Peer Reviewed Conferences and Journals
[ASPLOS'2024] Wei Niu, Md Musfiqur Rahman Sanim, Zhihao Shu, Jiexiong Guan, Xipeng Shen, Miao Yin, Gagan Agrawal, Bin Ren, SmartMem: Layout Transformation Elimination and Adaptation for Efficient DNN Execution on Mobile, International Conference on Architectural Support for Programming Languages and Operating Systems, 2024.
[ASPLOS'2024] Wei Niu, Gagan Agrawal, Bin Ren, SoD^2: Statically Optimizing Dynamic Deep Neural Network Execution, International Conference on Architectural Support for Programming Languages and Operating Systems, 2024.
[IPDPS'2024] Malith Jayaweera, Yanyu Li, Yanzhi Wang, Bin Ren, David Kaeli, DEFCON: Deformable Convolutions Leveraging Interval Search and GPU Texture Hardware, 38th IEEE International Parallel & Distributed Processing Symposium (IPDPS), 2024.
[ICLR'2024] Gen Li, Lu Yin, Jie Ji, Wei Niu, Minghai Qin, Bin Ren, Linke Guo, Shiwei Liu, Xiaolong Ma, NeurRev: Train Better Sparse Neural Network Practically via Neuron Revitalization, The Twelfth International Conference on Learning Representations (ICLR), 2024.
[USENIX ATC'2023] Hsin-Hsuan Sung, Jou-An Chen, Wei Niu, Jiexiong Guan, Bin Ren, Xipeng Shen, Decentralized Application-Level Adaptive Scheduling for Multi-Instance DNNs on Open Mobile Devices, USENIX Annual Technical Conference, 2023. (acceptance rate: 65/353=18.4%) [to appear]
[PPoPP'2023] Zhen Peng, Minjia Zhang, Kai Li, Ruoming Jin, Bin Ren, iQAN: Fast and Accurate Vector Search with Efficient Intra-Query Parallelism on Multi-Core Architectures,The 28th ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming, 2023.
[ACM TORS'2023] Dong Li, Ruoming Jin, Zhenming Liu, Bin Ren, Jing Gao, Zhi Liu, On Item-Sampling Evaluation for Recommender System, ACM Transactions on Recommender Systems.
[ICDM'2023] Hao Zhang, Malith Jayaweera, Bin Ren, Yanzhi Wang, Sucheta Soundarajan, Unfairness in Distributed Graph Frameworks, IEEE International Conference on Data Mining (ICDM), 2023 (Short Paper)
[CVPR'2023-Highlight] Gen Li, Jie Ji, Minghai Qin, Wei Niu, Bin Ren, Fatemeh Afghah, Linke Guo, Xiaolong Ma, Towards High-Quality and Efficient Video Super-Resolution via Spatial-Temporal Data Overfitting, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR, 2023, top 2.5%).
[CVPR'2023] Changdi Yang, Pu Zhao, Yanyu Li, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Bin Ren, Xue Lin, Yanzhi Wang, Pruning Parameterization with Bi-level Optimization for Efficient Semantic Segmentation on the Edge, in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR, 2023).
[AAAI'2023] Dong Li, Ruoming Jin, Zhenming Liu, Bin Ren, Jing Gao, and Zhi Liu, Towards Reliable Item Sampling for Recommendation Evaluation, Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 (Acceptance Rate: TBA).
[AAAI'2023] Yanyu Li, Changdi Yang, Pu Zhao, Geng Yuan, Wei Niu, Jiexiong Guan, Hao Tang, Minghai Qin, Bin Ren, Xue Lin, and Yanzhi Wang, Towards Real-Time Segmentation on the Edge, Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 (Acceptance Rate: TBA).
[NeurIPS'2022] Zifeng Wang, Zheng Zhan, Yifan Gong, Geng Yuan, Wei Niu, Tong Jian, Bin Ren, Stratis Ioannidis, Yanzhi Wang, Jennifer Dy, SparCL: Sparse Continual Learning on the Edge, Thirty-Sixth Conference on Neural Information Processing Systems, 2022
[ACM Computing Surveys'2022] Jou-An Chen, Wei Niu, Bin Ren, Yanzhi Wang, Xipeng Shen, Survey: Exploiting Data Redundancy for Optimization of Deep Learning, ACM Computing Surveys, 2022.
[MSN'2022] Junjie Wang, Jiexiong Guan, Y.Alicia Hong, Hong Xue, Shuangquan Wang, Zhenming Liu, Bin Ren, and Gang Zhou, Towards socially acceptable food type recognition, The 18th International Conference on Mobility, Sensing and Networking (MSN), 2022
[MICRO'2022] Wei Niu, Jiexiong Guan, Xipeng Shen, Yanzhi Wang, Gagan Agrawal, Bin Ren, GCD^2: A Globally Optimizing Compiler for Mapping DNNs to Mobile DSPs, 55th IEEE/ACM International Symposium on Microarchitecture (MICRO), 2022.
[ECCV'2022] Yushu Wu, Yifan Gong, Pu Zhao, Yanyu Li, Zheng Zhan, Wei Niu, Hao Tang, Minghai Qin, Bin Ren, and Yanzhi Wang, Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution, in Proc. of European Conference on Computer Vision (ECCV), 2022.
[ECCV'2022] Zhenglun Kong, Peiyan Dong, Xiaolong Ma, Xin Meng, Wei Niu, Mengshu Sun, Xuan Shen, Geng Yuan, Bin Ren, Hao Tang, Minghai Qin, and Yanzhi Wang, SPViT: Enabling Faster Vision Transformers via Soft Token Pruning, in Proc. of European Conference on Computer Vision (ECCV), 2022.
[IPDPS'2022]Qihan Wang, Bin Ren, Jie Chen, Robert G. Edwards, MICCO: An Enhanced Multi-GPU Scheduling Framework for Many-Body Correlation Functions, The 36th IEEE International Parallel & Distributed Processing Symposium (IPDPS), June 2022. (Acceptance rate of the 1st round: 9.7% = 46/474).
[TACO'2022] Qihan Wang, Zhen Peng, Bin Ren, Jie Chen, Robert G. Edwards, MemHC: An Optimized GPU Memory Management Framework for Accelerating Many-body Correlation, ACM Transactions on Architecture and Code Optimization (ACM TACO), June 2022. (Original Work, invited to HiPEAC'23)
[TECS'2022] Geng Yuan, Mengshu Sun, Wei Niu, Zhengang Li, Yuxuan Cai, Yanyu Li, Jun Liu, Weiwen Jiang, Xue Lin, Bin Ren, Xulong Tang, Yanzhi Wang, Mobile or FPGA? A Comprehensive Evaluation on Energy Efficiency and a Unified Optimization Framework, ACM Transactions on Embedded Computing Systems (TECS).
[ISQED'2022–invited] Xiaolong Ma, Geng Yuan, Zhengang Li, Wei Niu, Yifan Gong, Tianyun Zhang, Zheng Zhan, Pu Zhao, Jian Tang, Xue Lin, Bin Ren, Yanzhi Wang, A General Pruning Framework Enabling Real-Time Inference on Resource-Limited Mobile Devices, in Proceedings of the 23rd International Symposium on Quality Electronic Design (ISQED), April 2022.
[TPDS'2022] Mert Hidayetoglu, Tekin Bicer, Simon Garcia de Gonzalo, Bin Ren, Doga Gursoy, Rajkumar Kettimuthu, Ian T. Foster, Wen-Mei W. Hwu, MemXCT: Design, Optimization, Scaling, and Reproducibility of X-Ray Tomography Imaging, IEEE Transactions on Parallel and Distributed Systems. 33(9): 2014-2031 (2022).
[TODAES'2021] Yifan Gong*, Geng Yuan*, Zheng Zhan, Wei Niu, Zhengang Li, Pu Zhao, Yuxuan Cai, Sijia Liu, Bin Ren, Xue Lin, Xulong Tang, and Yanzhi Wang, Automatic mapping of the best-suited DNN pruning schemes for real-time mobile acceleration, ACM Transactions on Design Automation of Embedded Systems.
[NeurIPS'2021 Spotlight: Top 3%] Geng Yuan, Xiaolong Ma, Wei Niu, Zhengang Li, Zhenglun Kong, Ning Liu, Yifan Gong, Zheng Zhan, Chaoyang He, Qing Jin, Siyue Wang, Minghai Qin, Bin Ren, Yanzhi Wang, Sijia Liu, Xue Lin, MEST: Accurate and Fast Memory-Economic Sparse Training Framework on the Edge, Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), December 2021. (Acceptance rate: 2344/9122 = 26%, Spotlight 3%)
[HiPC'2021] Qihan Wang, Wei Niu, Li Chen, Ruoming Jin, Bin Ren, HEALS: A Parallel eALS Recommendation System on CPU/GPU Heterogeneous Platforms, The 28th IEEE International Conference on High Performance Computing, Data, & Analytics (HiPC), December 2021. (Acceptance rate: 23%)
[ICCV'2021] Zheng Zhan, Yifan Gong, Pu Zhao, Geng Yuan, Wei Niu, Yushu Wu, Tianyun Zhang, Malith Jayaweera, David Kaeli, Bin Ren, Xue Lin, Yanzhi Wang, Achieving On-Mobile Real-Time Super-Resolution With Neural Architecture and Pruning Search, International Conference on Computer Vision (ICCV), October 2021. (Acceptance rate: 25.9%)
[ESEC/FSE'2021] Jialiang Tan*, Yu Chen*, Zhenming Liu, Bin Ren, Shuaiwen Leon Song, Xipeng Shen, and Xu Liu (*equal contribution), Toward Efficient Interactions between Python and Native Libraries, 29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, August 2021. (Acceptance rate: 97/396 = 24.5%)
[PLDI'2021] Wei Niu, Jiexiong Guan, Yanzhi Wang, Gagan Agrawal, and Bin Ren, DNNFusion: Accelerating Deep Neural Networks Execution with Advanced Operator Fusion, 42nd ACM SIGPLAN Conference on Programming Language Design and Implementation, June 2021. (Acceptance rate: 87/320 = 27%)
[TPAMI'2021] Wei Niu*, Zhenggang Li*, Xiaolong Ma, Peiyan Dong, Gang Zhou, Xuehai Qian, Xue Lin, Yanzhi Wang, and Bin Ren, GRIM: A General, Real-Time Deep Learning Inference Framework for Mobile Devices based on Fine-Grained Structured Weight Sparsity, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021 (impact factor: 17.86).
[ICS'2021] Chengming Zhang, Geng Yuan, Wei Niu, Jiannan Tian, Sian Jin, Donglin Zhuang, Zhe Jiang, Yanzhi Wang, Bin Ren, Shuaiwen Leon Song, and Dingwen Tao, ClickTrain: Efficient and Accurate End-to-End Deep LearningTraining via Fine-Grained Architecture-Preserving Pruning, 35th ACM International Conference on Supercomputing, June 2021. (Acceptance Rate: 38/157 = 24%)
[Smart Health'2021] Shuangquan Wang, Gang Zhou, Jiexiong Guan, Yongsen Ma, Zhenming Liu, Bin Ren, Hongyang Zhao, Amanda Watson, and Woosub Jung, Inferring Food Types through Sensing and Characterizing Mastication Dynamics, Elsevier Smart Health, 2021.
[CVPR'2021 Oral Paper: top 5%] Zhengang Li, Geng Yuan, Wei Niu, Yanyu Li, Pu Zhao, Yuxuan Cai, Xuan Shen, Zheng Zhan, Zhenglun Kong, Qing Jin, Zhiyu Chen, Sijia Liu, Kaiyuan Yang, Yanzhi Wang, Bin Ren, and Xue Lin, NPAS: A compiler-aware framework of unified network pruning and architecture search for beyond real-time mobile acceleration. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021. Acceptance rate: 21.2% (1593/7500)
[CACM'2021] Hui Guan, Shaoshan Liu, Xiaolong Ma, Wei Niu, Bin Ren, Xipeng Shen, Yanzhi Wang, Pu Zhao (authors in alphabet order), CoCoPIE: Making Mobile AI Sweet as PIE - Compression-Compilation Co-Design Goes a Long Way, Communications of the ACM (CACM), 2021.
[DAC'2021] Pu Zhao, Geng Yuan, Yuxuan Cai, Wei Niu, Qi Liu, Wujie Wen, Bin Ren, Yanzhi Wang, and Xue Lin, Neural Pruning Search for Real-Time Object Detection of Autonomous Vehicles, 57th Annual Design Automation Conference (DAC), 2021.
[ASP-DAC'2021] Hongjia Li, Geng Yuan, Wei Niu, Yuxuan Cai, Mengshu Sun, Zhengang Li, Bin Ren, Xue Lin, and Yanzhi Wang, Real-Time Mobile Acceleration of DNNs: From Computer Vision to Medical Applications, in Proceeding of Asia and South Pacific Design Automation Conference (ASP-DAC), 2021.
[AAAI'2021] Wei Niu*, Mengshu Sun*, Zhengang Li*, Jou-An Chen, Jiexiong Guan, Xipeng Shen, Yanzhi Wang, Xue Lin, and Bin Ren (*equal contribution), Achieving Real-Time Execution of 3D Convolutional Neural Networks on Mobile Devices, Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021 (Acceptance Rate: 20.9%).
[AAAI'2021] Yuxuan Cai, Hongjia Li, Geng Yuan, Wei Niu, Yanyu Li, Xulong Tang, Bin Ren, and Yanzhi Wang, YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design, Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021 (Acceptance Rate: 20.9%).
[Smart Health'2020] Qihan Wang, Gang Zhou, Zhenming Liu, and Bin Ren, Building a Skeleton-based 3D Body Model with Angle Sensor Data, Elsevier Smart Health, 2020.
[SC'2020] Mert Hidayetoglu, Tekin Bicer, Simon Garcia de Gonzalo, Bin Ren, Vincent De Andrade, Doga Gursoy, Rajkumar Kettimuthu, Ian Foster, and Wen-mei Hwu, Petascale XCT: 3D Image Reconstruction with Hierarchical Communications on Multi-GPU Nodes, The 2020 ACM International Conference for High Performance Computing, Networking, Storage and Analysis (SC), November, 2020 (Best Paper Award and Best Student Paper Finalist). (Acceptance Rate: TBA)
[ASE'2020] Hongyu Liu*, Ruiqin Tian*, Bin Ren, and Tongping Liu (*equal contribution), Prober: Practically Defending Overflows with Page Protection, The 35th IEEE/ACM International Conference on Automated Software Engineering (ASE), September, 2020. (Acceptance Rate: 93/414 = 22.5%).
[ECCV'2020] Xiaolong Ma*, Wei Niu*, Tianyun Zhang, Sijia Liu, Sheng Lin, Hongjia Li, Xiang Chen, Jian Tang, Kaisheng Ma, Bin Ren, and Yanzhi Wang (*equal contribution), An Image Enhancing Pattern-based Sparsity for Real-Time Inference on Mobile Devices, The 16th European Conference on Computer Vision (ECCV), August, 2020. (Acceptance Rate: TBA)
[GLSVLSI'20] Yifan Gong, Zheng Zhan, Zhengang Li, Wei Niu, Xiaolong Ma, Wenhao Wang, Bin Ren, Caiwen Ding, Xue Lin, Xiaolin Xu, and Yanzhi Wang, A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework, in Proceedings of the 2020 on Great Lakes Symposium on VLSI (Special Session Paper), September. 2020.
[ICML'2020] Yu Chen, Zhenming Liu, Bin Ren, and Xin Jin, On Efficient Constructions of Checkpoints, The 37th International Conference on Machine Learning, July, 2020. (Acceptance Rate: 1,088/4,990 = 21.8%).
[ICS'2020] Ruoming Jin*, Zhen Peng*, Wendell Wu, Feodor Dragan, Gagan Agrawal, and Bin Ren (*equal contribution), Parallelizing Pruned Landmark Labeling: Dealing with Dependencies in Graph Algorithms, The 34th ACM International Conference on Supercomputing, June, 2020. (Acceptance rate: 40/132 = 30%).
[ICS'2020] Tyler Coy, Shuibing He, Bin Ren, and Xuechen Zhang, Compiler Aided Checkpointing using Crash-Consistent Data Structures in NVMM Systems, The 34th ACM International Conference on Supercomputing, June, 2020. (Acceptance rate: 40/132 = 30%).
[DAC'2020] Peiyan Dong, Siyue Wang, Wei Niu, Chengming Zhang, Sheng Lin, Zhengang Li, Yifan Gong, Bin Ren, Xue Lin, and Dingwen Tao, RTMobile: Beyond Real-Time Mobile Acceleration of RNNs for Speech Recognition, The 57th Annual Design Automation Conference, July, 2020. (Acceptance rate: TBA).
[ASPLOS'2020] Wei Niu, Xiaolong Ma, Sheng Lin, Shihao Wang, Xuehai Qian, Xue Lin, Yanzhi Wang, and Bin Ren, PatDNN: Achieving Real-Time DNN Execution on Mobile Devices with Pattern-based Weight Pruning, The 25th International Conference on Architectural Support for Programming Languages and Operating Systems, March, 2020 (Acceptance Rate: 86/476 = 18%).
[CGO'2020] Yu Chen, Ivy B. Peng, Zhen Peng, Xu Liu, and Bin Ren, ATMem: Adaptive Data Placement in Graph Applications on Heterogeneous Memories, The 2020 International Symposium on Code Generation and Optimization, February, 2020 (Acceptance Rate: 26/95 = 27%).
[AAAI'2020] Xiaolong Ma, Fu-Ming Guo, Wei Niu, Xue Lin, Jian Tang, Kaisheng Ma, Bin Ren, and Yanzhi Wang, PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Device, The 34th AAAI Conference on Artificial Intelligence, February, 2020 (Acceptance Rate: 1,591/7,737 = 20.6%).
[TPDS'2020] Soklong Lim, Tyler Coy, Zaixin Lu, Bin Ren, and Xuechen Zhang, NVGRAPH: Enforcing Crash Consistency of Evolving Network Analytics in NVMM Systems, The IEEE Transactions on Parallel and Distributed Systems (TPDS), January, 2020.
[TOPC'2019] Bin Ren, Shruthi Balakrishna, Youngjoon Jo, Sriram Krishnamoorthy, Kunal Agrawal, and Milind Kulkarni, Extracting SIMD Parallelism from Recursive Task-Parallel Programs, The ACM Transaction on Parallel Computing (TOPC), September, 2019.
[SC'2019] Mert Hidayetoglu, Tekin Bicer, Simon Garcia de Gonzalo, Bin Ren, Doga Gursoy, Rajkumar Kettimuthu, Ian T. Foster, and Wen-Mei W. Hwu, MemXCT: Memory-Centric X-Ray CT Reconstruction with Massive Parallelization, The International Conference for High Performance Computing, Networking, Storage, and Analysis, November, 2019 (SC20 Student Cluster Reprocubility Challenge Paper). (Acceptance Rate: 87/344 = 25%)
[PACT'2019] Soklong Lim, Zaixin Lu, Bin Ren, and Xuechen Zhang, Enforcing Crash Consistency of Evolving Network Analytics in Non-Volatile Main Memory Systems, The 28th International Conference on Parallel Architecture and Compilation Techniques, September, 2019. (Acceptance Rate: 26/126 = 21%)
[CLOUD'2019] Jared Polonitza, David Chiu, and Bin Ren, A Transactional Framework for Broadening Access to Geo-Diversification, The 12th IEEE International Conference on Cloud Computing, July, 2019. (Short Paper)
[CGO'2019] Ruiqin Tian*, Junqiao Qiu*, Zhijia Zhao, Xu Liu, and Bin Ren (* co-primary), Transforming Query Sequences for High-Throughput B+ Tree Processing on Many-core Processors, The 2019 International Symposium on Code Generation and Optimization (CGO), February, 2019. (Acceptance Rate: 21/69 = 31%)
[PACT'2018] Zhen Peng, Alexander Powell, Bo Wu, Tekin Bicer, and Bin Ren, GraphPhi: Efficient Parallel Graph Processing on Emerging Throughput-oriented Architectures, The 27th International Conference on Parallel Architectures and Compilation Techniques (PACT), November, 2018. (Acceptance Rate: 36/126 = 29%)
[eScience'2017] Tekin Bicer, Doga Gursoy, Rajkumar Kettimuthu, Ian T. Foster, Bin Ren, Vincent De Andrede, and Francesco De Carlo, Real-Time Data Analysis and Autonomous Steering of Synchrotron Light Source Experiments, The 13th IEEE International Conference on e-Science (eScience), October, 2017.
[PPoPP'2017] Bin Ren, Sriram Krishnamoorthy, Kunal Agrawal, and Milind Kulkarni, Exploiting Vector and Multicore Parallelism for Recursive Data- and Task-Parallel Programs, The 22nd ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), February, 2017. (Acceptance Rate: 29/132 = 22%)
[TACO'2017] Mehmet Can Kurt, Sriram Krishnamoorthy, Gagan Agrawal, and Bin Ren, User-Assisted Store Recycling for Dynamic Task Graph Schedulers, The ACM Transactions on Architecture and Code Optimization (TACO), January, 2017. (Original work, invited to HiPEAC'17)
[PACT'2016] Junqiao Qiu, Zhijia Zhao, and Bin Ren, MicroSpec: Fine-Grained Speculative Parallelization for FSM Computations, The 25th International Conference on Parallel Architecture and Compilation Techniques (PACT), September, 2016. (Acceptance Rate: 31/119 = 26%) [pdf]
[ICPP'2016] Jeff Daily, Ananth Kalyanaraman, Sriram Krishnamoorthy, and Bin Ren, On the Impact of Widening Vector Registers on Sequence Alignment, The 45th annual International Conference on Parallel Processing (ICPP), August, 2016. (Acceptance Rate: 53/251 = 21%)
[PLDI'2015] Bin Ren, Youngjoon Jo, Sriram Krishnamoorthy, Kunal Agrawal, and Milind Kulkarni, Efficient Execution of Recursive Programs on Commodity Vector Hardware, The 36th annual ACM SIGPLAN conference on Programming Language Design and Implementation (PLDI), June, 2015. (Acceptance Rate: 58/303 = 19%) [pdf]
[IPDPS'2015] Linchuan Chen, Xin Huo, Bin Ren, Surabhi Jain, and Gagan Agrawal, Efficient and Simplified Parallel Graph Processing over CPU and MIC, The 29th IEEE International Parallel & Distributed Processing Symposium (IPDPS), May, 2015. (Acceptance Rate: 108/496 = 21%) [pdf]
[ICS'2014] Xin Huo, Bin Ren, and Gagan Agrawal, A Programming System for Xeon Phis with Runtime SIMD Parallelization, The 28th International Conference on Supercomputing (ICS), June, 2014. (Acceptance Rate: 34/162 = 21%) [pdf]
[TACO'2014] Bin Ren, Todd Mytkowicz, and Gagan Agrawal, A Portable Optimization Engine for Accelerating Irregular Data-Traversal Applications on SIMD Architectures, The ACM Transactions on Architecture and Code Optimization (TACO), 2014. [pdf]
[CGO'2013] Bin Ren, Gagan Agrawal, James R. Larus, Todd Mytkowicz, Tomi Poutanen, and Wolfram Schulte, SIMD Parallelization of Applications that Traverse Irregular Data Structures, The 2013 International Symposium on Code Generation and Optimization (CGO), February, 2013 (CACM Research Highlight Nomination, SIGPLAN Research Highlight, Best Paper Award). (Acceptance Rate: 33/117 = 28%) [pdf]
[PACT'2011] Bin Ren, and Gagan Agrawal, Compiling Dynamic Data Structure in Python to Enable the Use of Multi-core and Many-core Libraries, The 20th International Conference on Parallel Architectures and Compilation Techniques (PACT), October, 2011. (Acceptance Rate: 36/221 = 16%)[pdf]
Peer Reviewed Demo Papers
[AAAI'2021 Demo track] Yuxuan Cai, Hongjia Li, Geng Yuan, Wei Niu, Yanyu Li, Xulong Tang, Bin Ren, and Yanzhi Wang, A Compression-Compilation Co-Design Framework Towards Real-Time Object Detection on Mobile Devices, in AAAI (Demonstration Paper), 2021.
[IJCAI'2020 (demo)] Wei Niu*, Pu Zhao*, Zheng Zhan, Xue Lin, Yanzhi Wang, and Bin Ren (*equal contribution), Towards Real-Time DNN Inference on Mobile Platforms with Model Pruning and Compiler Optimization, in Proc. of IJCAI, 2020. (Acceptance Rate: 15.8%). Demo links: Youtube, Bilibili
[ECCV'2020 Demo track] Wei Niu, Mengshu Sun, Zhengang Li, Geng Yuan, Pu Zhao, Xue Lin, Yanzhi Wang, and Bin Ren, Real-time 3D CNN Inference for Action Recognition on Mobile Devices, in European Conference on Computer Vision (ECCV), 2020.
[ECCV'2020 Demo track] Zheng Zhan, Pu Zhao, Geng Yuan, Wei Niu, Bin Ren, Xue Lin, and Yanzhi Wang, Real-time DNN Accelerations on Mobile Devices for Versatile Practical Deep Learning Applications, in European Conference on Computer Vision (ECCV), 2020.
Peer Reviewed Workshops
[IPDPS-Workshop'2023] Daniel T Chen, Ethan H Hansen, Xinpeng Li, Vinooth Kulkarni, Vipin Chaudhary, Bin Ren, Qiang Guan, Sanmukh Kuppannagari, Ji Liu, and Shuai Xu, Efficient quantum circuit cutting by neglecting basis elements, arXiv preprint arXiv:2304.04093, 2023.
[NIPS'2020 Workshop] Yuxuan Cai, Hongjia Li, Geng Yuan, Wei Niu, Yanyu Li, Xulong Tang, Bin Ren, and Yanzhi Wang, YOLObile: Real-Time Object Detection on Mobile Devices via Compression-Compilation Co-Design, in NeurIPS 2020 Workshop on Machine Learning for Autonomous Driving.
[WHPC'2020 Poster] Ruiqin Tian, Jiajia Li, Bin Ren, and Gokcen Kestor, High-Performance Sparse Tensor Algebra Compiler, The 11th International Women in High Performance Computing Workshop (WHPC), in conjunction with ACM/IEEE International Conference for High-Performance Computing, Networking, Storage, and Analysis (SC). 2020.
[LCPC'2020] Erdal Mutlu, Ruiqin Tian, Bin Ren, Sriram Krishnamoorthy, Roberto Gioiosa, Jacques Pienaar, and Gokcen Kestor, COMET: A Domain-Specific Compilation of High-Performance Computational Chemistry, The 33rd Workshop on Languages and Compilers for Parallel Computing (LCPC), October, 2020.
[ICML-Workshop'2019] Wei Niu, Xiaolong Ma, Yanzhi Wang, and Bin Ren, 26ms Inference Time for ResNet-50: Towards Real-Time Execution of all DNNs on Smartphone, The 36th International Conference on Machine Learning (Joint Workshop on On-Device Machine Learning and Compact Deep Neural Network Representations), June, 2019.
[LCPC'2015] Bin Ren, Nishkam Ravi, Yi Yang, Min Feng, Gagan Agrawal, and Srimat Chakradhar, Automatic and Efficient Data Host-Device Communication for Many-Core Coprocessors, The 28th International Workshop on Languages and Compilers for Parallel Computing (LCPC), September, 2015.
[LCPC'2015] Mehmet Can Kurt, Bin Ren, and Gagan Agrawal, Low-Overhead Fault-Tolerance Support using DISC Programming Model, The 28th International Workshop on Languages and Compilers for Parallel Computing (LCPC), September, 2015.
[HIPS'2011] Bin Ren, Gagan Agrawal, Brad Chamberlain, and Steve Deitz, Translating Chapel to Use FREERIDE: A Case Study in Using an HPC language for Data-intensive Computing, The 16th International Workshop on High-Level Parallel Programming Models and Supportive Environments (HIPS) held in conjunction with IPDPS, May, 2011, (LCPC2010 Poster).[pdf]
Thesis and Others
[Thesis'2014] Bin Ren, Supporting Applications Involving Dynamic Data Structures and Irregular Memory Access on Emerging Parallel Platforms, Phd Dissertation Thesis, The Ohio State University, 2014 [pdf]
[PPoPP'2016] Mehmet Can Kurt, Bin Ren, Sriram Krishnamoorthy, and Gagan Agrawal, User-assisted Storage Reuse Determination for Dynamic Task Graphs, The 21st ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP), March, 2016. (Poster Paper). [pdf]
[ICS'2014] Bin Ren, Nishkam Ravi, Yi Yang, Min Feng, Gagan Agrawal, and Srimat Chakradhar, Automating and Optimizing Data Transfers for Many-core Coprocessors, The 28th International Conference on Supercomputing (ICS), June, 2014. (Poster Paper). [pdf]
[PACT'2012] Bin Ren, Gagan Agrawal, James R. Larus, Todd Mytkowicz, Tomi Poutanen, and Wolfram Schulte, Fine-Grained Parallel Traversals of Irregular Data Structures, The 21th International Conference on Parallel Architectures and Compilation Techniques (PACT), October, 2012. (Poster Paper). [pdf]