DocumentCode :
183030
Title :
DataCenter 2020: Near-memory acceleration for data-oriented applications
Author :
Doller, Edward ; Akel, Ameen ; Wang, Jiacheng ; Curewitz, Ken ; Eilert, Sean
Author_Institution :
Memory Syst. Archit. R&D, Micron Technol. Inc., Folsom, CA, USA
fYear :
2014
fDate :
10-13 June 2014
Firstpage :
1
Lastpage :
4
Abstract :
In the years between now and 2020, we should expect continued exponential data growth [15][16]. A number of ongoing advances in storage: the transition to solid-state drives (SSDs), the scaling of NAND flash capacity, and advanced silicon packaging techniques will dramatically increase the capacity of storage subsystems over the same timeframe. This will significantly reduce the ratio of storage bandwidth to storage density. Consequently, the majority of data in 2020 will either be cold or will require near-memory acceleration to pull rich information out of the sea of big data. We argue that, increasingly over time, value lies not merely in the size of the data, but rather in what one can do with it.
Keywords :
NAND circuits; electronics packaging; elemental semiconductors; flash memories; silicon; DataCenter 2020; NAND flash memory capacity; SSD; Si; advanced silicon packaging technique; data-oriented application; near-memory acceleration; solid-state drive; storage density; Acceleration; Bandwidth; Computer architecture; Databases; Engines; Hardware; Software;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
VLSI Circuits Digest of Technical Papers, 2014 Symposium on
Conference_Location :
Honolulu, HI
Print_ISBN :
978-1-4799-3327-3
Type :
conf
DOI :
10.1109/VLSIC.2014.6858357
Filename :
6858357
Link To Document :
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