NDLI: Towards sustainable in-situ server systems in the big data era

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Redundant memory mappings for fast access to large memories

Quantitative comparison of hardware transactional memory for Blue Gene/Q, zEnterprise EC12, Intel Core, and POWER8

Cost-effective speculative scheduling in high performance processors

Exploring the potential of heterogeneous von neumann/dataflow execution models

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Thermal time shifting

A variable warp size architecture

Manycore network interfaces for in-memory rack-scale computing

Towards sustainable in-situ server systems in the big data era

A scalable processing-in-memory accelerator for parallel graph processing

Profiling a warehouse-scale computer

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Flexible auto-refresh

Semantic locality and context-based prefetching using reinforcement learning

Architecting to achieve a billion requests per second throughput on a single key-value store server platform

Dynamic thread block launch

Volume 43, Issue 1, March 2015

Towards sustainable in-situ server systems in the big data era

Content Provider	ACM Digital Library
Author	Gu, Juncheng Liang, Xiaoyao Yuan, Jingling Li, Tao Song, Mingcong Liu, Longjun Li, Chao Hu, Yang
Abstract	Recent years have seen an explosion of data volumes from a myriad of distributed sources such as ubiquitous cameras and various sensors. The challenges of analyzing these geographically dispersed datasets are increasing due to the significant data movement overhead, time-consuming data aggregation, and escalating energy needs. Rather than constantly move a tremendous amount of raw data to remote warehouse-scale computing systems for processing, it would be beneficial to leverage in-situ server systems (InS) to pre-process data, i.e., bringing computation to where the data is located. This paper takes the first step towards designing server clusters for data processing in the field. We investigate two representative in-situ computing applications, where data is normally generated from environmentally sensitive areas or remote places that lack established utility infrastructure. These very special operating environments of in-situ servers urge us to explore standalone (i.e., off-grid) systems that offer the opportunity to benefit from local, self-generated energy sources. In this work we implement a heavily instrumented proof-of-concept prototype called InSURE: in-situ server systems using renewable energy. We develop a novel energy buffering mechanism and a unique joint spatio-temporal power management strategy to coordinate standalone power supplies and in-situ servers. We present detailed deployment experiences to quantify how our design fits with in-situ processing in the real world. Overall, InSURE yields 20%~60% improvements over a state-of-the-art baseline. It maintains impressive control effectiveness in under-provisioned environment and can economically scale along with the data processing needs. The proposed design is well complementary to today's grid-connected cloud data centers and provides competitive cost-effectiveness.
Starting Page	14
Ending Page	26
Page Count	13
File Format	PDF
ISSN	01635964
DOI	10.1145/2872887.2750381
Journal	ACM SIGARCH Computer Architecture News (CARN)
Volume Number	43
Issue Number	3
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1981-04-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Content Type	Text
Resource Type	Article

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