Yida Wang - RankMe

62 papers A* 7A 5B 3C 1Misc 1Journal 29Unranked 15

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	SAS: Sparse Attention Synthesizer for Efficient Language Model Inference. EuroSys Yuan Zhou, Shaojie Xiang, Lingfan Yu, Zhenyu Song, Charith Mendis, Yida Wang
2026	J	`jnl`	StreamFusion: Scalable Sequence Parallelism for Distributed Inference of Diffusion Transformers on GPUs. CoRR Jiacheng Yang, Jun Wu, Yaoyao Ding, Zhiying Xu, Yida Wang, Gennady Pekhimenko
2026	—	`conf`	Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation. ASPLOS (1) Yaoyao Ding, Bohan Hou, Xiao Zhang, Allan Lin, Tianqi Chen, Cody Hao Yu, Yida Wang, Gennady Pekhimenko
2025	J	`jnl`	Block-Diagonal LoRA for Eliminating Communication Overhead in Tensor Parallel LoRA Serving. CoRR Xinyu Wang, Jonas M. Kübler, Kailash Budhathoki, Yida Wang, Matthäus Kleindessner
2025	A*	`conf`	DCP: Addressing Input Dynamism In Long-Context Training via Dynamic Context Parallelism. SOSP Chenyu Jiang, Zhenkun Cai, Ye Tian, Zhen Jia, Yida Wang, Chuan Wu
2025	J	`jnl`	DCP: Addressing Input Dynamism In Long-Context Training via Dynamic Context Parallelism. CoRR Chenyu Jiang, Zhenkun Cai, Ye Tian, Zhen Jia, Yida Wang, Chuan Wu
2025	—	`conf`	KDD 2025 Workshop on Inference Optimization for Generative AI. KDD (2) Panpan Xu, Youngsuk Park, Lin Lee Cheong, Yida Wang, Yiying Zhang, George Karypis, Sherry Marcus
2025	—	`conf`	ScaleFusion: Scalable Inference of Spatial-Temporal Diffusion Transformers for High-Resolution Long Video Generation. MLSys Jiacheng Yang, Jun Wu, Zhen Zhang, Xinwei Fu, Zhiying Xu, Zhen Jia, Yida Wang, Gennady Pekhimenko
2025	J	`jnl`	Tilus: A Virtual Machine for Arbitrary Low-Precision GPGPU Computation in LLM Serving. CoRR Yaoyao Ding, Bohan Hou, Xiao Zhang, Allan Lin, Tianqi Chen, Cody Yu Hao, Yida Wang, Gennady Pekhimenko
2024	Misc	`conf`	DISTMM: Accelerating Distributed Multimodal Model Training. NSDI Jun Huang, Zhen Zhang, Shuai Zheng, Feng Qin, Yida Wang
2024	—	`conf`	DiffusionPipe: Training Large Diffusion Models with Efficient Pipelines. MLSys Ye Tian, Zhen Jia, Ziyue Luo, Yida Wang, Chuan Wu
2024	J	`jnl`	DiffusionPipe: Training Large Diffusion Models with Efficient Pipelines. CoRR Ye Tian, Zhen Jia, Ziyue Luo, Yida Wang, Chuan Wu
2024	—	`conf`	Distributed Training of Large Language Models on AWS Trainium. SoCC Xinwei Fu, Zhen Zhang, Haozheng Fan, Guangtai Huang, Mohammad El-Shabani, Randy Huang, Rahul Solanki, Fei Wu, Ron Diamant, Yida Wang
2024	A	`conf`	DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines. EuroSys Chenyu Jiang, Zhen Jia, Shuai Zheng, Yida Wang, Chuan Wu
2024	J	`jnl`	Fast Convolution Meets Low Precision: Exploring Efficient Quantized Winograd Convolution on Modern CPUs. ACM Trans. Archit. Code Optim. Xueying Wang, Guangli Li, Zhen Jia, Xiaobing Feng, Yida Wang
2024	B	`conf`	HLAT: High-quality Large Language Model Pre-trained on AWS Trainium. IEEE Big Data Haozheng Fan, Hao Zhou, Guangtai Huang, Parameswaran Raman, Xinwei Fu, Gaurav Gupta, Dhananjay Ram, Yida Wang, Jun Huan
2024	J	`jnl`	HLAT: High-quality Large Language Model Pre-trained on AWS Trainium. CoRR Haozheng Fan, Hao Zhou, Guangtai Huang, Parameswaran Raman, Xinwei Fu, Gaurav Gupta, Dhananjay Ram, Yida Wang, Jun Huan
2024	A*	`conf`	Inference Optimization of Foundation Models on AI Accelerators. KDD Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis
2024	J	`jnl`	Inference Optimization of Foundation Models on AI Accelerators. CoRR Youngsuk Park, Kailash Budhathoki, Liangfu Chen, Jonas M. Kübler, Jiaji Huang, Matthäus Kleindessner, Jun Huan, Volkan Cevher, Yida Wang, George Karypis
2024	—	`conf`	Lancet: Accelerating Mixture-of-Experts Training via Whole Graph Computation-Communication Overlapping. MLSys Chenyu Jiang, Ye Tian, Zhen Jia, Shuai Zheng, Chuan Wu, Yida Wang
2024	J	`jnl`	Lancet: Accelerating Mixture-of-Experts Training via Whole Graph Computation-Communication Overlapping. CoRR Chenyu Jiang, Ye Tian, Zhen Jia, Shuai Zheng, Chuan Wu, Yida Wang
2024	—	`conf`	Slapo: A Schedule Language for Progressive Optimization of Large Deep Learning Model Training. ASPLOS (2) Hongzheng Chen, Cody Hao Yu, Shuai Zheng, Zhen Zhang, Zhiru Zhang, Yida Wang
2023	J	`jnl`	Decoupled Model Schedule for Deep Learning Training. CoRR Hongzheng Chen, Cody Hao Yu, Shuai Zheng, Zhen Zhang, Zhiru Zhang, Yida Wang
2023	J	`jnl`	DynaPipe: Optimizing Multi-task Training through Dynamic Pipelines. CoRR Chenyu Jiang, Zhen Jia, Shuai Zheng, Yida Wang, Chuan Wu
2023	A*	`conf`	GEMINI: Fast Failure Recovery in Distributed Training with In-Memory Checkpoints. SOSP Zhuang Wang, Zhen Jia, Shuai Zheng, Zhen Zhang, Xinwei Fu, T. S. Eugene Ng, Yida Wang
2023	A*	`conf`	Grape: Practical and Efficient Graphed Execution for Dynamic Deep Neural Networks on GPUs. MICRO Bojian Zheng, Cody Hao Yu, Jie Wang, Yaoyao Ding, Yizhi Liu, Yida Wang, Gennady Pekhimenko
2023	—	`conf`	Hidet: Task-Mapping Programming Paradigm for Deep Learning Tensor Programs. ASPLOS (2) Yaoyao Ding, Cody Hao Yu, Bojian Zheng, Yizhi Liu, Yida Wang, Gennady Pekhimenko
2023	J	`jnl`	Perception and memory retrieval states are reflected in distributed patterns of background functional connectivity. NeuroImage Y. Peeta Li, Yida Wang, Nicholas B. Turk-Browne, Brice A. Kuhl, J. Benjamin Hutchinson
2023	J	`jnl`	RAF: Holistic Compilation for Deep Learning Model Training. CoRR Cody Hao Yu, Haozheng Fan, Guangtai Huang, Zhen Jia, Yizhi Liu, Jie Wang, Zach Zheng, Yuan Zhou, Haichen Shen, Junru Shao, Mu Li, Yida Wang
2023	A*	`conf`	Training Large-scale Foundation Models on Emerging AI Chips. KDD Aashiq Muhamed, Christian Bock, Rahul Solanki, Youngsuk Park, Yida Wang, Jun Huan
2022	A*	`conf`	Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. OSDI Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Eric P. Xing, Joseph E. Gonzalez, Ion Stoica
2022	J	`jnl`	Alpa: Automating Inter- and Intra-Operator Parallelism for Distributed Deep Learning. CoRR Lianmin Zheng, Zhuohan Li, Hao Zhang, Yonghao Zhuang, Zhifeng Chen, Yanping Huang, Yida Wang, Yuanzhong Xu, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica
2022	—	`conf`	DietCode: Automatic Optimization for Dynamic Tensor Programs. MLSys Bojian Zheng, Ziheng Jiang, Cody Hao Yu, Haichen Shen, Joshua Fromm, Yizhi Liu, Yida Wang, Luis Ceze, Tianqi Chen, Gennady Pekhimenko
2022	J	`jnl`	Hidet: Task Mapping Programming Paradigm for Deep Learning Tensor Programs. CoRR Yaoyao Ding, Cody Hao Yu, Bojian Zheng, Yizhi Liu, Yida Wang, Gennady Pekhimenko
2022	J	`jnl`	MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud. CoRR Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin
2022	J	`jnl`	MiCS: Near-linear Scaling for Training Gigantic Model on Public Cloud. Proc. VLDB Endow. Zhen Zhang, Shuai Zheng, Yida Wang, Justin Chiu, George Karypis, Trishul Chilimbi, Mu Li, Xin Jin
2021	J	`jnl`	Bring Your Own Codegen to Deep Learning Compiler. CoRR Zhi Chen, Cody Hao Yu, Trevor Morris, Jorn Tuyls, Yi-Hsiang Lai, Jared Roesch, Elliott Delaye, Vin Sharma, Yida Wang
2021	B	`conf`	LoWino: Towards Efficient Low-Precision Winograd Convolutions on Modern CPUs. ICPP Guangli Li, Zhen Jia, Xiaobing Feng, Yida Wang
2021	—	`conf`	Lorien: Efficient Deep Learning Workloads Delivery. SoCC Cody Hao Yu, Xingjian Shi, Haichen Shen, Zhi Chen, Mu Li, Yida Wang
2021	—	`conf`	Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference. MLSys Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang
2021	A	`conf`	UNIT: Unifying Tensorized Instruction Compilation. CGO Jian Weng, Animesh Jain, Jie Wang, Leyuan Wang, Yida Wang, Tony Nowatzki
2021	J	`jnl`	UNIT: Unifying Tensorized Instruction Compilation. CoRR Jian Weng, Animesh Jain, Jie Wang, Leyuan Wang, Yida Wang, Tony Nowatzki
2020	J	`jnl`	Ansor : Generating High-Performance Tensor Programs for Deep Learning. CoRR Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica
2020	A*	`conf`	Ansor: Generating High-Performance Tensor Programs for Deep Learning. OSDI Lianmin Zheng, Chengfan Jia, Minmin Sun, Zhao Wu, Cody Hao Yu, Ameer Haj-Ali, Yida Wang, Jun Yang, Danyang Zhuo, Koushik Sen, Joseph E. Gonzalez, Ion Stoica
2020	J	`jnl`	Efficient Execution of Quantized Deep Learning Models: A Compiler Approach. CoRR Animesh Jain, Shoubhik Bhattacharya, Masahiro Masuda, Vin Sharma, Yida Wang
2020	J	`jnl`	FeatGraph: A Flexible and Efficient Backend for Graph Neural Network Systems. CoRR Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang
2020	A	`conf`	FeatGraph: a flexible and efficient backend for graph neural network systems. SC Yuwei Hu, Zihao Ye, Minjie Wang, Jiali Yu, Da Zheng, Mu Li, Zheng Zhang, Zhiru Zhang, Yida Wang
2020	—	`conf`	Is Network the Bottleneck of Distributed Training? NetAI@SIGCOMM Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, Raman Arora, Xin Jin
2020	J	`jnl`	Is Network the Bottleneck of Distributed Training? CoRR Zhen Zhang, Chaokun Chang, Haibin Lin, Yida Wang, Raman Arora, Xin Jin
2020	J	`jnl`	Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference. CoRR Haichen Shen, Jared Roesch, Zhi Chen, Wei Chen, Yong Wu, Mu Li, Vin Sharma, Zachary Tatlock, Yida Wang
2019	B	`conf`	A Unified Optimization Approach for CNN Model Inference on Integrated GPUs. ICPP Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang
2019	J	`jnl`	A Unified Optimization Approach for CNN Model Inference on Integrated GPUs. CoRR Leyuan Wang, Zhi Chen, Yizhi Liu, Yao Wang, Lianmin Zheng, Mu Li, Yida Wang
2019	—	`conf`	Optimizing CNN Model Inference on CPUs. USENIX ATC Yizhi Liu, Yao Wang, Ruofei Yu, Mu Li, Vin Sharma, Yida Wang
2018	J	`jnl`	Optimizing CNN Model Inference on CPUs. CoRR Yizhi Liu, Yao Wang, Ruofei Yu, Mu Li, Vin Sharma, Yida Wang
2018	J	`jnl`	Scheduling Computation Graphs of Deep Learning Models on Manycore CPUs. CoRR Linpeng Tang, Yida Wang, Theodore L. Willke, Kai Li
2017	J	`jnl`	BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods. PLoS Comput. Biol. Krzysztof J. Gorgolewski, Fidel Alfaro-Almagro, Tibor Auer, Pierre Bellec, Mihai Capota, M. Mallar Chakravarty, Nathan William Churchill, Alexander Li Cohen, R. Cameron Craddock, Gabriel A. Devenyi, Anders Eklund, Oscar Esteban, Guillaume Flandin, Satrajit S. Ghosh, J. Swaroop Guntupalli, Mark Jenkinson, Anisha Keshavan, Gregory Kiar, Franziskus Liem, Pradeep Reddy Raamana, David Raffelt, Christopher John Steele, Pierre-Olivier Quirion, Robert E. Smith, Stephen C. Strother, Gaël Varoquaux, Yida Wang, Tal Yarkoni, Russell A. Poldrack
2017	C	`conf`	High-Performance Incremental SVM Learning on Intel ISC Dipanjan Sengupta, Yida Wang, Narayanan Sundaram, Theodore L. Willke
2016	J	`jnl`	Enabling Factor Analysis on Thousand-Subject Neuroimaging Datasets. CoRR Michael J. Anderson, Mihai Capota, Javier S. Turek, Xia Zhu, Theodore L. Willke, Yida Wang, Po-Hsuan Chen, Jeremy R. Manning, Peter J. Ramadge, Kenneth A. Norman
2016	—	`conf`	Enabling factor analysis on thousand-subject neuroimaging datasets. IEEE BigData Michael J. Anderson, Mihai Capota, Javier S. Turek, Xia Zhu, Theodore L. Willke, Yida Wang, Po-Hsuan Chen, Jeremy R. Manning, Peter J. Ramadge, Kenneth A. Norman
2016	—	`—`	Large-scale analyses of functional interactions in the human brain Yida Wang
2016	—	`conf`	Real-time full correlation matrix analysis of fMRI data. IEEE BigData Yida Wang, Bryn Keller, Mihai Capota, Michael J. Anderson, Narayanan Sundaram, Jonathan D. Cohen, Kai Li, Nicholas B. Turk-Browne, Theodore L. Willke
2015	A	`conf`	Full correlation matrix analysis of fMRI data on Intel® Xeon Phi™ coprocessors. SC Yida Wang, Michael J. Anderson, Jonathan D. Cohen, Alexander Heinecke, Kai Li, Nadathur Satish, Narayanan Sundaram, Nicholas B. Turk-Browne, Theodore L. Willke