Yuxiong He

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 107

Top Venues

CoRR

NeurIPS

ICLR

Publications

Guanhua Wang, Olatunji Ruwase, Bing Xie, Yuxiong He
FastPersist: Accelerating Model Checkpointing in Deep Learning. CoRR (2024)
Haojun Xia, Zhen Zheng, Xiaoxia Wu, Shiyang Chen, Zhewei Yao, Stephen Youn, Arash Bakhtiari, Michael Wyatt, Donglin Zhuang, Zhongzhu Zhou, Olatunji Ruwase, Yuxiong He, Shuaiwen Leon Song
Quant-LLM: Accelerating the Serving of Large Language Models via FP6-Centric Algorithm-System Co-Design on Modern GPUs. USENIX ATC (2024)
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Xiaoxia Wu, Connor Holmes, Zhewei Yao, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
ZeRO++: Extremely Efficient Collective Communication for Large Model Training. ICLR (2024)
Zhewei Yao, Xiaoxia Wu, Cheng Li, Stephen Youn, Yuxiong He
Exploring Post-training Quantization in LLMs from Comprehensive Study to Low Rank Compensation. AAAI (2024)
Connor Holmes, Masahiro Tanaka, Michael Wyatt, Ammar Ahmad Awan, Jeff Rasley, Samyam Rajbhandari, Reza Yazdani Aminabadi, Heyang Qin, Arash Bakhtiari, Lev Kurilenko, Yuxiong He
DeepSpeed-FastGen: High-throughput Text Generation for LLMs via MII and DeepSpeed-Inference. CoRR (2024)
Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminabadi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. IPDPS (Workshops) (2024)
Haojun Xia, Zhen Zheng, Xiaoxia Wu, Shiyang Chen, Zhewei Yao, Stephen Youn, Arash Bakhtiari, Michael Wyatt, Donglin Zhuang, Zhongzhu Zhou, Olatunji Ruwase, Yuxiong He, Shuaiwen Leon Song
FP6-LLM: Efficiently Serving Large Language Models Through FP6-Centric Algorithm-System Co-Design. CoRR (2024)
Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Reza Yazdani Aminadabi, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. PODC (2024)
Conglong Li, Zhewei Yao, Xiaoxia Wu, Minjia Zhang, Connor Holmes, Cheng Li, Yuxiong He
DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing. AAAI (2024)
Quentin Anthony, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He, Aamir Shafi, Mustafa Abduljabbar, Hari Subramoni, Dhabaleswar K. Panda
MCR-DL: Mix-and-Match Communication Runtime for Deep Learning. CoRR (2023)
Siddharth Singh, Olatunji Ruwase, Ammar Ahmad Awan, Samyam Rajbhandari, Yuxiong He, Abhinav Bhatele
A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize Mixture-of-Experts Training. ICS (2023)
Syed Zawad, Cheng Li, Zhewei Yao, Elton Zheng, Yuxiong He, Feng Yan
DySR: Adaptive Super-Resolution via Algorithm and System Co-design. ICLR (2023)
Chengming Zhang, Shaden Smith, Baixi Sun, Jiannan Tian, Jonathan Soifer, Xiaodong Yu, Shuaiwen Leon Song, Yuxiong He, Dingwen Tao
HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs. ICS (2023)
Guanhua Wang, Heyang Qin, Sam Ade Jacobs, Connor Holmes, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
ZeRO++: Extremely Efficient Collective Communication for Giant Model Training. CoRR (2023)
Sheng Shen, Zhewei Yao, Chunyuan Li, Trevor Darrell, Kurt Keutzer, Yuxiong He
Scaling Vision-Language Models with Sparse Mixture of Experts. EMNLP (Findings) (2023)
Chengming Zhang, Shaden Smith, Baixi Sun, Jiannan Tian, Jonathan Soifer, Xiaodong Yu, Shuaiwen Leon Song, Yuxiong He, Dingwen Tao
HEAT: A Highly Efficient and Affordable Training System for Collaborative Filtering Based Recommendation on CPUs. CoRR (2023)
Fengxiang Bie, Yibo Yang, Zhongzhu Zhou, Adam Ghanem, Minjia Zhang, Zhewei Yao, Xiaoxia Wu, Connor Holmes, Pareesa Ameneh Golnari, David A. Clifton, Yuxiong He, Dacheng Tao, Shuaiwen Leon Song
RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Model. CoRR (2023)
Quentin Anthony, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He, Aamir Shafi, Mustafa Abduljabbar, Hari Subramoni, Dhabaleswar K. Panda
MCR-DL: Mix-and-Match Communication Runtime for Deep Learning. IPDPS (2023)
Zhewei Yao, Xiaoxia Wu, Conglong Li, Minjia Zhang, Heyang Qin, Olatunji Ruwase, Ammar Ahmad Awan, Samyam Rajbhandari, Yuxiong He
DeepSpeed-VisualChat: Multi-Round Multi-Image Interleave Chat via Multi-Modal Causal Attention. CoRR (2023)
Zhewei Yao, Reza Yazdani Aminabadi, Stephen Youn, Xiaoxia Wu, Elton Zheng, Yuxiong He
ZeroQuant-HERO: Hardware-Enhanced Robust Optimized Post-Training Quantization Framework for W8A8 Transformers. CoRR (2023)
Zhewei Yao, Reza Yazdani Aminabadi, Olatunji Ruwase, Samyam Rajbhandari, Xiaoxia Wu, Ammar Ahmad Awan, Jeff Rasley, Minjia Zhang, Conglong Li, Connor Holmes, Zhongzhu Zhou, Michael Wyatt, Molly Smith, Lev Kurilenko, Heyang Qin, Masahiro Tanaka, Shuai Che, Shuaiwen Leon Song, Yuxiong He
DeepSpeed-Chat: Easy, Fast and Affordable RLHF Training of ChatGPT-like Models at All Scales. CoRR (2023)
Siddharth Singh, Olatunji Ruwase, Ammar Ahmad Awan, Samyam Rajbhandari, Yuxiong He, Abhinav Bhatele
A Novel Tensor-Expert Hybrid Parallelism Approach to Scale Mixture-of-Experts Training. CoRR (2023)
Sam Ade Jacobs, Masahiro Tanaka, Chengming Zhang, Minjia Zhang, Shuaiwen Leon Song, Samyam Rajbhandari, Yuxiong He
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models. CoRR (2023)
Yucheng Lu, Conglong Li, Minjia Zhang, Christopher De Sa, Yuxiong He
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam. ICLR (2023)
Xiaoxia Wu, Zhewei Yao, Yuxiong He
ZeroQuant-FP: A Leap Forward in LLMs Post-Training W4A8 Quantization Using Floating-Point Formats. CoRR (2023)
Minjia Zhang, Uma-Naresh Niranjan, Yuxiong He
Revisiting the Efficiency-Accuracy Tradeoff in Adapting Transformer Models via Adversarial Fine-Tuning. ECAI (2023)
Xiaoxia Wu, Cheng Li, Reza Yazdani Aminabadi, Zhewei Yao, Yuxiong He
Understanding Int4 Quantization for Language Models: Latency Speedup, Composability, and Failure Cases. ICML (2023)
Reza Yazdani Aminabadi, Olatunji Ruwase, Minjia Zhang, Yuxiong He, José-María Arnau, Antonio Gonazalez
SHARP: An Adaptable, Energy-Efficient Accelerator for Recurrent Neural Networks. ACM Trans. Embed. Comput. Syst. 22 (2) (2023)
Sheng Shen, Zhewei Yao, Chunyuan Li, Trevor Darrell, Kurt Keutzer, Yuxiong He
Scaling Vision-Language Models with Sparse Mixture of Experts. CoRR (2023)
Zhewei Yao, Cheng Li, Xiaoxia Wu, Stephen Youn, Yuxiong He
A Comprehensive Study on Post-Training Quantization for Large Language Models. CoRR (2023)
Pareesa Ameneh Golnari, Zhewei Yao, Yuxiong He
Selective Guidance: Are All the Denoising Steps of Guided Diffusion Important? CoRR (2023)
Xiaoxia Wu, Cheng Li, Reza Yazdani Aminabadi, Zhewei Yao, Yuxiong He
Understanding INT4 Quantization for Transformer Models: Latency Speedup, Composability, and Failure Cases. CoRR (2023)
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR (2023)
Xiaoxia Wu, Haojun Xia, Stephen Youn, Zhen Zheng, Shiyang Chen, Arash Bakhtiari, Michael Wyatt, Reza Yazdani Aminabadi, Yuxiong He, Olatunji Ruwase, Leon Song, Zhewei Yao
ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks. CoRR (2023)
Shaden Smith, Mostofa Patwary, Brandon Norick, Patrick LeGresley, Samyam Rajbhandari, Jared Casper, Zhun Liu, Shrimai Prabhumoye, George Zerveas, Vijay Korthikanti, Elton Zheng, Rewon Child, Reza Yazdani Aminabadi, Julie Bernauer, Xia Song, Mohammad Shoeybi, Yuxiong He, Michael Houston, Saurabh Tiwary, Bryan Catanzaro
Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model. CoRR (2022)
Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He
Extreme Compression for Pre-trained Transformers Made Simple and Efficient. CoRR (2022)
Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang, Reza Yazdani Aminabadi, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He
DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale. ICML (2022)
Yuxin Ma, Ping Gong, Jun Yi, Zhewei Yao, Minjie Wang, Cheng Li, Yuxiong He, Feng Yan
BiFeat: Supercharge GNN Training via Graph Feature Quantization. CoRR (2022)
Yucheng Lu, Conglong Li, Minjia Zhang, Christopher De Sa, Yuxiong He
Maximizing Communication Efficiency for Large-scale Training via 0/1 Adam. CoRR (2022)
Zhewei Yao, Xiaoxia Wu, Conglong Li, Connor Holmes, Minjia Zhang, Cheng Li, Yuxiong He
Random-LTD: Random and Layerwise Token Dropping Brings Efficient Training for Large-scale Transformers. CoRR (2022)
Minjia Zhang, Wenhan Wang, Yuxiong He
GraSP: Optimizing Graph-based Nearest Neighbor Search with Subgraph Sampling and Pruning. WSDM (2022)
Xiao Zhang, Yuxiong He, Youhuai Wang, Xiaoming Chen, Shi Jin, Ye Liang
Task Offloading Based on GRU Model in IoT. EITCE (2022)
Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He
ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers. CoRR (2022)
Conglong Li, Zhewei Yao, Xiaoxia Wu, Minjia Zhang, Yuxiong He
DeepSpeed Data Efficiency: Improving Deep Learning Model Quality and Training Efficiency via Efficient Data Sampling and Routing. CoRR (2022)
Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu
Compressing Pre-trained Transformers via Low-Bit NxM Sparsity for Natural Language Understanding. CoRR (2022)
Xiaoxia Wu, Zhewei Yao, Minjia Zhang, Conglong Li, Yuxiong He
XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient. NeurIPS (2022)
Conglong Li, Minjia Zhang, Yuxiong He
The Stability-Efficiency Dilemma: Investigating Sequence Length Warmup for Training GPT Models. NeurIPS (2022)
Conglong Li, Ammar Ahmad Awan, Hanlin Tang, Samyam Rajbhandari, Yuxiong He
1-bit LAMB: Communication Efficient Large-Scale Large-Batch Training with LAMB's Convergence Speed. HIPC (2022)
Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang, Reza Yazdani Aminabadi, Ammar Ahmad Awan, Jeff Rasley, Yuxiong He
DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale. CoRR (2022)
Minjia Zhang, Uma-Naresh Niranjan, Yuxiong He
Adversarial Data Augmentation for Task-Specific Knowledge Distillation of Pre-trained Transformers. AAAI (2022)
Minjia Zhang, Uma-Naresh Niranjan, Yuxiong He
ScaLA: Accelerating Adaptation of Pre-Trained Transformer-Based Language Models via Efficient Large-Batch Adversarial Noise. CoRR (2022)
Reza Yazdani Aminabadi, Samyam Rajbhandari, Ammar Ahmad Awan, Cheng Li, Du Li, Elton Zheng, Olatunji Ruwase, Shaden Smith, Minjia Zhang, Jeff Rasley, Yuxiong He
DeepSpeed- Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale. SC (2022)
Reza Yazdani Aminabadi, Samyam Rajbhandari, Minjia Zhang, Ammar Ahmad Awan, Cheng Li, Du Li, Elton Zheng, Jeff Rasley, Shaden Smith, Olatunji Ruwase, Yuxiong He
DeepSpeed Inference: Enabling Efficient Inference of Transformer Models at Unprecedented Scale. CoRR (2022)
Zhewei Yao, Reza Yazdani Aminabadi, Minjia Zhang, Xiaoxia Wu, Conglong Li, Yuxiong He
ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers. NeurIPS (2022)
Conglong Li, Minjia Zhang, Yuxiong He
Curriculum Learning: A Regularization Method for Efficient and Stable Billion-Scale GPT Model Pre-Training. CoRR (2021)
Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, Shaden Smith, Yuxiong He
ZeRO-Infinity: Breaking the GPU Memory Wall for Extreme Scale Deep Learning. CoRR (2021)
Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, Olatunji Ruwase, Shuangyan Yang, Minjia Zhang, Dong Li, Yuxiong He
ZeRO-Offload: Democratizing Billion-Scale Model Training. USENIX Annual Technical Conference (2021)
Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, Olatunji Ruwase, Shuangyan Yang, Minjia Zhang, Dong Li, Yuxiong He
ZeRO-Offload: Democratizing Billion-Scale Model Training. CoRR (2021)
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed. ICML (2021)
Young Jin Kim, Ammar Ahmad Awan, Alexandre Muzio, Andrés Felipe Cruz-Salinas, Liyang Lu, Amr Hendy, Samyam Rajbhandari, Yuxiong He, Hany Hassan Awadalla
Scalable and Efficient MoE Training for Multitask Multilingual Models. CoRR (2021)
Hanlin Tang, Shaoduo Gan, Ammar Ahmad Awan, Samyam Rajbhandari, Conglong Li, Xiangru Lian, Ji Liu, Ce Zhang, Yuxiong He
1-bit Adam: Communication Efficient Large-Scale Training with Adam's Convergence Speed. CoRR (2021)
Samyam Rajbhandari, Olatunji Ruwase, Jeff Rasley, Shaden Smith, Yuxiong He
ZeRO-infinity: breaking the GPU memory wall for extreme scale deep learning. SC (2021)
Conglong Li, Ammar Ahmad Awan, Hanlin Tang, Samyam Rajbhandari, Yuxiong He
1-bit LAMB: Communication Efficient Large-Scale Large-Batch Training with LAMB's Convergence Speed. CoRR (2021)
Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM. CoRR (2021)
Heyang Qin, Samyam Rajbhandari, Olatunji Ruwase, Feng Yan, Lei Yang, Yuxiong He
SimiGrad: Fine-Grained Adaptive Batching for Large Scale Training using Gradient Similarity Measurement. NeurIPS (2021)
Connor Holmes, Minjia Zhang, Yuxiong He, Bo Wu
NxMTransformer: Semi-Structured Sparsification for Natural Language Understanding via ADMM. NeurIPS (2021)
Conglong Li, Minjia Zhang, David G. Andersen, Yuxiong He
Improving Approximate Nearest Neighbor Search through Learned Adaptive Early Termination. SIGMOD Conference (2020)
Yang You, Yuxiong He, Samyam Rajbhandari, Wenhan Wang, Cho-Jui Hsieh, Kurt Keutzer, James Demmel
Fast LSTM by dynamic decomposition on cloud and distributed systems. Knowl. Inf. Syst. 62 (11) (2020)
Samyam Rajbhandari, Jeff Rasley, Olatunji Ruwase, Yuxiong He
ZeRO: memory optimizations toward training trillion parameter models. SC (2020)
Minjia Zhang, Yuxiong He
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping. CoRR (2020)
Abdulaziz Almaslukh, Amr Magdy, Ahmed M. Aly, Mohamed F. Mokbel, Sameh Elnikety, Yuxiong He, Suman Nath, Walid G. Aref
Local trend discovery on real-time microblogs with uncertain locations in tight memory environments. GeoInformatica 24 (2) (2020)
Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase, Yuxiong He
DeepSpeed: System Optimizations Enable Training Deep Learning Models with Over 100 Billion Parameters. KDD (2020)
Minjia Zhang, Yuxiong He
Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping. NeurIPS (2020)
Hanlin Tang, Shaoduo Gan, Samyam Rajbhandari, Xiangru Lian, Ji Liu, Yuxiong He, Ce Zhang
APMSqueeze: A Communication Efficient Adam-Preconditioned Momentum SGD Algorithm. CoRR (2020)
Yu Su, Xiaoqi Ren, Shai Vardi, Adam Wierman, Yuxiong He
Communication-Aware Scheduling of Precedence-Constrained Tasks. SIGMETRICS Perform. Evaluation Rev. 47 (2) (2019)
Yang You, Yuxiong He, Samyam Rajbhandari, Wenhan Wang, Cho-Jui Hsieh, Kurt Keutzer, James Demmel
Fast LSTM Inference by Dynamic Decomposition on Cloud Systems. ICDM (2019)
Samyam Rajbhandari, Jeff Rasley, Olatunji Ruwase, Yuxiong He
ZeRO: Memory Optimization Towards Training A Trillion Parameter Models. CoRR (2019)
Connor Holmes, Daniel Mawhirter, Yuxiong He, Feng Yan, Bo Wu
GRNN: Low-Latency and Scalable RNN Inference on GPUs. EuroSys (2019)
Minjia Zhang, Samyam Rajbhandari, Wenhan Wang, Elton Zheng, Olatunji Ruwase, Jeff Rasley, Jason Li, Junhua Wang, Yuxiong He
Accelerating Large Scale Deep Learning Inference through DeepCPU at Microsoft. OpML (2019)
Samyam Rajbhandari, Harsh Shrivastava, Yuxiong He
AntMan: Sparse Low-Rank Compression to Accelerate RNN inference. CoRR (2019)
Jonathan Soifer, Jason Li, Mingqin Li, Jeffrey Zhu, Yingnan Li, Yuxiong He, Elton Zheng, Adi Oltean, Maya Mosyak, Chris Barnes, Thomas Liu, Junhua Wang
Deep Learning Inference Service at Microsoft. OpML (2019)
Minjia Zhang, Yuxiong He
GRIP: Multi-Store Capacity-Optimized High-Performance Nearest Neighbor Search for Vector Search Engine. CIKM (2019)
Reza Yazdani, Olatunji Ruwase, Minjia Zhang, Yuxiong He, José-María Arnau, Antonio González
LSTM-Sharp: An Adaptable, Energy-Efficient Hardware Accelerator for Long Short-Term Memory. CoRR (2019)
Feng Yan, Yuxiong He, Olatunji Ruwase, Evgenia Smirni
Efficient Deep Neural Network Serving: Fast and Furious. IEEE Trans. Netw. Serv. Manag. 15 (1) (2018)
Wei Wen, Yuxiong He, Samyam Rajbhandari, Minjia Zhang, Wenhan Wang, Fang Liu, Bin Hu, Yiran Chen, Hai Li
Learning Intrinsic Sparse Structures within Long Short-Term Memory. ICLR (Poster) (2018)
Minjia Zhang, Samyam Rajbhandari, Wenhan Wang, Yuxiong He
DeepCPU: Serving RNN-based Deep Learning Models 10x Faster. USENIX Annual Technical Conference (2018)
Minjia Zhang, Yuxiong He
Zoom: SSD-based Vector Search for Optimizing Accuracy, Latency and Memory. CoRR (2018)
Conglong Li, David G. Andersen, Qiang Fu, Sameh Elnikety, Yuxiong He
Better Caching in Search Advertising Systems with Rapid Refresh Predictions. WWW (2018)
Minjia Zhang, Xiaodong Liu, Wenhan Wang, Jianfeng Gao, Yuxiong He
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models. CoRR (2018)
Farshid Farhat, Diman Zad Tootaghaj, Yuxiong He, Anand Sivasubramaniam, Mahmut T. Kandemir, Chita R. Das
Stochastic Modeling and Optimization of Stragglers. IEEE Trans. Cloud Comput. 6 (4) (2018)
Minjia Zhang, Wenhan Wang, Xiaodong Liu, Jianfeng Gao, Yuxiong He
Navigating with Graph Representations for Fast and Scalable Decoding of Neural Language Models. NeurIPS (2018)
Bob Goodwin, Michael Hopcroft, Dan Luu, Alex Clemmer, Mihaela Curmei, Sameh Elnikety, Yuxiong He
BitFunnel: Revisiting Signatures for Search. SIGIR (2017)
Tim Kaler, Yuxiong He, Sameh Elnikety
Optimal Reissue Policies for Reducing Tail Latency. SPAA (2017)
Md. Enamul Haque, Yuxiong He, Sameh Elnikety, Thu D. Nguyen, Ricardo Bianchini, Kathryn S. McKinley
Exploiting heterogeneity for tail latency and energy efficiency. MICRO (2017)
Xinning Hui, Zhihui Du, Jason Liu, Hongyang Sun, Yuxiong He, David A. Bader
When Good Enough Is Better: Energy-Aware Scheduling for Multicore Servers. IPDPS Workshops (2017)
Wei Wen, Yuxiong He, Samyam Rajbhandari, Wenhan Wang, Fang Liu, Bin Hu, Yiran Chen, Hai Li
Learning Intrinsic Sparse Structures within Long Short-term Memory. CoRR (2017)
Jeff Rasley, Yuxiong He, Feng Yan, Olatunji Ruwase, Rodrigo Fonseca
HyperDrive: exploring hyperparameters with POP scheduling. Middleware (2017)
Conglong Li, David G. Andersen, Qiang Fu, Sameh Elnikety, Yuxiong He
Workload analysis and caching strategies for search advertising systems. SoCC (2017)
Arpan Gujarati, Sameh Elnikety, Yuxiong He, Kathryn S. McKinley, Björn B. Brandenburg
Swayam: distributed autoscaling to meet SLAs of machine learning inference services with resource efficiency. Middleware (2017)
Samyam Rajbhandari, Yuxiong He, Olatunji Ruwase, Michael Carbin, Trishul M. Chilimbi
Optimizing CNNs on Multicores for Scalability, Performance and Goodput. ASPLOS (2017)

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Publication Activity (10 Years)

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Yuxiong He