Assistant Professor, Ph.D.
Department of Computer Science
Texas Tech University Email: yong.chen[at]ttu.edu, Office: ENGCTR 315 Tel.: 806-834-0284, Fax.: 806-742-3519 Home / Teaching / Research /
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Mail: Department of Computer Science
Texas Tech University, Box 43104
Lubbock, TX 79409-3104
Thank you for visiting my website. I am an Assistant Professor in the Computer Science Department of the Texas Tech University (TTU) in Lubbock, Texas. I am the founding Director of the Data-Intensive Scalable Computing Laboratory (DISCL). I am also the Associate Director of the Cloud and Autonomic Computing site at TTU (CAC@TTU). My research focuses on data-intensive computing, parallel and distributed computing, high-performance computing, Cloud computing, computer architectures and systems software support for high-performance scientific computing/high-end enterprise computing.
Y. Lu, Y. Chen, Y. Zhuang, J.L. Liu and R. Thakur. Collective input/output under memory constraints The International Journal of High Performance Computing Applications IJHPCA , Vol. 2, Issue 3, pages 117–126, 2015. [PDF][BibTex][txt]
J.L. Liu and Y. Chen. Segmented In-Advance Data Analytics for Fast Scientific Discovery. IEEE Transactions on Cloud Computing . [PDF][BibTex][txt]
J. Zhou, Y. Chen, W. Wang and D. Meng. MAMS: A Highly Reliable Policy for Metadata Service. In the Proc. of the 44th International Conference on Parallel Processing (ICPP'15), 2015. (acceptance rate: 99/305=32.5%) [PDF][BibTex][txt]
D. Dai, P. Carns, R. Ross, J. Jenkins, K. Blauer, and Y. Chen. GraphTrek: Asynchronous Graph Traversal for Property Graph Based Metadata Management. In the Proc. of the IEEE International Conference on Cluster Computing, (Cluster'15), 2015. (acceptance rate: 38/157=24.2%)[PDF][BibTex][txt]
Y. Chen, Y. Lu, P. Amritkar, R. Thakur, and Y. Zhuang. Performance Model Directed Data Sieving for High Performance I/O. The Journal of Supercomputing, Volume 71, Issue 6, Page 2066-2090, 2015.[PDF][BibTex][txt]
D. Dai, Y. Chen, D. Kimpe, and R. Ross. Two-Choice Randomized Dynamic I/O Scheduler for Object Storage Systems. The Proceedings of the ACM/IEEE Supercomputing Conference (SC'14). (acceptance rate: 82/394=20.8%).[PDF][BibTex][txt]
J.L. Liu, B. Crysler, Y. Lu, and Y. Chen. Locality-driven High-level I/O Aggregation for Processing Scientific Datasets. In the Proceedings of The 2013 IEEE International Conference on Big Data, (BigData'13), 2013. (acceptance rate: 45/259=17.4%). [PDF][BibTex][txt]
J.L. Liu, Y. Chen, and Y. Zhuang. Hierarchical I/O Scheduling for Collective I/O. Accepted to appear at the 13th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), 2013. (acceptance rate: 57/257=22.18%). [PDF][BibTex][txt]
Y. Chen, H. Zhu, H. Jin, and X.-H. Sun. Algorithm-level Feedback-controlled Adaptive Data Prefetcher: Accelerating Data Access for High-Performance Processors. International Journal of the Parallel Computing (ParCo), Volume 38, Issues 10–11, Pages 533-551, 2012.[PDF][BibTex][txt]
Y. Chen, C. Chen, X.-H. Sun, W. D. Gropp, and R. Thakur. A Decoupled Execution Paradigm for Data-Intensive High-End Computing. In the Proc. of the IEEE International Conference on Cluster Computing 2012 (Cluster'12), 2012.[PDF][BibTex][txt]
C. Chen and Y. Chen. Dynamic Active Storage for High Performance I/O. Proc. of the 41st International Conference on Parallel Processing (ICPP'12), 2012. (acceptance rate: 53/187=28.3%). [PDF][BibTex][txt]
H. Song, Y. Yin, Y. Chen and X.-H. Sun. A Cost-Based Application-Specific Data Layout Scheme for Parallel File Systems. In the Proc. of the 20th International Symposium on High Performance Distributed Computing (HPDC'11), 2011. (acceptance rate: 22/170=12.9%). [PDF][BibTex][txt]
Y. Chen, H. Zhu, P. C. Roth, H. Jin and X.-H. Sun. Global-aware and Multi-order Context-based Prefetching for High-Performance Processors. In the International Journal of High Performance Computing Applications (IJHPCA'11), Vol. 25, No. 4, Pages 355-370, 2011. [PDF][BibTex][txt]
Y. Chen, X.-H. Sun, R. Thakur, P. C. Roth and W. Gropp. LACIO: A New Layout-Aware Collective I/O Strategy for Parallel I/O Systems. In the Proc. of IEEE International Parallel and Distributed Processing Symposium (IPDPS'11), 2011. (acceptance rate: 112/571=19.6%). [PDF][BibTex][txt]