Title :
Blast: Accelerating high-performance data analytics applications by optical multicast
Author :
Yiting Xia ; Ng, T. S. Eugene ; Sun, Xiaoye Steven
Author_Institution :
Rice Univ., Houston, TX, USA
fDate :
April 26 2015-May 1 2015
Abstract :
Multicast data dissemination is the performance bottleneck for high-performance data analytics applications in cluster computing, because terabytes of data need to be distributed routinely from a single data source to hundreds of computing servers. The state-of-the-art solutions for delivering these massive data sets all rely on application-layer overlays, which suffer from inherent performance limitations. This paper presents Blast, a system for accelerating data analytics applications by optical multicast. Blast leverages passive optical power splitting to duplicate data at line rate on a physical-layer broadcast medium separate from the packet-switched network core. We implement Blast on a small-scale hardware testbed. Multicast transmission can start 33ms after an application issues the request, resulting in a very small control overhead. We evaluate Blast´s performance at the scale of thousands of servers through simulation. Using only a 10Gbps optical uplink per rack, Blast achieves upto 102× better performance than the state-of-the-art solutions even when they are used over a non-blocking core network with a 400Gbps uplink per rack.
Keywords :
data analysis; multicast communication; optical fibre networks; Blast; bit rate 400 Gbit/s; cluster computing; high-performance data analytics application acceleration; massive data sets; multicast data dissemination; nonblocking core network; optical multicast communication; packet switched network core; Adaptive optics; Optical fiber networks; Optical packet switching; Optical receivers; Optical sensors; Optical switches; Unicast;
Conference_Titel :
Computer Communications (INFOCOM), 2015 IEEE Conference on
Conference_Location :
Kowloon
DOI :
10.1109/INFOCOM.2015.7218576