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 Shanjiang Tang

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Average citations per article2.06
Citation Count35
Publication count17
Publication years2012-2019
Available for download5
Average downloads per article146.80
Downloads (cumulative)734
Downloads (12 Months)382
Downloads (6 Weeks)109
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12 results found Export Results: bibtexendnoteacmrefcsv

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1 published by ACM
June 2019 HPDC '19: Proceedings of the 28th International Symposium on High-Performance Parallel and Distributed Computing
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 23,   Downloads (12 Months): 110,   Downloads (Overall): 110

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Cloud gaming has been very popular recently, but providing satisfactory gaming experiences to players at a modest cost is still challenging. Colocating several games onto one server could improve server utilization. To enable efficient colocations while providing Quality of Service (QoS) guarantees, a precise quantification of performance interference among colocated ...
Keywords: cloud gaming, game co-location, machine learning, performance interference, performance prediction

2
June 2019 International Journal of Parallel Programming: Volume 47 Issue 3, June 2019
Publisher: Kluwer Academic Publishers
Bibliometrics:
Citation Count: 0

Smith---Waterman algorithm (SW) is a popular dynamic programming algorithm widely used in bioinformatics for local biological sequence alignment. Due to the $$O(n^2)$$O(n2) high time and space complexity of SW and growing size of biological data, it is crucial to accelerate SW for high performance. In view of the GPU high ...
Keywords: APU, Heterogeneous processors, Load balancing, Smith---Waterman algorithm

3 published by ACM
August 2018 ICPP 2018: Proceedings of the 47th International Conference on Parallel Processing
Publisher: ACM
Bibliometrics:
Citation Count: 0
Downloads (6 Weeks): 3,   Downloads (12 Months): 82,   Downloads (Overall): 100

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In this paper, we propose a network-agnostic and convergence-invariant light-weight parallelization framework, namely GLP4NN, to accelerate the training of Deep Neural Networks (DNNs) by taking advantage of emerging GPU features, especially concurrent kernel execution. To determine the number of concurrent kernels on the fly, we design an analytical model in ...

4
November 2016 SC '16: Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis
Publisher: IEEE Press
Bibliometrics:
Citation Count: 3
Downloads (6 Weeks): 1,   Downloads (12 Months): 15,   Downloads (Overall): 126

Full text available: PDFPDF
Fairness and efficiency are two important concerns for users in a shared computer system, and there tends to be a tradeoff between them. Heterogeneous computing poses new challenging issues on the fair allocation of computational resources among users due to the availability of different kinds of computing devices (e.g., CPU ...
Keywords: APU, coupled CPU-GPU architecture, EMRF, fairness

5
November 2015 CLOUDCOM '15: Proceedings of the 2015 IEEE 7th International Conference on Cloud Computing Technology and Science (CloudCom)
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 0

In data-intensive cluster computing platforms such as Hadoop YARN, performance and fairness are two important factors for system design and optimizations. Many previous studies are either for performance or for fairness solely, without considering the tradeoff between performance and fairness. Recent studies observe that there is a tradeoff between performance ...

6
December 2014 CLOUDCOM '14: Proceedings of the 2014 IEEE 6th International Conference on Cloud Computing Technology and Science
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 1

Recent trends indicate that the pay-as-you-go Infrastructure-as-a-Service (IaaS) cloud computing has become a popular platform for big data processing applications, due to its merits of accessibility, elasticity and flexibility. However, the resource demands of processing workloads are often varying over time for individual users, implying that it is hard for ...
Keywords: Long-Term Resource Fairness, Multi-Resource Fairness, Pay-as-you-go, Cloud Computing, YARN, LTYARN, Spark

7 published by ACM
June 2014 ICS '14: Proceedings of the 28th ACM international conference on Supercomputing
Publisher: ACM
Bibliometrics:
Citation Count: 7
Downloads (6 Weeks): 4,   Downloads (12 Months): 20,   Downloads (Overall): 243

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Fair resource allocation is a key building block of any shared computing system. However, MemoryLess Resource Fairness (MLRF), widely used in many existing frameworks such as YARN, Mesos and Dryad, is not suitable for pay-as-you-use computing. To address this problem, this paper proposes Long-Term Resource Fairness (LTRF), a novel fair ...
Keywords: cloud computing, long-term resource fairness, mapreduce, yarn

8
August 2013 Euro-Par'13: Proceedings of the 19th international conference on Parallel Processing
Publisher: Springer-Verlag
Bibliometrics:
Citation Count: 1

MapReduce has become a widely used computing model for large-scale data processing in clusters and data centers. A MapReduce workload generally contains multiple jobs. Due to the general execution constraints that map tasks are executed before reduce tasks, different job execution orders in a MapReduce workload can have significantly different ...

9
May 2013 IPDPSW '13: Proceedings of the 2013 IEEE 27th International Symposium on Parallel and Distributed Processing Workshops and PhD Forum
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 3

Dynamic programming approach solves complex problems efficiently by breaking them down into simpler sub-problems, and is widely utilized in scientific computing. With the increasing data volume of scientific applications and development of multi-core/multi-processor hardware technologies, it is necessary to develop efficient techniques for parallelizing dynamic programming algorithms, particularly in multilevel ...
Keywords: dynamic programming, EasyHPS, multilevel computing environment, Directed Acyclic Graph Data Driven Model, task scheduling, load balancing

10
May 2012 IPDPSW '12: Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 0

This paper studies the speedup for multi-level parallel computing. Two models of parallel speedup are considered, namely, fixed-size speedup and fixed-time speedup. Based on these two models, we start with the speedup formulation that takes into account uneven allocation and communication latency, and gives an accurate estimation. Next, we propose ...
Keywords: E-Amdahl's Law, E-Gustafson's Law, Multi-Level Parallel Computing

11
May 2012 IPDPSW '12: Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum
Publisher: IEEE Computer Society
Bibliometrics:
Citation Count: 1

Load balancing is a challenging work for parallel dynamic programming due to its intrinsically strong data dependency. Two issues are mainly involved and equally important, namely, the partitioning method as well as scheduling and distribution policy of subtasks. However, researchers take into account their load balancing strategies primarily from the ...
Keywords: Dynamic Programming, DAG Data Driven Model, Adaptive Data Refinement, Load Balancing

12
May 2012 IEEE Transactions on Parallel and Distributed Systems: Volume 23 Issue 5, May 2012
Publisher: IEEE Press
Bibliometrics:
Citation Count: 4

Dynamic programming (DP) is a popular and efficient technique in many scientific applications such as computational biology. Nevertheless, its performance is limited due to the burgeoning volume of scientific data, and parallelism is necessary and crucial to keep the computation time at acceptable levels. The intrinsically strong data dependency of ...
Keywords: Dynamic programming, Easypdp, DAG data driven model, fault tolerance, DAG pattern, multicore, block cycle.



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