Proceedings Article10.1145/1272457.1272462
Parallel XML processing by work stealing
Wei Lu,Dennis Gannon +1 more
- 25 Jun 2007
- pp 31-38
52
TL;DR: A stealing-based dynamic load-balancing mechanism, called ThreadCrew, by which multiple threads are able to process the disjointed parts of the XML document in parallel with balanced load distribution, and a novel mechanism to trace the stealing actions is provided.
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Abstract: A language for semi-structured documents, XML has emerged as the core of the web services architecture, and is playing crucial roles in messaging systems, databases, and document processing. However, the processing of XML documents has been regarded as the performance bottleneck in most systems and applications. On the other side, the multicore processor, emerged as a solution for the clock-speed limitation of the modern CPUs, has been growingly prevalent. Leveraging the parallelism provided by the multicorere source to speedup the software execution is becoming the trend of the software development. In this paper, we present a parallel processing model for the XML document. The model is not designed just for a specific XML processing task, instead, it is a general model, by which we are able to explore various parallel XML document processing. The kernel of the model is a stealing-based dynamic load-balancing mechanism, called ThreadCrew, by which multiple threads are able to process the disjointed parts of the XML document in parallel with balanced load distribution. The model also provides a novel mechanism to trace the stealing actions, thus the equivalent sequential result can be gotten by gluing the multiple parallel-running results together. To show the feasibility and effectiveness of our approaches, we present our C# implementation of parallel XML serialization in this paper. Our empirical study shows our parallel XML serialization algorithm can improved the XML serializing performance significantly on a multicore machine.
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Citations
Computing with Nearby Mobile Devices: A Work Sharing Algorithm for Mobile Edge-Clouds
TL;DR: This paper presents a work-sharing model, called Honeybee, using an adaptation of the well-known work stealing method to load balance independent jobs among heterogeneous mobile nodes, able to accommodate nodes randomly leaving and joining the system.
126
Parallelization of XPath queries using multi-core processors: challenges and experiences
Rajesh Bordawekar,Lipyeow Lim,Oded Shmueli +2 more
- 24 Mar 2009
TL;DR: Experimental results demonstrate that the proposed parallelization strategies work very effectively in practice; for a majority of XPath queries under evaluation, the execution performance scaled linearly as the number of threads was increased.
Statistics-based parallelization of XPath queries in shared memory systems
Rajesh Bordawekar,Lipyeow Lim,Anastasios Kementsietsidis,Bryant Wei Lun Kok +3 more
- 22 Mar 2010
TL;DR: This paper proposes a novel, end-to-end parallelization framework that determines the optimal way of parallelizing an XML query, based on a statistics-based approach that relies both on the query specifics and the data statistics.
Mobile Crowd Computing with Work Stealing
Niroshinie Fernando,Seng Wai Loke,Wenny Rahayu +2 more
- 26 Sep 2012
TL;DR: This work explores the concept of 'work stealing' for crowd computing on an opportunistic network of mobile devices, for both machine and human computation.
Performance evaluation of parallel multithreaded A* heuristic search algorithm
TL;DR: This paper proposes a parallel generic approach based on multithreading for solving the 15 puzzle problem and finds that the parallel multithreaded A* heuristic search algorithm, in particular, outperforms the sequential approach in terms of time complexity and speedup.
23
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