DocumentCode :
2271712
Title :
Transforming memory systems: Optimizing for client value on emerging workloads
Author :
Nowka, Kevin J.
Author_Institution :
IBM Res. - Austin, Austin, TX, USA
fYear :
2012
fDate :
23-25 April 2012
Firstpage :
1
Lastpage :
2
Abstract :
Computing systems are increasingly being transformed to better satisfy the demands of cloud computing, Big Data, and deep, sophisticated analytics applications. These applications are driving an explosion in volume of data, acceleration of the rate at which this data must be consumed, and an increase in the diversity of sources of data. Memory system architectures and designs are perhaps most affected by these changes in computing applications. The disruptive trends resulting from these new application spaces lead to significant capacity, power, and cost pressures on computing systems. These trends will lead to changes in traditional memory technologies and memory systems and represent an opportunity of new memory technologies and organizations. Storage class memory is particularly suited to a significant set of these application spaces.
Keywords :
memory architecture; big data; client value; cloud computing; computing systems; emerging workloads; memory system architectures; memory system design; sophisticated analytics applications; storage class memory; Abstracts; Memory architecture; Random access memory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
VLSI Design, Automation, and Test (VLSI-DAT), 2012 International Symposium on
Conference_Location :
Hsinchu
ISSN :
PENDING
Print_ISBN :
978-1-4577-2080-2
Type :
conf
DOI :
10.1109/VLSI-DAT.2012.6212609
Filename :
6212609
Link To Document :
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