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Optimizing Web Browser on Many-Core Architectures

Authors: Lingjun Fan; Weisong Shi; Shibin Tang; Chenggang Yan; Dongrui Fan;

Optimizing Web Browser on Many-Core Architectures

Abstract

As more and more Web applications emerging on sever end today, the Web browser on client end has become a host of a variety of applications other than just rendering static Web pages. This leads to more and more performance requirements of a Web browser, for which user experience is very important. This situation may become more urgency when on handheld devices. Some efforts like redesign a new Web browser have been made to overcome this problem. In this paper, we address this issue by optimizing the main processes of the Web browser on a state-of-the-art 64-core architecture, Godson-T, which was developed at Chinese Academy of Sciences, as multi-/many-core architecture to be the mainstream processor in the upcoming years. We start a new core to process a new tab when facing up to intensive URL requests, and we use scratch-pad memory (SPM) of each core as a local buffer to store the HTML source data to be processed to reduce off-chip memory access and exploit more data locality, otherwise, we use DTA to transfer HTML data for backup. Experiments conducted on the cycle-accurate simulator show that, starting each tab process by a new core could obtain 5.7% to 50% speedup with different number of cores used to process corresponding URL requests, with on-chip scratchpad memory of each core used to store the HTML data, more speedup could be achieved when number of cores increase. Also, as Data Transfer Agent (DTA) used to transfer the HTML data, the backup of HTML data can get 2X to 5X speedups according to different data amount.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
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