Gennady Pekhimenko

146 papers A* 30A 6B 7Journal 71Unranked 29

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	BHCast: Unlocking Black Hole Plasma Dynamics from a Single Blurry Image with Long-Term Forecasting. CoRR Renbo Tu, Ali SaraerToosi, Nicholas S. Conroy, Gennady Pekhimenko, Aviad Levis
2026	J	`jnl`	Fusing Adds and Shifts for Efficient Dot Products. IEEE Comput. Archit. Lett. Pavel Golikov, Karthik Ganesan, Gennady Pekhimenko, Mark C. Jeffrey
2026	A	`conf`	Hexcute: A Compiler Framework for Automating Layout Synthesis in GPU Programs. CGO Xiao Zhang, Yaoyao Ding, Bolin Sun, Yang Hu, Tatiana Shpeisman, Gennady Pekhimenko
2026	A	`conf`	LoRAFusion: Efficient LoRA Fine-Tuning for LLMs. EuroSys Zhanda Zhu, Qidong Su, Yaoyao Ding, Kevin Song, Shang Wang, Gennady Pekhimenko
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`	A Tensor Compiler for Processing-In-Memory Architectures. CoRR Peiming Yang, Sankeerth Durvasula, Ivan Fernandez, Mohammad Sadrosadati, Onur Mutlu, Gennady Pekhimenko, Christina Giannoula
2025	—	`conf`	APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts. ACL (1) Honghua Dong, Qidong Su, Yubo Gao, Zhaoyu Li, Yangjun Ruan, Gennady Pekhimenko, Chris J. Maddison, Xujie Si
2025	J	`jnl`	Aegis: Taxonomy and Optimizations for Overcoming Agent-Environment Failures in LLM Agents. CoRR Kevin Song, Anand Jayarajan, Yaoyao Ding, Qidong Su, Zhanda Zhu, Sihang Liu, Gennady Pekhimenko
2025	J	`jnl`	DPQuant: Efficient and Differentially-Private Model Training via Dynamic Quantization Scheduling. CoRR Yubo Gao, Renbo Tu, Gennady Pekhimenko, Nandita Vijaykumar
2025	J	`jnl`	Hexcute: A Tile-based Programming Language with Automatic Layout and Task-Mapping Synthesis. CoRR Xiao Zhang, Yaoyao Ding, Yang Hu, Gennady Pekhimenko
2025	—	`conf`	HybridTier: an Adaptive and Lightweight CXL-Memory Tiering System. ASPLOS (3) Kevin Song, Jiacheng Yang, Zixuan Wang, Jishen Zhao, Sihang Liu, Gennady Pekhimenko
2025	J	`jnl`	LoRAFusion: Efficient LoRA Fine-Tuning for LLMs. CoRR Zhanda Zhu, Qidong Su, Yaoyao Ding, Kevin Song, Shang Wang, Gennady Pekhimenko
2025	A	`conf`	Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization. EuroSys Zhanda Zhu, Christina Giannoula, Muralidhar Andoorveedu, Qidong Su, Karttikeya Mangalam, Bojian Zheng, Gennady Pekhimenko
2025	J	`jnl`	Mist: Efficient Distributed Training of Large Language Models via Memory-Parallelism Co-Optimization. CoRR Zhanda Zhu, Christina Giannoula, Muralidhar Andoorveedu, Qidong Su, Karttikeya Mangalam, Bojian Zheng, Gennady Pekhimenko
2025	—	`conf`	PyGim: An Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures. SIGMETRICS (Abstracts) Christina Giannoula, Peiming Yang, Ivan Fernandez, Jiacheng Yang, Sankeerth Durvasula, Yu Xin Li, Mohammad Sadrosadati, Juan Gómez-Luna, Onur Mutlu, Gennady Pekhimenko
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	—	`conf`	Seesaw: High-throughput LLM Inference via Model Re-sharding. MLSys Qidong Su, Wei Zhao, Xin Li, Muralidhar Andoorveedu, Chenhao Jiang, Zhanda Zhu, Kevin Song, Christina Giannoula, Gennady Pekhimenko
2025	J	`jnl`	Seesaw: High-throughput LLM Inference via Model Re-sharding. CoRR Qidong Su, Wei Zhao, Xin Li, Muralidhar Andoorveedu, Chenhao Jiang, Zhanda Zhu, Kevin Song, Christina Giannoula, Gennady Pekhimenko
2025	—	`conf`	Tally: Non-Intrusive Performance Isolation for Concurrent Deep Learning Workloads. ASPLOS (1) Wei Zhao, Anand Jayarajan, 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
2025	A*	`conf`	TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories. ICML Honghua Dong, Jiacheng Yang, Xun Deng, Yuhe Jiang, Gennady Pekhimenko, Fan Long, Xujie Si
2025	J	`jnl`	TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories. CoRR Honghua Dong, Jiacheng Yang, Xun Deng, Yuhe Jiang, Gennady Pekhimenko, Fan Long, Xujie Si
2025	J	`jnl`	What Limits Agentic Systems Efficiency? CoRR Song Bian, Minghao Yan, Anand Jayarajan, Gennady Pekhimenko, Shivaram Venkataraman
2024	J	`jnl`	APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts. CoRR Honghua Dong, Qidong Su, Yubo Gao, Zhaoyu Li, Yangjun Ruan, Gennady Pekhimenko, Chris J. Maddison, Xujie Si
2024	J	`jnl`	Accelerating Graph Neural Networks on Real Processing-In-Memory Systems. CoRR Christina Giannoula, Peiming Yang, Ivan Fernandez Vega, Jiacheng Yang, Yu Xin Li, Juan Gómez-Luna, Mohammad Sadrosadati, Onur Mutlu, Gennady Pekhimenko
2024	B	`conf`	BOOM: Use your Desktop to Accurately Predict the Performance of Large Deep Neural Networks. PACT Qidong Su, Jiacheng Yang, Gennady Pekhimenko
2024	A*	`conf`	Guaranteed Approximation Bounds for Mixed-Precision Neural Operators. ICLR Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar
2024	A	`conf`	Minuet: Accelerating 3D Sparse Convolutions on GPUs. EuroSys Jiacheng Yang, Christina Giannoula, Jun Wu, Mostafa Elhoushi, James Gleeson, Gennady Pekhimenko
2024	J	`jnl`	Minuet: Accelerating 3D Sparse Convolutions on GPUs. CoRR Jiacheng Yang, Christina Giannoula, Jun Wu, Mostafa Elhoushi, James Gleeson, Gennady Pekhimenko
2024	—	`ed.`	Proceedings of the Seventh Annual Conference on Machine Learning and Systems, MLSys 2024, Santa Clara, CA, USA, May 13-16, 2024 MLSys Phillip B. Gibbons, Gennady Pekhimenko, Christopher De Sa
2024	—	`conf`	Proteus: Preserving Model Confidentiality during Graph Optimizations. MLSys Yubo Gao, Maryam Haghifam, Christina Giannoula, Renbo Tu, Gennady Pekhimenko, Nandita Vijaykumar
2024	J	`jnl`	Proteus: Preserving Model Confidentiality during Graph Optimizations. CoRR Yubo Gao, Maryam Haghifam, Christina Giannoula, Renbo Tu, Gennady Pekhimenko, Nandita Vijaykumar
2024	J	`jnl`	PyGim : An Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures. Proc. ACM Meas. Anal. Comput. Syst. Christina Giannoula, Peiming Yang, Ivan Fernandez, Jiacheng Yang, Sankeerth Durvasula, Yu Xin Li, Mohammad Sadrosadati, Juan Gómez-Luna, Onur Mutlu, Gennady Pekhimenko
2024	A	`conf`	Sylva: Sparse Embedded Adapters via Hierarchical Approximate Second-Order Information. ICS Baorun Mu, Christina Giannoula, Shang Wang, Gennady Pekhimenko
2024	J	`jnl`	Tally: Non-Intrusive Performance Isolation for Concurrent Deep Learning Workloads. CoRR Wei Zhao, Anand Jayarajan, Gennady Pekhimenko
2023	—	`conf`	Arbitor: A Numerically Accurate Hardware Emulation Tool for DNN Accelerators. USENIX ATC Chenhao Jiang, Anand Jayarajan, Hao Lu, Gennady Pekhimenko
2023	J	`jnl`	Federated benchmarking of medical artificial intelligence with MedPerf. Nat. Mac. Intell. Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Anna Wuest, Sarthak Pati, Hasan Kassem, Maximilian Zenk, Ujjwal Baid, Prakash Narayana Moorthy, Alexander Chowdhury, Junyi Guo, Sahil S. Nalawade, Jacob Rosenthal, David Kanter, Maria Xenochristou, Daniel J. Beutel, Verena Chung, Timothy Bergquist, James A. Eddy, Abubakar Abid, Lewis Tunstall, Omar Sanseviero, Dimitrios Dimitriadis, Yiming Qian, Xinxing Xu, Yong Liu, Rick Siow Mong Goh, Srini Bala, Victor Bittorf, Sreekar Reddy Puchala, Biagio Ricciuti, Soujanya Samineni, Eshna Sengupta, Akshay Chaudhari, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Cassiano Ferro Moraes, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Abhishek Singh, Jayaraman J. Thiagarajan, Jacob Albrecht, Thomas Wolf, Geralyn Miller, Huazhu Fu, Prashant Shah, Daguang Xu, Poonam Yadav, David Talby, Mark M. Awad, Jeremy P. Howard, Michael Rosenthal, Luigi Marchionni, Massimo Loda, Jason M. Johnson, Spyridon Bakas, Peter Mattson
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	—	`conf`	Hotline Profiler: Automatic Annotation and A Multi-Scale Timeline for Visualizing Time-Use in DNN Training. MLSys Daniel Snider, Fanny Chevalier, Gennady Pekhimenko
2023	J	`jnl`	Lightweight Frequency-Based Tiering for CXL Memory Systems. CoRR Kevin Song, Jiacheng Yang, Sihang Liu, Gennady Pekhimenko
2023	J	`jnl`	Speeding up Fourier Neural Operators via Mixed Precision. CoRR Colin White, Renbo Tu, Jean Kossaifi, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar
2023	J	`jnl`	The Synergy of Speculative Decoding and Batching in Serving Large Language Models. CoRR Qidong Su, Christina Giannoula, Gennady Pekhimenko
2023	—	`conf`	TiLT: A Time-Centric Approach for Stream Query Optimization and Parallelization. ASPLOS (2) Anand Jayarajan, Wei Zhao, Yudi Sun, Gennady Pekhimenko
2023	J	`jnl`	TiLT: A Time-Centric Approach for Stream Query Optimization and Parallelization. CoRR Anand Jayarajan, Wei Zhao, Yudi Sun, Gennady Pekhimenko
2023	B	`conf`	TorchProbe: Fuzzing Dynamic Deep Learning Compilers. APLAS Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si
2023	J	`jnl`	TorchProbe: Fuzzing Dynamic Deep Learning Compilers. CoRR Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si
2022	A	`conf`	Automatic Horizontal Fusion for GPU Kernels. CGO Ao Li, Bojian Zheng, Gennady Pekhimenko, Fan Long
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	B	`conf`	GPUPool: A Holistic Approach to Fine-Grained GPU Sharing in the Cloud. PACT Xiaodan Serina Tan, Pavel Golikov, Nandita Vijaykumar, 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	—	`conf`	How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU. CHIL Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg
2022	—	`conf`	Keynote Talk 1: Efficient DNN Training at Scale: from Algorithms to Hardware. IPDPS Workshops Gennady Pekhimenko
2022	J	`jnl`	Optimizing Data Collection in Deep Reinforcement Learning. CoRR James Gleeson, Daniel Snider, Yvonne Yang, Moshe Gabel, Eyal de Lara, Gennady Pekhimenko
2022	B	`conf`	Pavise: Integrating Fault Tolerance Support for Persistent Memory Applications. PACT Han Jie Qiu, Sihang Liu, Xinyang Song, Samira Manabi Khan, Gennady Pekhimenko
2022	A*	`conf`	ROLLER: Fast and Efficient Tensor Compilation for Deep Learning. OSDI Hongyu Zhu, Ruofan Wu, Yijia Diao, Shanbin Ke, Haoyu Li, Chen Zhang, Jilong Xue, Lingxiao Ma, Yuqing Xia, Wei Cui, Fan Yang, Mao Yang, Lidong Zhou, Asaf Cidon, Gennady Pekhimenko
2022	A*	`conf`	Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction. NeurIPS Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng, Gennady Pekhimenko
2022	J	`jnl`	Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction. CoRR Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng, Gennady Pekhimenko
2021	—	`conf`	Boveda: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick. MLSys Isak Edo Vivancos, Sayeh Sharify, Daniel Ly-Ma, Ameer Abdelhadi, Ciaran Bannon, Milos Nikolic, Mostafa Mahmoud, Alberto Delmas Lascorz, Gennady Pekhimenko, Andreas Moshovos
2021	J	`jnl`	Computational Performance Predictions for Deep Neural Network Training: A Runtime-Based Approach. CoRR Geoffrey X. Yu, Yubo Gao, Pavel Golikov, Gennady Pekhimenko
2021	A*	`conf`	Distributed Deep Learning In Open Collaborations. NeurIPS Michael Diskin, Alexey Bukhtiyarov, Max Ryabinin, Lucile Saulnier, Quentin Lhoest, Anton Sinitsin, Dmitry Popov, Dmitry V. Pyrkin, Maxim Kashirin, Alexander Borzunov, Albert Villanova del Moral, Denis Mazur, Ilia Kobelev, Yacine Jernite, Thomas Wolf, Gennady Pekhimenko
2021	J	`jnl`	Distributed Deep Learning in Open Collaborations. CoRR Michael Diskin, Alexey Bukhtiyarov, Max Ryabinin, Lucile Saulnier, Quentin Lhoest, Anton Sinitsin, Dmitry Popov, Dmitry V. Pyrkin, Maxim Kashirin, Alexander Borzunov, Albert Villanova del Moral, Denis Mazur, Ilia Kobelev, Yacine Jernite, Thomas Wolf, Gennady Pekhimenko
2021	A*	`conf`	FPRaker: A Processing Element For Accelerating Neural Network Training. MICRO Omar Mohamed Awad, Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Ciaran Bannon, Anand Jayarajan, Gennady Pekhimenko, Andreas Moshovos
2021	J	`jnl`	Gretch: A Hardware Prefetcher for Graph Analytics. ACM Trans. Archit. Code Optim. Anirudh Mohan Kaushik, Gennady Pekhimenko, Hiren D. Patel
2021	—	`conf`	Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training. USENIX ATC Geoffrey X. Yu, Yubo Gao, Pavel Golikov, Gennady Pekhimenko
2021	—	`conf`	Horizontally Fused Training Array: An Effective Hardware Utilization Squeezer for Training Novel Deep Learning Models. MLSys Shang Wang, Peiming Yang, Yuxuan Zheng, Xin Li, Gennady Pekhimenko
2021	J	`jnl`	Horizontally Fused Training Array: An Effective Hardware Utilization Squeezer for Training Novel Deep Learning Models. CoRR Shang Wang, Peiming Yang, Yuxuan Zheng, Xin Li, Gennady Pekhimenko
2021	—	`conf`	IOS: Inter-Operator Scheduler for CNN Acceleration. MLSys Yaoyao Ding, Ligeng Zhu, Zhihao Jia, Gennady Pekhimenko, Song Han
2021	A*	`conf`	LifeStream: a high-performance stream processing engine for periodic streams. ASPLOS Anand Jayarajan, Kimberly Hau, Andrew Goodwin, Gennady Pekhimenko
2021	J	`jnl`	MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. CoRR Alexandros Karargyris, Renato Umeton, Micah J. Sheller, Alejandro Aristizabal, Johnu George, Srini Bala, Daniel J. Beutel, Victor Bittorf, Akshay Chaudhari, Alexander Chowdhury, Cody Coleman, Bala Desinghu, Gregory F. Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Junyi Guo, Xinyuan Huang, David Kanter, Satyananda Kashyap, Nicholas D. Lane, Indranil Mallick, Pietro Mascagni, Virendra Mehta, Vivek Natarajan, Nikola Nikolov, Nicolas Padoy, Gennady Pekhimenko, Vijay Janapa Reddi, G. Anthony Reina, Pablo Ribalta, Jacob Rosenthal, Abhishek Singh, Jayaraman J. Thiagarajan, Anna Wuest, Maria Xenochristou, Daguang Xu, Poonam Yadav, Michael Rosenthal, Massimo Loda, Jason M. Johnson, Peter Mattson
2021	A*	`conf`	Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. NeurIPS Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko
2021	J	`jnl`	Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. CoRR Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko
2021	A*	`conf`	NVOverlay: Enabling Efficient and Scalable High-Frequency Snapshotting to NVM. ISCA Ziqi Wang, Chul-Hwan Choo, Michael A. Kozuch, Todd C. Mowry, Gennady Pekhimenko, Vivek Seshadri, Dimitrios Skarlatos
2021	J	`jnl`	RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads. CoRR James Gleeson, Srivatsan Krishnan, Moshe Gabel, Vijay Janapa Reddi, Eyal de Lara, Gennady Pekhimenko
2021	—	`conf`	RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads. MLSys James Gleeson, Moshe Gabel, Gennady Pekhimenko, Eyal de Lara, Srivatsan Krishnan, Vijay Janapa Reddi
2020	J	`jnl`	Automatic Horizontal Fusion for GPU Kernels. CoRR Ao Li, Bojian Zheng, Gennady Pekhimenko, Fan Long
2020	—	`conf`	BPPSA: Scaling Back-propagation by Parallel Scan Algorithm. MLSys Shang Wang, Yifan Bai, Gennady Pekhimenko
2020	—	`conf`	Daydream: Accurately Estimating the Efficacy of Optimizations for DNN Training. USENIX ATC Hongyu Zhu, Amar Phanishayee, Gennady Pekhimenko
2020	J	`jnl`	Daydream: Accurately Estimating the Efficacy of Optimizations for DNN Training. CoRR Hongyu Zhu, Amar Phanishayee, Gennady Pekhimenko
2020	A*	`conf`	Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training. ISCA Bojian Zheng, Nandita Vijaykumar, Gennady Pekhimenko
2020	J	`jnl`	FPRaker: A Processing Element For Accelerating Neural Network Training. CoRR Omar Mohamed Awad, Mostafa Mahmoud, Isak Edo Vivancos, Ali Hadi Zadeh, Ciaran Bannon, Anand Jayarajan, Gennady Pekhimenko, Andreas Moshovos
2020	J	`jnl`	IOS: Inter-Operator Scheduler for CNN Acceleration. CoRR Yaoyao Ding, Ligeng Zhu, Zhihao Jia, Gennady Pekhimenko, Song Han
2020	J	`jnl`	LifeStream: A High-performance Stream Processing Engine for Waveform Data. CoRR Anand Jayarajan, Kimberly Hau, Andrew Goodwin, Gennady Pekhimenko
2020	A*	`conf`	MLPerf Inference Benchmark. ISCA Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou
2020	—	`conf`	MLPerf Training Benchmark. MLSys Peter Mattson, Christine Cheng, Gregory F. Diamos, Cody Coleman, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debo Dutta, Udit Gupta, Kim M. Hazelwood, Andy Hock, Xinyuan Huang, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia
2020	J	`jnl`	Multi-node Bert-pretraining: Cost-efficient Approach. CoRR Jiahuang Lin, Xin Li, Gennady Pekhimenko
2020	A*	`conf`	Skyline: Interactive In-Editor Computational Performance Profiling for Deep Neural Network Training. UIST Geoffrey X. Yu, Tovi Grossman, Gennady Pekhimenko
2020	J	`jnl`	Skyline: Interactive In-Editor Computational Performance Profiling for Deep Neural Network Training. CoRR Geoffrey X. Yu, Tovi Grossman, Gennady Pekhimenko
2020	J	`jnl`	TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference. CoRR Mostafa Mahmoud, Isak Edo Vivancos, Ali Hadi Zadeh, Omar Mohamed Awad, Gennady Pekhimenko, Jorge Albericio, Andreas Moshovos
2020	A*	`conf`	TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training. MICRO Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Omar Mohamed Awad, Gennady Pekhimenko, Jorge Albericio, Andreas Moshovos
2019	A*	`conf`	Janus: optimizing memory and storage support for non-volatile memory systems. ISCA Sihang Liu, Korakit Seemakhupt, Gennady Pekhimenko, Aasheesh Kolli, Samira Manabi Khan
2019	J	`jnl`	MLPerf Inference Benchmark. CoRR Vijay Janapa Reddi, Christine Cheng, David Kanter, Peter Mattson, Guenther Schmuelling, Carole-Jean Wu, Brian Anderson, Maximilien Breughe, Mark Charlebois, William Chou, Ramesh Chukka, Cody Coleman, Sam Davis, Pan Deng, Greg Diamos, Jared Duke, Dave Fick, J. Scott Gardner, Itay Hubara, Sachin Idgunji, Thomas B. Jablin, Jeff Jiao, Tom St. John, Pankaj Kanwar, David Lee, Jeffery Liao, Anton Lokhmotov, Francisco Massa, Peng Meng, Paulius Micikevicius, Colin Osborne, Gennady Pekhimenko, Arun Tejusve Raghunath Rajan, Dilip Sequeira, Ashish Sirasao, Fei Sun, Hanlin Tang, Michael Thomson, Frank Wei, Ephrem Wu, Lingjie Xu, Koichi Yamada, Bing Yu, George Yuan, Aaron Zhong, Peizhao Zhang, Yuchen Zhou
2019	J	`jnl`	MLPerf Training Benchmark. CoRR Peter Mattson, Christine Cheng, Cody Coleman, Greg Diamos, Paulius Micikevicius, David A. Patterson, Hanlin Tang, Gu-Yeon Wei, Peter Bailis, Victor Bittorf, David Brooks, Dehao Chen, Debojyoti Dutta, Udit Gupta, Kim M. Hazelwood, Andrew Hock, Xinyuan Huang, Bill Jia, Daniel Kang, David Kanter, Naveen Kumar, Jeffery Liao, Guokai Ma, Deepak Narayanan, Tayo Oguntebi, Gennady Pekhimenko, Lillian Pentecost, Vijay Janapa Reddi, Taylor Robie, Tom St. John, Carole-Jean Wu, Lingjie Xu, Cliff Young, Matei Zaharia
2019	—	`conf`	Priority-based Parameter Propagation for Distributed DNN Training. SysML Anand Jayarajan, Jinliang Wei, Garth Gibson, Alexandra Fedorova, Gennady Pekhimenko
2019	J	`jnl`	Priority-based Parameter Propagation for Distributed DNN Training. CoRR Anand Jayarajan, Jinliang Wei, Garth Gibson, Alexandra Fedorova, Gennady Pekhimenko
2019	J	`jnl`	Scaling Back-propagation by Parallel Scan Algorithm. CoRR Shang Wang, Yifan Bai, Gennady Pekhimenko
2019	A*	`conf`	StreamBox-HBM: Stream Analytics on High Bandwidth Hybrid Memory. ASPLOS Hongyu Miao, Myeongjae Jeon, Gennady Pekhimenko, Kathryn S. McKinley, Felix Xiaozhu Lin
2019	J	`jnl`	StreamBox-HBM: Stream Analytics on High Bandwidth Hybrid Memory. CoRR Hongyu Miao, Myeongjae Jeon, Gennady Pekhimenko, Kathryn S. McKinley, Felix Xiaozhu Lin
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
2019	—	`ch.`	Towards Breaking the Memory Bandwidth Wall Using Approximate Value Prediction. Approximate Circuits Amir Yazdanbakhsh, Gennady Pekhimenko, Hadi Esmaeilzadeh, Onur Mutlu, Todd C. Mowry
2018	A*	`conf`	A Case for Richer Cross-Layer Abstractions: Bridging the Semantic Gap with Expressive Memory. ISCA Nandita Vijaykumar, Abhilasha Jain, Diptesh Majumdar, Kevin Hsieh, Gennady Pekhimenko, Eiman Ebrahimi, Nastaran Hajinazar, Phillip B. Gibbons, Onur Mutlu
2018	J	`jnl`	Adaptive-Latency DRAM: Reducing DRAM Latency by Exploiting Timing Margins. CoRR Donghyuk Lee, Yoongu Kim, Gennady Pekhimenko, Samira Manabi Khan, Vivek Seshadri, Kevin K. Chang, Onur Mutlu
2018	—	`conf`	Benchmarking and Analyzing Deep Neural Network Training. IISWC Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Anand Jayarajan, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko
2018	—	`conf`	Compiler-driven performance workshop. CASCON Gennady Pekhimenko, Ettore Tiotto
2018	J	`jnl`	Decoupling GPU Programming Models from Resource Management for Enhanced Programming Ease, Portability, and Performance. CoRR Nandita Vijaykumar, Kevin Hsieh, Gennady Pekhimenko, Samira Manabi Khan, Ashish Shrestha, Saugata Ghose, Adwait Jog, Phillip B. Gibbons, Onur Mutlu
2018	J	`jnl`	EcoRNN: Fused LSTM RNN Implementation with Data Layout Optimization. CoRR Bojian Zheng, Akshay Nair, Qiongsi Wu, Nandita Vijaykumar, Gennady Pekhimenko
2018	J	`jnl`	Exploiting Row-Level Temporal Locality in DRAM to Reduce the Memory Access Latency. CoRR Hasan Hassan, Gennady Pekhimenko, Nandita Vijaykumar, Vivek Seshadri, Donghyuk Lee, Oguz Ergin, Onur Mutlu
2018	J	`jnl`	Flexible-Latency DRAM: Understanding and Exploiting Latency Variation in Modern DRAM Chips. CoRR Kevin K. Chang, Abhijith Kashyap, Hasan Hassan, Saugata Ghose, Kevin Hsieh, Donghyuk Lee, Tianshi Li, Gennady Pekhimenko, Samira Manabi Khan, Onur Mutlu
2018	A*	`conf`	Gist: Efficient Data Encoding for Deep Neural Network Training. ISCA Animesh Jain, Amar Phanishayee, Jason Mars, Lingjia Tang, Gennady Pekhimenko
2018	J	`jnl`	RowClone: Accelerating Data Movement and Initialization Using DRAM. CoRR Vivek Seshadri, Yoongu Kim, Chris Fallin, Donghyuk Lee, Rachata Ausavarungnirun, Gennady Pekhimenko, Yixin Luo, Onur Mutlu, Phillip B. Gibbons, Michael A. Kozuch, Todd C. Mowry
2018	J	`jnl`	SoftMC: Practical DRAM Characterization Using an FPGA-Based Infrastructure. CoRR Hasan Hassan, Nandita Vijaykumar, Samira Manabi Khan, Saugata Ghose, Kevin K. Chang, Gennady Pekhimenko, Donghyuk Lee, Oguz Ergin, Onur Mutlu
2018	J	`jnl`	TBD: Benchmarking and Analyzing Deep Neural Network Training. CoRR Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko
2018	—	`conf`	TerseCades: Efficient Data Compression in Stream Processing. USENIX ATC Gennady Pekhimenko, Chuanxiong Guo, Myeongjae Jeon, Peng Huang, Lidong Zhou
2018	J	`jnl`	Zorua: Enhancing Programming Ease, Portability, and Performance in GPUs by Decoupling Programming Models from Resource Management. CoRR Nandita Vijaykumar, Kevin Hsieh, Gennady Pekhimenko, Samira Manabi Khan, Ashish Shrestha, Saugata Ghose, Phillip B. Gibbons, Onur Mutlu
2017	—	`conf`	Design-Induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms. SIGMETRICS (Abstracts) Donghyuk Lee, Samira Manabi Khan, Lavanya Subramanian, Saugata Ghose, Rachata Ausavarungnirun, Gennady Pekhimenko, Vivek Seshadri, Onur Mutlu
2017	J	`jnl`	Design-Induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms. Proc. ACM Meas. Anal. Comput. Syst. Donghyuk Lee, Samira Manabi Khan, Lavanya Subramanian, Saugata Ghose, Rachata Ausavarungnirun, Gennady Pekhimenko, Vivek Seshadri, Onur Mutlu
2017	A*	`conf`	SoftMC: A Flexible and Practical Open-Source Infrastructure for Enabling Experimental DRAM Studies. HPCA Hasan Hassan, Nandita Vijaykumar, Samira Manabi Khan, Saugata Ghose, Kevin K. Chang, Gennady Pekhimenko, Donghyuk Lee, Oguz Ergin, Onur Mutlu
2017	—	`conf`	StreamBox: Modern Stream Processing on a Multicore Machine. USENIX ATC Hongyu Miao, Heejin Park, Myeongjae Jeon, Gennady Pekhimenko, Kathryn S. McKinley, Felix Xiaozhu Lin
2016	J	`jnl`	A Framework for Accelerating Bottlenecks in GPU Execution with Assist Warps. CoRR Nandita Vijaykumar, Gennady Pekhimenko, Adwait Jog, Saugata Ghose, Abhishek Bhowmick, Rachata Ausavarungnirun, Chita R. Das, Mahmut T. Kandemir, Todd C. Mowry, Onur Mutlu
2016	A*	`conf`	A case for toggle-aware compression for GPU systems. HPCA Gennady Pekhimenko, Evgeny Bolotin, Nandita Vijaykumar, Onur Mutlu, Todd C. Mowry, Stephen W. Keckler
2016	J	`jnl`	Adaptive-Latency DRAM (AL-DRAM). CoRR Donghyuk Lee, Yoongu Kim, Gennady Pekhimenko, Samira Manabi Khan, Vivek Seshadri, Kevin Kai-Wei Chang, Onur Mutlu
2016	A*	`conf`	ChargeCache: Reducing DRAM latency by exploiting row access locality. HPCA Hasan Hassan, Gennady Pekhimenko, Nandita Vijaykumar, Vivek Seshadri, Donghyuk Lee, Oguz Ergin, Onur Mutlu
2016	J	`jnl`	Mitigating the Memory Bottleneck With Approximate Load Value Prediction. IEEE Des. Test Amir Yazdanbakhsh, Bradley Thwaites, Hadi Esmaeilzadeh, Gennady Pekhimenko, Onur Mutlu, Todd C. Mowry
2016	J	`jnl`	Optimal seed solver: optimizing seed selection in read mapping. Bioinform. Hongyi Xin, Sunny Nahar, Richard L. Zhu, John Emmons, Gennady Pekhimenko, Carl Kingsford, Can Alkan, Onur Mutlu
2016	J	`jnl`	Practical Data Compression for Modern Memory Hierarchies. CoRR Gennady Pekhimenko
2016	J	`jnl`	RFVP: Rollback-Free Value Prediction with Safe-to-Approximate Loads. ACM Trans. Archit. Code Optim. Amir Yazdanbakhsh, Gennady Pekhimenko, Bradley Thwaites, Hadi Esmaeilzadeh, Onur Mutlu, Todd C. Mowry
2016	J	`jnl`	Reducing DRAM Latency by Exploiting Design-Induced Latency Variation in Modern DRAM Chips. CoRR Donghyuk Lee, Samira Manabi Khan, Lavanya Subramanian, Rachata Ausavarungnirun, Gennady Pekhimenko, Vivek Seshadri, Saugata Ghose, Onur Mutlu
2016	J	`jnl`	Simultaneous Multi-Layer Access: Improving 3D-Stacked Memory Bandwidth at Low Cost. ACM Trans. Archit. Code Optim. Donghyuk Lee, Saugata Ghose, Gennady Pekhimenko, Samira Manabi Khan, Onur Mutlu
2016	A*	`conf`	Understanding Latency Variation in Modern DRAM Chips: Experimental Characterization, Analysis, and Optimization. SIGMETRICS Kevin K. Chang, Abhijith Kashyap, Hasan Hassan, Saugata Ghose, Kevin Hsieh, Donghyuk Lee, Tianshi Li, Gennady Pekhimenko, Samira Manabi Khan, Onur Mutlu
2016	A*	`conf`	Zorua: A holistic approach to resource virtualization in GPUs. MICRO Nandita Vijaykumar, Kevin Hsieh, Gennady Pekhimenko, Samira Manabi Khan, Ashish Shrestha, Saugata Ghose, Adwait Jog, Phillip B. Gibbons, Onur Mutlu
2015	A*	`conf`	A case for core-assisted bottleneck acceleration in GPUs: enabling flexible data compression with assist warps. ISCA Nandita Vijaykumar, Gennady Pekhimenko, Adwait Jog, Abhishek Bhowmick, Rachata Ausavarungnirun, Chita R. Das, Mahmut T. Kandemir, Todd C. Mowry, Onur Mutlu
2015	A*	`conf`	Adaptive-latency DRAM: Optimizing DRAM timing for the common-case. HPCA Donghyuk Lee, Yoongu Kim, Gennady Pekhimenko, Samira Manabi Khan, Vivek Seshadri, Kevin Kai-Wei Chang, Onur Mutlu
2015	A*	`conf`	Exploiting compressed block size as an indicator of future reuse. HPCA Gennady Pekhimenko, Tyler Huberty, Rui Cai, Onur Mutlu, Phillip B. Gibbons, Michael A. Kozuch, Todd C. Mowry
2015	J	`jnl`	Optimal Seed Solver: Optimizing Seed Selection in Read Mapping. CoRR Hongyi Xin, Richard L. Zhu, Sunny Nahar, John Emmons, Gennady Pekhimenko, Carl Kingsford, Can Alkan, Onur Mutlu
2015	A*	`conf`	Page overlays: an enhanced virtual memory framework to enable fine-grained memory management. ISCA Vivek Seshadri, Gennady Pekhimenko, Olatunji Ruwase, Onur Mutlu, Phillip B. Gibbons, Michael A. Kozuch, Todd C. Mowry, Trishul M. Chilimbi
2015	A*	`conf`	PocketTrend: Timely Identification and Delivery of Trending Search Content to Mobile Users. WWW Gennady Pekhimenko, Dimitrios Lymberopoulos, Oriana Riva, Karin Strauss, Doug Burger
2015	J	`jnl`	Shifted Hamming distance: a fast and accurate SIMD-friendly filter to accelerate alignment verification in read mapping. Bioinform. Hongyi Xin, John Greth, John Emmons, Gennady Pekhimenko, Carl Kingsford, Can Alkan, Onur Mutlu
2015	J	`jnl`	Simultaneous Multi Layer Access: A High Bandwidth and Low Cost 3D-Stacked Memory Interface. CoRR Donghyuk Lee, Gennady Pekhimenko, Samira Manabi Khan, Saugata Ghose, Onur Mutlu
2015	J	`jnl`	Toggle-Aware Compression for GPUs. IEEE Comput. Archit. Lett. Gennady Pekhimenko, Evgeny Bolotin, Mike O'Connor, Onur Mutlu, Todd C. Mowry, Stephen W. Keckler
2014	B	`conf`	Rollback-free value prediction with approximate loads. PACT Bradley Thwaites, Gennady Pekhimenko, Hadi Esmaeilzadeh, Amir Yazdanbakhsh, Onur Mutlu, Jongse Park, Girish Mururu, Todd C. Mowry
2013	A*	`conf`	Linearly compressed pages: a low-complexity, low-latency main memory compression framework. MICRO Gennady Pekhimenko, Vivek Seshadri, Yoongu Kim, Hongyi Xin, Onur Mutlu, Phillip B. Gibbons, Michael A. Kozuch, Todd C. Mowry
2013	A*	`conf`	RowClone: fast and energy-efficient in-DRAM bulk data copy and initialization. MICRO Vivek Seshadri, Yoongu Kim, Chris Fallin, Donghyuk Lee, Rachata Ausavarungnirun, Gennady Pekhimenko, Yixin Luo, Onur Mutlu, Phillip B. Gibbons, Michael A. Kozuch, Todd C. Mowry
2012	B	`conf`	Base-delta-immediate compression: practical data compression for on-chip caches. PACT Gennady Pekhimenko, Vivek Seshadri, Onur Mutlu, Phillip B. Gibbons, Michael A. Kozuch, Todd C. Mowry
2012	B	`conf`	Linearly compressed pages: a main memory compression framework with low complexity and low latency. PACT Gennady Pekhimenko, Todd C. Mowry, Onur Mutlu
2010	—	`ch.`	Efficient Program Compilation Through Machine Learning Techniques. Software Automatic Tuning, From Concepts to State-of-the-Art Results Gennady Pekhimenko, Angela Demke Brown