DocumentCode
726279
Title
Energy efficient MapReduce with VFI-enabled multicore platforms
Author
Duraisamy, Karthi ; Kim, Ryan Gary ; Wonje Choi ; Guangshuo Liu ; Pande, Partha Pratim ; Marculescu, Radu ; Marculescu, Diana
Author_Institution
Sch. of EECS, Washington State Univ., Pullman, WA, USA
fYear
2015
fDate
8-12 June 2015
Firstpage
1
Lastpage
6
Abstract
In an era when power constraints and data movement are proving to be significant barriers for high-end computing, multicore architectures offer a low-power and highly scalable platform suitable for both data- and compute-intensive applications. MapReduce is a popular framework to facilitate the management and development of big-data workloads. In this work, we demonstrate that by using a wireless NoC-enabled Voltage Frequency Island (VFI)-based multicore platform it is possible to enhance the energy efficiency of MapReduce implementations without paying significant execution time penalties. Our experimental results show that for the benchmarks considered, the designed VFI system can achieve an average of 33.7% energy-delay product (EDP) savings over the standard baseline non-VFI mesh-based system while paying a maximum of 3.22% execution time penalty.
Keywords
Big Data; energy conservation; multiprocessing programs; parallel processing; software architecture; Big Data workloads; MapReduce; VFI-enabled multicore platforms; compute-intensive applications; data movement; data-intensive applications; energy efficient; energy-delay product; high-end computing; multicore architectures; power constraints; wireless NoC-enabled voltage frequency island; Benchmark testing; Energy efficiency; Multicore processing; Principal component analysis; Switches; Wireless communication; Big data; Multicore; NoC; VFI; Wireless; low power;
fLanguage
English
Publisher
ieee
Conference_Titel
Design Automation Conference (DAC), 2015 52nd ACM/EDAC/IEEE
Conference_Location
San Francisco, CA
Type
conf
DOI
10.1145/2744769.2744835
Filename
7167189
Link To Document