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2020 – today
- 2024
[j29]Jianbin Fang, Jidong Zhai, Zheng Wang:
Editorial for the special issue on programming models and system software for High-Performance Computing (HPC) environments. CCF Trans. High Perform. Comput. 6(3): 241-242 (2024)- [j28]Mouzhi Yang, Peng Zhang, Jianbin Fang, Weifeng Liu, Chun Huang:
thSORT: an efficient parallel sorting algorithm on multi-core DSPs. CCF Trans. High Perform. Comput. 6(5): 503-518 (2024) - [j27]Tao Tang, Kai Lu, Lin Peng, Yingbo Cui, Jianbin Fang, Chun Huang, Ruibo Wang, Canqun Yang, Yifei Guo:
SNCL: a supernode OpenCL implementation for hybrid computing arrays. J. Supercomput. 80(7): 9471-9493 (2024) - [j26]Weiling Yang
, Jianbin Fang, Dezun Dong, Xing Su, Zheng Wang:
Optimizing Full-Spectrum Matrix Multiplications on ARMv8 Multi-Core CPUs. IEEE Trans. Parallel Distributed Syst. 35(3): 439-454 (2024) - [c46]Fugeng Zhu, Xinxin Qi, Peng Zhang, Jianbin Fang, Tao Tang, Yonggang Che, Kainan Yu, Jing Xie, Chun Huang, Jie Ren:
Optimizing Stencil Computation on Multi-core DSPs. ICPP 2024: 679-690 - [c45]Deshun Bi, Shengguo Li, Dezun Dong, Peng Zhang, Jianbin Fang:
Optimizing SpMV on Heterogeneous Multi-Core DSPs through Improved Locality and Vectorization. ICPP 2024: 1145-1155 - [c44]Kainan Yu, Xinxin Qi, Peng Zhang, Jianbin Fang, Dezun Dong, Ruibo Wang, Tao Tang, Chun Huang, Yonggang Che, Zheng Wang:
Optimizing General Matrix Multiplications on Modern Multi-core DSPs. IPDPS 2024: 964-975 - [c43]Haozhong Qiu, Chuanfu Xu, Jianbin Fang, Liang Deng, Jian Zhang, Qingsong Wang, Yue Ding, Zhe Dai, Yonggang Che, Shizhao Chen, Jie Liu:
Towards Scalable Unstructured Mesh Computations on Shared Memory Many-Cores. PPoPP 2024: 109-119 - [c42]Xinbiao Gan, Guang Wu, Shenghao Qiu, Feng Xiong, Jiaqi Si, Jianbin Fang, Dezun Dong, Chunye Gong, Tiejun Li, Zheng Wang:
GraphCube: Interconnection Hierarchy-aware Graph Processing. PPoPP 2024: 160-174 - 2023
- [j25]Wanrong Gao, Jianbin Fang, Chun Huang, Chuanfu Xu, Zheng Wang:
wrBench: Comparing Cache Architectures and Coherency Protocols on ARMv8 Many-Core Systems. J. Comput. Sci. Technol. 38(6): 1323-1338 (2023) - [j24]Jianbin Fang, Peng Zhang, Chun Huang, Tao Tang, Kai Lu, Ruibo Wang, Zheng Wang:
Programming bare-metal accelerators with heterogeneous threading models: a case study of Matrix-3000. Frontiers Inf. Technol. Electron. Eng. 24(4): 509-520 (2023) - [c41]Zhangyu Liu, Cheng Zhang, Huijun Wu, Jianbin Fang, Lin Peng, Guixin Ye, Zhanyong Tang:
Optimizing HPC I/O Performance with Regression Analysis and Ensemble Learning. CLUSTER 2023: 234-246 - [c40]Jintao Peng, Jianbin Fang, Jie Liu, Min Xie, Yi Dai, Bo Yang, Shengguo Li, Zheng Wang:
Optimizing MPI Collectives on Shared Memory Multi-Cores. SC 2023: 34:1-34:15 - [c39]Pengyu Wang, Weiling Yang, Jianbin Fang, Dezun Dong, Chun Huang, Peng Zhang, Tao Tang, Zheng Wang:
Optimizing Direct Convolutions on ARM Multi-Cores. SC 2023: 70:1-70:13 - 2022
- [j23]Kai Lu, Yaohua Wang, Yang Guo, Chun Huang, Sheng Liu, Ruibo Wang, Jianbin Fang, Tao Tang, Zhaoyun Chen, Biwei Liu, Zhong Liu, Yuanwu Lei, Haiyan Sun:
MT-3000: a heterogeneous multi-zone processor for HPC. CCF Trans. High Perform. Comput. 4(2): 150-164 (2022) - [j22]Donglin Chen, Xiang Gao, Chuanfu Xu, Siqi Wang, Shizhao Chen, Jianbin Fang, Zheng Wang:
FlowDNN: a physics-informed deep neural network for fast and accurate flow prediction. Frontiers Inf. Technol. Electron. Eng. 23(2): 207-219 (2022) - [c38]Wei Jiang, Bo Wang, Sheng Ma, Xiang Hou, Libo Huang, Yi Dai, Jianbin Fang:
PipeFB: An Optimized Pipeline Parallelism Scheme to Reduce the Peak Memory Usage. ICA3PP 2022: 590-604 - [i11]Jianbin Fang, Peng Zhang, Chun Huang, Tao Tang, Kai Lu, Ruibo Wang, Zheng Wang:
Programming Bare-Metal Accelerators with Heterogeneous Threading Models: A Case Study of Matrix-3000. CoRR abs/2210.12230 (2022) - 2021
- [j21]Jianbin Fang, Xiangke Liao, Chun Huang, Dezun Dong:
Performance Evaluation of Memory-Centric ARMv8 Many-Core Architectures: A Case Study with Phytium 2000+. J. Comput. Sci. Technol. 36(1): 33-43 (2021) - [j20]Jing Chen, Jianbin Fang, Weifeng Liu, Canqun Yang:
BALS: Blocked Alternating Least Squares for Parallel Sparse Matrix Factorization on GPUs. IEEE Trans. Parallel Distributed Syst. 32(9): 2291-2302 (2021) - [c37]Wanrong Gao, Jianbin Fang, Chun Huang, Chuanfu Xu, Zheng Wang:
Optimizing Barrier Synchronization on ARMv8 Many-Core Architectures. CLUSTER 2021: 542-552 - [c36]Pengyu Wang, Wanrong Gao, Jianbin Fang, Chun Huang, Zheng Wang:
Characterizing OpenMP Synchronization Implementations on ARMv8 Multi-Cores. HPCC/DSS/SmartCity/DependSys 2021: 669-676 - [c35]Weiling Yang, Jianbin Fang, Dezun Dong:
Characterizing Small-Scale Matrix Multiplications on ARMv8-based Many-Core Architectures. IPDPS 2021: 101-110 - [c34]Weiling Yang, Jianbin Fang, Dezun Dong, Xing Su, Zheng Wang:
LIBSHALOM: optimizing small and irregular-shaped matrix multiplications on ARMv8 multi-cores. SC 2021: 72 - 2020
- [j19]Jianbin Fang, Chun Huang, Tao Tang, Zheng Wang:
Parallel programming models for heterogeneous many-cores: a comprehensive survey. CCF Trans. High Perform. Comput. 2(4): 382-400 (2020) - [j18]Jing Chen, Jianbin Fang, Weifeng Liu, Tao Tang, Canqun Yang:
clMF: A fine-grained and portable alternating least squares algorithm for parallel matrix factorization. Future Gener. Comput. Syst. 108: 1192-1205 (2020) - [j17]Donglin Chen, Jianbin Fang, Chuanfu Xu, Shizhao Chen, Zheng Wang:
Characterizing Scalability of Sparse Matrix-Vector Multiplications on Phytium FT-2000+. Int. J. Parallel Program. 48(1): 80-97 (2020) - [j16]Zhaoyun Chen, Wei Quan, Mei Wen, Jianbin Fang, Jie Yu, Chunyuan Zhang, Lei Luo:
Deep Learning Research and Development Platform: Characterizing and Scheduling with QoS Guarantees on GPU Clusters. IEEE Trans. Parallel Distributed Syst. 31(1): 34-50 (2020) - [j15]Peng Zhang, Jianbin Fang, Canqun Yang, Chun Huang, Tao Tang, Zheng Wang:
Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures. IEEE Trans. Parallel Distributed Syst. 31(8): 1878-1896 (2020) - [c33]Guixin Ye, Zhanyong Tang, Huanting Wang, Dingyi Fang, Jianbin Fang, Songfang Huang, Zheng Wang:
Deep Program Structure Modeling Through Multi-Relational Graph-based Learning. PACT 2020: 111-123 - [c32]Wanrong Gao, Jianbin Fang, Chuanfu Xu, Chun Huang:
Dissecting the Phytium 2000+ Memory Hierarchy via Microbenchmarking. ACA 2020: 150-162 - [c31]Donglin Chen, Xiang Gao, Chuanfu Xu, Shizhao Chen, Jianbin Fang, Zhenghua Wang, Zheng Wang:
FlowGAN: A Conditional Generative Adversarial Network for Flow Prediction in Various Conditions. ICTAI 2020: 315-322 - [c30]Xiaosong Yu, Huihui Ma, Zhengyu Qu, Jianbin Fang, Weifeng Liu:
NUMA-Aware Optimization of Sparse Matrix-Vector Multiplication on ARMv8-Based Many-Core Architectures. NPC 2020: 231-242 - [i10]Peng Zhang, Jianbin Fang, Canqun Yang, Chun Huang, Tao Tang, Zheng Wang:
Optimizing Streaming Parallelism on Heterogeneous Many-Core Architectures: A Machine Learning Based Approach. CoRR abs/2003.04294 (2020) - [i9]Jianbin Fang, Chun Huang, Tao Tang, Zheng Wang:
Parallel Programming Models for Heterogeneous Many-Cores : A Survey. CoRR abs/2005.04094 (2020)
2010 – 2019
- 2019
- [j14]Donglin Chen, Jianbin Fang, Shizhao Chen, Chuanfu Xu, Zheng Wang:
Optimizing Sparse Matrix-Vector Multiplications on an ARMv8-based Many-Core Architecture. Int. J. Parallel Program. 47(3): 418-432 (2019) - [j13]Cheng Chen, Yunfei Du, Ke Zuo, Jianbin Fang, Canqun Yang:
Toward fault-tolerant hybrid programming over large-scale heterogeneous clusters via checkpointing/restart optimization. J. Supercomput. 75(8): 4226-4247 (2019) - [c29]Wenxu Zheng, Jianbin Fang, Chen Juan, Feihao Wu, Xiaodong Pan, Hao Wang, Xiaole Sun, Yuan Yuan, Min Xie, Chun Huang, Tao Tang, Zheng Wang:
Auto-Tuning MPI Collective Operations on Large-Scale Parallel Systems. HPCC/SmartCity/DSS 2019: 670-677 - [i8]Donglin Chen, Jianbin Fang, Chuanfu Xu, Shizhao Chen, Zheng Wang:
Characterizing Scalability of Sparse Matrix-Vector Multiplications on Phytium FT-2000+ Many-cores. CoRR abs/1911.08779 (2019) - 2018
- [j12]Xiangke Liao, Kai Lu, Canqun Yang, Jin-wen Li, Yuan Yuan, Ming-che Lai, Libo Huang, Ping-jing Lu, Jianbin Fang, Jing Ren, Jie Shen:
Moving from exascale to zettascale computing: challenges and techniques. Frontiers Inf. Technol. Electron. Eng. 19(10): 1236-1244 (2018) - [j11]Minquan Fang, Jianbin Fang, Weimin Zhang, Haifang Zhou, Jianxing Liao, Yuangang Wang:
Benchmarking the GPU memory at the warp level. Parallel Comput. 71: 23-41 (2018) - [j10]Xuhao Chen, Cheng Chen, Jie Shen, Jianbin Fang, Tao Tang, Canqun Yang, Zhiying Wang:
Orchestrating parallel detection of strongly connected components on GPUs. Parallel Comput. 78: 101-114 (2018) - [c28]Peng Zhang, Tao Tang, Jianbin Fang, Chun Huang, Canqun Yang, Zheng Wang:
MOCL: an efficient openCL implementation for the matrix-2000 architecture. CF 2018: 26-35 - [c27]Jie Ren, Xiaoming Wang, Jianbin Fang, Yansong Feng, Dongxiao Zhu, Zhunchen Luo, Jie Zheng, Zheng Wang:
Proteus: network-aware web browsing on heterogeneous mobile systems. CoNEXT 2018: 379-392 - [c26]Shizhao Chen, Jianbin Fang, Donglin Chen, Chuanfu Xu, Zheng Wang:
Adaptive Optimization of Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures. HPCC/SmartCity/DSS 2018: 649-658 - [c25]Peng Zhang, Jianbin Fang, Tao Tang, Canqun Yang, Zheng Wang:
Auto-tuning Streamed Applications on Intel Xeon Phi. IPDPS 2018: 515-525 - [c24]Qing Qin, Jie Ren, Jialong Yu, Hai Wang, Ling Gao, Jie Zheng, Yansong Feng, Jianbin Fang, Zheng Wang:
To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference. ISPA/IUCC/BDCloud/SocialCom/SustainCom 2018: 729-736 - [i7]Peng Zhang, Jianbin Fang, Tao Tang, Canqun Yang, Zheng Wang:
Tuning Streamed Applications on Intel Xeon Phi: A Machine Learning Based Approach. CoRR abs/1802.02760 (2018) - [i6]Shizhao Chen, Jianbin Fang, Donglin Chen, Chuanfu Xu, Zheng Wang:
Optimizing Sparse Matrix-Vector Multiplication on Emerging Many-Core Architectures. CoRR abs/1805.11938 (2018) - [i5]Qing Qin, Jie Ren, Jialong Yu, Ling Gao, Hai Wang, Jie Zheng, Yansong Feng, Jianbin Fang, Zheng Wang:
To Compress, or Not to Compress: Characterizing Deep Learning Model Compression for Embedded Inference. CoRR abs/1810.08899 (2018) - 2017
- [j9]Cheng Chen, Jianbin Fang, Tao Tang, Canqun Yang:
LU factorization on heterogeneous systems: an energy-efficient approach towards high performance. Computing 99(8): 791-811 (2017) - [j8]Xuhao Chen, Pingfan Li, Jianbin Fang, Tao Tang, Zhiying Wang, Canqun Yang:
Efficient and high-quality sparse graph coloring on GPUs. Concurr. Comput. Pract. Exp. 29(10) (2017) - [j7]Jing Chen, Jianbin Fang, Tao Tang, Canqun Yang:
多核/众核平台上推荐算法的实现与性能评估 (Implementation and Performance Evaluation of Recommender Algorithms Based on Multi-/Many-core Platforms). 计算机科学 44(10): 71-74 (2017) - [c23]Xi Yang, Jianbin Fang, Jing Chen, Chengkun Wu, Tao Tang, Kai Lu:
High Performance Coordinate Descent Matrix Factorization for Recommender Systems. Conf. Computing Frontiers 2017: 117-126 - [c22]Jing Chen, Jianbin Fang, Weifeng Liu, Tao Tang, Xuhao Chen, Canqun Yang:
Efficient and Portable ALS Matrix Factorization for Recommender Systems. IPDPS Workshops 2017: 409-418 - [c21]Jianbin Fang, Peng Zhang, Tao Tang, Chun Huang, Canqun Yang:
Implementing and Evaluating OpenCL on an ARMv8 Multi-Core CPU. ISPA/IUCC 2017: 860-867 - [c20]Pingfan Li, Xuhao Chen, Jie Shen, Jianbin Fang, Tao Tang, Canqun Yang:
High Performance Detection of Strongly Connected Components in Sparse Graphs on GPUs. PMAM@PPoPP 2017: 48-57 - 2016
- [j6]Jianbin Fang, Peng Zhang, Zhaokui Li, Tao Tang, Xuhao Chen, Cheng Chen, Canqun Yang:
Evaluating Multiple Streams on Heterogeneous Platforms. Parallel Process. Lett. 26(4): 1640002:1-1640002:18 (2016) - [c19]Canqun Yang, Cheng Chen, Tao Tang, Xuhao Chen, Jianbin Fang, Jingling Xue:
An Energy-Efficient Implementation of LU Factorization on Heterogeneous Systems. ICPADS 2016: 971-979 - [c18]Pingfan Li, Xuhao Chen, Zhe Quan, Jianbin Fang, Huayou Su, Tao Tang, Canqun Yang:
High Performance Parallel Graph Coloring on GPGPUs. IPDPS Workshops 2016: 845-854 - [c17]Zhaokui Li, Jianbin Fang, Tao Tang, Xuhao Chen, Cheng Chen, Canqun Yang:
Evaluating the Performance Impact of Multiple Streams on the MIC-Based Heterogeneous Platform. IPDPS Workshops 2016: 1341-1350 - [c16]Liang Deng, Jianbin Fang, Fang Wang, Hanli Bai:
Evaluating Multi-core and Many-Core Architectures through Accelerating an Alternating Direction Implicit CFD Solver. ISPDC 2016: 1-10 - [c15]Zhaokui Li, Jianbin Fang, Tao Tang, Xuhao Chen, Canqun Yang:
Streaming Applications on Heterogeneous Platforms. NPC 2016: 116-129 - [i4]Zhaokui Li, Jianbin Fang, Tao Tang, Xuhao Chen, Cheng Chen, Canqun Yang:
Evaluating the Performance Impact of Multiple Streams on the MIC-based Heterogeneous Platform. CoRR abs/1603.08619 (2016) - [i3]Zhaokui Li, Jianbin Fang, Tao Tang, Xuhao Chen, Canqun Yang:
Streaming Applications on Heterogeneous Platforms. CoRR abs/1608.03044 (2016) - 2015
- [j5]Yonggang Che, Chuanfu Xu, Jianbin Fang, Yongxian Wang, Zhenghua Wang:
Realistic Performance Characterization of CFD Applications on Intel Many Integrated Core Architecture. Comput. J. 58(12): 3279-3294 (2015) - [j4]Jianbin Fang, Ana Lucia Varbanescu, Xiangke Liao, Henk J. Sips:
Evaluating vector data type usage in OpenCL kernels. Concurr. Comput. Pract. Exp. 27(17): 4586-4602 (2015) - [c14]Minquan Fang, Yi Yu, Weimin Zhang, Heng Wu, Mingzhu Deng, Jianbin Fang:
High Performance Computing of Fast Independent Component Analysis for Hyperspectral Image Dimensionality Reduction on MIC-Based Clusters. ICPP Workshops 2015: 138-145 - [i2]Robert Andrawis, José David Bermeo, James Charles, Jianbin Fang, Jim Fonseca, Yu He, Gerhard Klimeck, Zhengping Jiang, Tillmann Kubis, Daniel F. Mejia, Daniel Lemus, Michael Povolotskyi, Santiago Alonso Pérez-Rubiano, Prasad Sarangapani, Lang Zeng:
NEMO5: Achieving High-end Internode Communication for Performance Projection Beyond Moore's Law. CoRR abs/1510.04686 (2015) - 2014
- [b1]Jianbin Fang:
Towards a Systematic Exploration of the Optimization Space for Many-Core Processors. Delft University of Technology, Netherlands, 2014 - [j3]Chuanfu Xu, Xiaogang Deng, Lilun Zhang, Jianbin Fang, Guangxue Wang, Yi Jiang, Wei Cao, Yonggang Che, Yongxian Wang, Zhenghua Wang, Wei Liu, Xinghua Cheng:
Collaborating CPU and GPU for large-scale high-order CFD simulations with complex grids on the TianHe-1A supercomputer. J. Comput. Phys. 278: 275-297 (2014) - [j2]Jianbin Fang, Henk J. Sips, Ana Lucia Varbanescu:
Aristotle: A performance impact indicator for the OpenCL kernels using local memory. Sci. Program. 22(3): 239-257 (2014) - [c13]Jianbin Fang, Henk J. Sips, Pekka Jääskeläinen, Ana Lucia Varbanescu:
Grover: Looking for Performance Improvement by Disabling Local Memory Usage in OpenCL Kernels. ICPP 2014: 162-171 - [c12]Chuanfu Xu, Lilun Zhang, Xiaogang Deng, Jianbin Fang, Guangxue Wang, Wei Cao, Yonggang Che, Yongxian Wang, Wei Liu:
Balancing CPU-GPU Collaborative High-Order CFD Simulations on the Tianhe-1A Supercomputer. IPDPS 2014: 725-734 - [c11]Jianbin Fang, Ana Lucia Varbanescu, Baldomero Imbernon, José M. Cecilia, Horacio Emilio Pérez Sánchez:
Parallel Computation of Non-Bonded Interactions in Drug Discovery: Nvidia GPUs vs. Intel Xeon Phi. IWBBIO 2014: 579-588 - [c10]Jianbin Fang, Henk J. Sips, Lilun Zhang, Chuanfu Xu, Yonggang Che, Ana Lucia Varbanescu:
Test-driving Intel Xeon Phi. ICPE 2014: 137-148 - 2013
- [j1]Jie Shen, Jianbin Fang, Henk J. Sips, Ana Lucia Varbanescu:
An application-centric evaluation of OpenCL on multi-core CPUs. Parallel Comput. 39(12): 834-850 (2013) - [c9]Jianbin Fang, Ana Lucia Varbanescu, Henk J. Sips:
Sesame: A User-Transparent Optimizing Framework for Many-Core Processors. CCGRID 2013: 70-73 - [c8]Jie Shen, Jianbin Fang, Henk J. Sips, Ana Lucia Varbanescu:
Performance Traps in OpenCL for CPUs. PDP 2013: 38-45 - [c7]Jianbin Fang, Ana Lucia Varbanescu, Jie Shen, Henk J. Sips:
ELMO: A User-Friendly API to Enable Local Memory in OpenCL Kernels. PDP 2013: 375-383 - [c6]Chuanfu Xu, Xiaogang Deng, Lilun Zhang, Yi Jiang, Wei Cao, Jianbin Fang, Yonggang Che, Yongxian Wang, Wei Liu:
Parallelizing a High-Order CFD Software for 3D, Multi-block, Structural Grids on the TianHe-1A Supercomputer. ISC 2013: 26-39 - [i1]Jianbin Fang, Ana Lucia Varbanescu, Henk J. Sips, Lilun Zhang, Yonggang Che, Chuanfu Xu:
An Empirical Study of Intel Xeon Phi. CoRR abs/1310.5842 (2013) - 2012
- [c5]Jianbin Fang, Ana Lucia Varbanescu, Jie Shen, Henk J. Sips, Gorkem Saygili, Laurens van der Maaten:
Accelerating Cost Aggregation for Real-Time Stereo Matching. ICPADS 2012: 472-481 - [c4]Jie Shen, Jianbin Fang, Henk J. Sips, Ana Lucia Varbanescu:
Performance Gaps between OpenMP and OpenCL for Multi-core CPUs. ICPP Workshops 2012: 116-125 - 2011
- [c3]Jianbin Fang, Ana Lucia Varbanescu, Henk J. Sips:
An Auto-tuning Solution to Data Streams Clustering in OpenCL. CSE 2011: 587-594 - [c2]Jianbin Fang, Ana Lucia Varbanescu, Henk J. Sips:
A Comprehensive Performance Comparison of CUDA and OpenCL. ICPP 2011: 216-225 - 2010
- [c1]Chuanfu Xu, Yonggang Che, Jianbin Fang, Zhenghua Wang:
Optimizing Adaptive Synchronization in Parallel Simulators for Large-scale Parallel Systems and Applications. CIT 2010: 131-138
Coauthor Index
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