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
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;
Conference_Titel :
Design Automation Conference (DAC), 2015 52nd ACM/EDAC/IEEE
Conference_Location :
San Francisco, CA
DOI :
10.1145/2744769.2744835