Projects
- 4 Finished
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R6410CSC: NanoStreams: A Hardware and Software Stack for Real-Time Analytics on Fast Data Streams
Nikolopoulos, D. (PI), Spence, I. (CoI) & Woods, R. (CoI)
01/08/2013 → 28/02/2017
Project: Research
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R1330CSC: Abstraction-Level Energy Accounting and Optimization in Many-core Programming Languages
Nikolopoulos, D. (PI) & de Supinski, B. (CoI)
01/08/2012 → 28/04/2017
Project: Research