Data Base Machines are Coming, Data Base Machines are Coming!

Hsiao,

doi:10.1109/mc.1979.1658647

Cited by 29 publications

(2 citation statements)

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“…Moving data processing functions closer to the storage device has its origins in the database machines of the 1970s and 1980s [Hsiao 1979;Ozkarahan 1975;Su 1979]. It was studied briefly in the late 1990s and early 2000s when active disk drives were introduced.…”

Section: Active Storagementioning

confidence: 99%

Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters

Kaitoua

Hajj

Saghir

et al. 2014

ACM Trans. Archit. Code Optim.

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In this article, we propose new extensions to Hadoop to enable clusters of reconfigurable active solid-state drives (RASSDs) to process streaming data from SSDs using FPGAs. We also develop an analytical model to estimate the performance of RASSD clusters running under Hadoop. Using the Hadoop RASSD platform and network simulators, we validate our design and demonstrate its impact on performance for different workloads taken from Stanford's Phoenix MapReduce project. Our results show that for a hardware acceleration factor of 20×, compute-intensive workloads processing 153MB of data can run up to 11× faster than a standard Hadoop cluster.

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Section: Active Storagementioning

confidence: 99%

Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters

Kaitoua

Hajj

Saghir

et al. 2014

ACM Trans. Archit. Code Optim.

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show abstract

“…The approach of moving the data processing functions closer to the storage device has its origins in the database machines of the 1970's and 1980's [4][8] [10], and was studied briefly in the late 1990's and early 2000's through the introduction of active disk drives. These devices consisted of hard disk drives tightly coupled with local disk processors [9].…”

Section: Related Workmentioning

confidence: 99%

An operating system for a Reconfigurable Active SSD processing node

Ali

Jomaa

Romanous

et al. 2012

2012 19th International Conference on Telecommunications (ICT)

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We have recently proposed a Distributed Reconfigurable Active SSD computation platform (RASSD) for processing data-intensive applications at the storage node itself, without having to move data over slow networks. In this paper, we present the design of an operating system (OS) for the RASSD node. RASSD OS is a multitasking real-time operating system that runs on the 32-bit MicroBlaze ® soft processor core available for Xilinx ® FPGA's. We discuss in this paper our OS design features which include initializing the node and configuring the different components of the RASSD node, monitoring the node's activities, and processing middleware requests. RASSD OS provides a set of services to the middleware through which it hides the low-level details of the node's hardware architecture. We describe the functions essential for the data-intensive processing within the RASSD node using examples that capture the common states of the node and various possible requests.

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2008

High‐Performance Parallel Database Processing and Grid Databases

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Data Base Machines are Coming, Data Base Machines are Coming!

Cited by 29 publications

References 1 publication

Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters

Hadoop Extensions for Distributed Computing on Reconfigurable Active SSD Clusters

An operating system for a Reconfigurable Active SSD processing node

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