Investigating the Limits of SOAP Performance for Scientific Computing
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
XML parsing: a threat to database performance
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Architectural Characterization of an XML-Centric Commercial Server Workload
ICPP '04 Proceedings of the 2004 International Conference on Parallel Processing
A Binary XML for Scientific Applications
E-SCIENCE '05 Proceedings of the First International Conference on e-Science and Grid Computing
Benchmarking XML processors for applications in grid web services
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Approaching a parallelized XML parser optimized for multi-coreprocessors
Proceedings of the 2007 workshop on Service-oriented computing performance: aspects, issues, and approaches
Reconfigurable content-based router using hardware-accelerated language parser
ACM Transactions on Design Automation of Electronic Systems (TODAES)
High performance XML parsing using parallel bit stream technology
CASCON '08 Proceedings of the 2008 conference of the center for advanced studies on collaborative research: meeting of minds
A Parallel Approach to XML Parsing
GRID '06 Proceedings of the 7th IEEE/ACM International Conference on Grid Computing
A 1 cycle-per-byte XML parsing accelerator
Proceedings of the 18th annual ACM/SIGDA international symposium on Field programmable gate arrays
On Improving Parallelized Network Coding with Dynamic Partitioning
IEEE Transactions on Parallel and Distributed Systems
Application-level voltage and frequency tuning of multi-phase program on the SCC
Proceedings of the 3rd International Workshop on Adaptive Self-Tuning Computing Systems
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As Extensible Markup Language (XML) becomes prevalent in cloud computing environments, it also introduces significant performance overheads. In this paper, we analyze the performance of XML parsing, identify that a significant fraction of the performance overhead is indeed incurred by memory data loading. To address this problem, we propose implementing memory-side acceleration on top of computation-side acceleration of XML parsing. To this end, we study the impact of memory-side acceleration on performance, and evaluate its implementation feasibility including bus bandwidth utilization, hardware cost, and energy consumption. Our results show that this technique is able to improve performance by up to 20% as well as produce up to 12.77% of energy saving when implemented in 32 nm technology.