Back to Results
First PageMeta Content
Distributed computing architecture / MapReduce / Cloud computing / Cloud infrastructure / Data Intensive Computing / Apache Hadoop / Parallel ATA / Computing / Concurrent computing / Parallel computing


Applying Idealized Lower-Bound Runtime Models to Understand Inefficiencies in Data-Intensive Computing Elie Krevat∗ , Tomer Shiran∗ , Eric Anderson† , Joseph Tucek† , Jay J. Wylie† , Gregory R. Ganger∗ ∗ Ca
Add to Reading List

Document Date: 2012-02-07 18:33:12

Open Document

File Size: 296,79 KB

Share Result on Facebook

City

San Jose / /

Company

Storage Systems / Google / HP / /

Country

United States / /

Facility

Carnegie Mellon University / /

IndustryTerm

map-reduce systems / faster network / software stack / computing / map operator / well-tuned systems / actual hardware / /

Organization

Carnegie Mellon University / /

Person

Gregory R. Ganger / Tomer Shiran / Joseph Tucek / Jay J. Wylie / Eric Anderson / /

Position

author / representative / General / disk head / /

ProvinceOrState

California / /

PublishedMedium

Communications of the ACM / /

Technology

Ethernet / Operating Systems / Xeon processors / /

URL

http /

SocialTag