Gennady Pekhimenko

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 102

Top Venues

CoRR

MLSys

ISCA

USENIX Annual Technical Conference

Publications

Baorun Mu, Christina Giannoula, Shang Wang, Gennady Pekhimenko
Sylva: Sparse Embedded Adapters via Hierarchical Approximate Second-Order Information. ICS (2024)
Honghua Dong, Qidong Su, Yubo Gao, Zhaoyu Li, Yangjun Ruan, Gennady Pekhimenko, Chris J. Maddison, Xujie Si
APPL: A Prompt Programming Language for Harmonious Integration of Programs and Large Language Model Prompts. CoRR (2024)
Christina Giannoula, Peiming Yang, Ivan Fernandez Vega, Jiacheng Yang, Yu Xin Li, Juan Gómez-Luna, Mohammad Sadrosadati, Onur Mutlu, Gennady Pekhimenko
Accelerating Graph Neural Networks on Real Processing-In-Memory Systems. CoRR (2024)
Renbo Tu, Colin White, Jean Kossaifi, Boris Bonev, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar
Guaranteed Approximation Bounds for Mixed-Precision Neural Operators. ICLR (2024)
Yubo Gao, Maryam Haghifam, Christina Giannoula, Renbo Tu, Gennady Pekhimenko, Nandita Vijaykumar
Proteus: Preserving Model Confidentiality during Graph Optimizations. CoRR (2024)
Jiacheng Yang, Christina Giannoula, Jun Wu, Mostafa Elhoushi, James Gleeson, Gennady Pekhimenko
Minuet: Accelerating 3D Sparse Convolutions on GPUs. EuroSys (2024)
Yubo Gao, Maryam Haghifam, Christina Giannoula, Renbo Tu, Gennady Pekhimenko, Nandita Vijaykumar
Proteus: Preserving Model Confidentiality during Graph Optimizations. MLSys (2024)
Jiacheng Yang, Christina Giannoula, Jun Wu, Mostafa Elhoushi, James Gleeson, Gennady Pekhimenko
Minuet: Accelerating 3D Sparse Convolutions on GPUs. CoRR (2024)
Yaoyao Ding, Cody Hao Yu, Bojian Zheng, Yizhi Liu, Yida Wang, Gennady Pekhimenko
Hidet: Task-Mapping Programming Paradigm for Deep Learning Tensor Programs. ASPLOS (2) (2023)
Kevin Song, Jiacheng Yang, Sihang Liu, Gennady Pekhimenko
Lightweight Frequency-Based Tiering for CXL Memory Systems. CoRR (2023)
Anand Jayarajan, Wei Zhao, Yudi Sun, Gennady Pekhimenko
TiLT: A Time-Centric Approach for Stream Query Optimization and Parallelization. ASPLOS (2) (2023)
Qidong Su, Christina Giannoula, Gennady Pekhimenko
The Synergy of Speculative Decoding and Batching in Serving Large Language Models. CoRR (2023)
Chenhao Jiang, Anand Jayarajan, Hao Lu, Gennady Pekhimenko
Arbitor: A Numerically Accurate Hardware Emulation Tool for DNN Accelerators. USENIX Annual Technical Conference (2023)
Bojian Zheng, Cody Hao Yu, Jie Wang, Yaoyao Ding, Yizhi Liu, Yida Wang, Gennady Pekhimenko
Grape: Practical and Efficient Graphed Execution for Dynamic Deep Neural Networks on GPUs. MICRO (2023)
Anand Jayarajan, Wei Zhao, Yudi Sun, Gennady Pekhimenko
TiLT: A Time-Centric Approach for Stream Query Optimization and Parallelization. CoRR (2023)
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 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 Diamos, Debo Dutta, Diane Feddema, Grigori Fursin, Xinyuan Huang, Satyananda Kashyap, Nicholas 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
Federated benchmarking of medical artificial intelligence with MedPerf. Nat. Mac. Intell. 5 (7) (2023)
Daniel Snider, Fanny Chevalier, Gennady Pekhimenko
Hotline Profiler: Automatic Annotation and A Multi-Scale Timeline for Visualizing Time-Use in DNN Training. MLSys (2023)
Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si
TorchProbe: Fuzzing Dynamic Deep Learning Compilers. CoRR (2023)
Qidong Su, Chuqin Geng, Gennady Pekhimenko, Xujie Si
TorchProbe: Fuzzing Dynamic Deep Learning Compilers. APLAS (2023)
Colin White, Renbo Tu, Jean Kossaifi, Gennady Pekhimenko, Kamyar Azizzadenesheli, Anima Anandkumar
Speeding up Fourier Neural Operators via Mixed Precision. CoRR (2023)
Bojian Zheng, Ziheng Jiang, Cody Hao Yu, Haichen Shen, Joshua Fromm, Yizhi Liu, Yida Wang, Luis Ceze, Tianqi Chen, Gennady Pekhimenko
DietCode: Automatic Optimization for Dynamic Tensor Programs. MLSys (2022)
Gennady Pekhimenko
Keynote Talk 1: Efficient DNN Training at Scale: from Algorithms to Hardware. IPDPS Workshops (2022)
Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng, Gennady Pekhimenko
Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction. CoRR (2022)
Han Jie Qiu, Sihang Liu, Xinyang Song, Samira Manabi Khan, Gennady Pekhimenko
Pavise: Integrating Fault Tolerance Support for Persistent Memory Applications. PACT (2022)
James Gleeson, Daniel Snider, Yvonne Yang, Moshe Gabel, Eyal de Lara, Gennady Pekhimenko
Optimizing Data Collection in Deep Reinforcement Learning. CoRR (2022)
Sana Tonekaboni, Gabriela Morgenshtern, Azadeh Assadi, Aslesha Pokhrel, Xi Huang, Anand Jayarajan, Robert Greer, Gennady Pekhimenko, Melissa D. McCradden, Mjaye Mazwi, Anna Goldenberg
How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU. CHIL (2022)
Yaoyao Ding, Cody Hao Yu, Bojian Zheng, Yizhi Liu, Yida Wang, Gennady Pekhimenko
Hidet: Task Mapping Programming Paradigm for Deep Learning Tensor Programs. CoRR (2022)
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
ROLLER: Fast and Efficient Tensor Compilation for Deep Learning. OSDI (2022)
Ao Li, Bojian Zheng, Gennady Pekhimenko, Fan Long
Automatic Horizontal Fusion for GPU Kernels. CGO (2022)
Muralidhar Andoorveedu, Zhanda Zhu, Bojian Zheng, Gennady Pekhimenko
Tempo: Accelerating Transformer-Based Model Training through Memory Footprint Reduction. NeurIPS (2022)
Xiaodan Serina Tan, Pavel Golikov, Nandita Vijaykumar, Gennady Pekhimenko
GPUPool: A Holistic Approach to Fine-Grained GPU Sharing in the Cloud. PACT (2022)
Geoffrey X. Yu, Yubo Gao, Pavel Golikov, Gennady Pekhimenko
Computational Performance Predictions for Deep Neural Network Training: A Runtime-Based Approach. CoRR (2021)
Ziqi Wang, Chul-Hwan Choo, Michael A. Kozuch, Todd C. Mowry, Gennady Pekhimenko, Vivek Seshadri, Dimitrios Skarlatos
NVOverlay: Enabling Efficient and Scalable High-Frequency Snapshotting to NVM. ISCA (2021)
Michael Diskin, Alexey Bukhtiyarov, Max Ryabinin, Lucile Saulnier, Quentin Lhoest, Anton Sinitsin, Dmitriy Popov, Dmitry Pyrkin, Maxim Kashirin, Alexander Borzunov, Albert Villanova del Moral, Denis Mazur, Ilia Kobelev, Yacine Jernite, Thomas Wolf, Gennady Pekhimenko
Distributed Deep Learning in Open Collaborations. CoRR (2021)
James Gleeson, Srivatsan Krishnan, Moshe Gabel, Vijay Janapa Reddi, Eyal de Lara, Gennady Pekhimenko
RL-Scope: Cross-Stack Profiling for Deep Reinforcement Learning Workloads. CoRR (2021)
James Gleeson, Moshe Gabel, Gennady Pekhimenko, Eyal de Lara, Srivatsan Krishnan, Vijay Janapa Reddi
RL-Scope: Cross-stack Profiling for Deep Reinforcement Learning Workloads. MLSys (2021)
Anirudh Mohan Kaushik, Gennady Pekhimenko, Hiren D. Patel
Gretch: A Hardware Prefetcher for Graph Analytics. ACM Trans. Archit. Code Optim. 18 (2) (2021)
Omar Mohamed Awad, Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Ciaran Bannon, Anand Jayarajan, Gennady Pekhimenko, Andreas Moshovos
FPRaker: A Processing Element For Accelerating Neural Network Training. MICRO (2021)
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
Distributed Deep Learning In Open Collaborations. NeurIPS (2021)
Yaoyao Ding, Ligeng Zhu, Zhihao Jia, Gennady Pekhimenko, Song Han
IOS: Inter-Operator Scheduler for CNN Acceleration. MLSys (2021)
Isak Edo Vivancos, Sayeh Sharify, Daniel Ly-Ma, Ameer Abdelhadi, Ciaran Bannon, Milos Nikolic, Mostafa Mahmoud, Alberto Delmas Lascorz, Gennady Pekhimenko, Andreas Moshovos
Boveda: Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick. MLSys (2021)
Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. CoRR (2021)
Anand Jayarajan, Kimberly Hau, Andrew Goodwin, Gennady Pekhimenko
LifeStream: a high-performance stream processing engine for periodic streams. ASPLOS (2021)
Geoffrey X. Yu, Yubo Gao, Pavel Golikov, Gennady Pekhimenko
Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training. USENIX Annual Technical Conference (2021)
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
MedPerf: Open Benchmarking Platform for Medical Artificial Intelligence using Federated Evaluation. CoRR (2021)
Shang Wang, Peiming Yang, Yuxuan Zheng, Xin Li, Gennady Pekhimenko
Horizontally Fused Training Array: An Effective Hardware Utilization Squeezer for Training Novel Deep Learning Models. MLSys (2021)
Max Ryabinin, Eduard Gorbunov, Vsevolod Plokhotnyuk, Gennady Pekhimenko
Moshpit SGD: Communication-Efficient Decentralized Training on Heterogeneous Unreliable Devices. NeurIPS (2021)
Shang Wang, Peiming Yang, Yuxuan Zheng, Xin Li, Gennady Pekhimenko
Horizontally Fused Training Array: An Effective Hardware Utilization Squeezer for Training Novel Deep Learning Models. CoRR (2021)
Geoffrey X. Yu, Tovi Grossman, Gennady Pekhimenko
Skyline: Interactive In-Editor Computational Performance Profiling for Deep Neural Network Training. CoRR (2020)
Ao Li, Bojian Zheng, Gennady Pekhimenko, Fan Long
Automatic Horizontal Fusion for GPU Kernels. CoRR (2020)
Mostafa Mahmoud, Isak Edo Vivancos, Ali Hadi Zadeh, Omar Mohamed Awad, Gennady Pekhimenko, Jorge Albericio, Andreas Moshovos
TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training and Inference. CoRR (2020)
Shang Wang, Yifan Bai, Gennady Pekhimenko
BPPSA: Scaling Back-propagation by Parallel Scan Algorithm. MLSys (2020)
Mostafa Mahmoud, Isak Edo, Ali Hadi Zadeh, Omar Mohamed Awad, Gennady Pekhimenko, Jorge Albericio, Andreas Moshovos
TensorDash: Exploiting Sparsity to Accelerate Deep Neural Network Training. MICRO (2020)
Yaoyao Ding, Ligeng Zhu, Zhihao Jia, Gennady Pekhimenko, Song Han
IOS: Inter-Operator Scheduler for CNN Acceleration. CoRR (2020)
Jiahuang Lin, Xin Li, Gennady Pekhimenko
Multi-node Bert-pretraining: Cost-efficient Approach. CoRR (2020)
Geoffrey X. Yu, Tovi Grossman, Gennady Pekhimenko
Skyline: Interactive In-Editor Computational Performance Profiling for Deep Neural Network Training. UIST (2020)
Hongyu Zhu, Amar Phanishayee, Gennady Pekhimenko
Daydream: Accurately Estimating the Efficacy of Optimizations for DNN Training. USENIX Annual Technical Conference (2020)
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
MLPerf Inference Benchmark. ISCA (2020)
Hongyu Zhu, Amar Phanishayee, Gennady Pekhimenko
Daydream: Accurately Estimating the Efficacy of Optimizations for DNN Training. CoRR (2020)
Anand Jayarajan, Kimberly Hau, Andrew Goodwin, Gennady Pekhimenko
LifeStream: A High-performance Stream Processing Engine for Waveform Data. CoRR (2020)
Bojian Zheng, Nandita Vijaykumar, Gennady Pekhimenko
Echo: Compiler-based GPU Memory Footprint Reduction for LSTM RNN Training. ISCA (2020)
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
MLPerf Training Benchmark. MLSys (2020)
Omar Mohamed Awad, Mostafa Mahmoud, Isak Edo Vivancos, Ali Hadi Zadeh, Ciaran Bannon, Anand Jayarajan, Gennady Pekhimenko, Andreas Moshovos
FPRaker: A Processing Element For Accelerating Neural Network Training. CoRR (2020)
Anand Jayarajan, Jinliang Wei, Garth Gibson, Alexandra Fedorova, Gennady Pekhimenko
Priority-based Parameter Propagation for Distributed DNN Training. MLSys (2019)
Sihang Liu, Korakit Seemakhupt, Gennady Pekhimenko, Aasheesh Kolli, Samira Manabi Khan
Janus: optimizing memory and storage support for non-volatile memory systems. ISCA (2019)
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
MLPerf Training Benchmark. CoRR (2019)
Shang Wang, Yifan Bai, Gennady Pekhimenko
Scaling Back-propagation by Parallel Scan Algorithm. CoRR (2019)
Anand Jayarajan, Jinliang Wei, Garth Gibson, Alexandra Fedorova, Gennady Pekhimenko
Priority-based Parameter Propagation for Distributed DNN Training. CoRR (2019)
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
MLPerf Inference Benchmark. CoRR (2019)
Hongyu Miao, Myeongjae Jeon, Gennady Pekhimenko, Kathryn S. McKinley, Felix Xiaozhu Lin
StreamBox-HBM: Stream Analytics on High Bandwidth Hybrid Memory. CoRR (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric 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 G. 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 R. 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
SysML: The New Frontier of Machine Learning Systems. CoRR (2019)
Hongyu Miao, Myeongjae Jeon, Gennady Pekhimenko, Kathryn S. McKinley, Felix Xiaozhu Lin
StreamBox-HBM: Stream Analytics on High Bandwidth Hybrid Memory. ASPLOS (2019)
Nandita Vijaykumar, Kevin Hsieh, Gennady Pekhimenko, Samira Manabi Khan, Ashish Shrestha, Saugata Ghose, Phillip B. Gibbons, Onur Mutlu
Zorua: Enhancing Programming Ease, Portability, and Performance in GPUs by Decoupling Programming Models from Resource Management. CoRR (2018)
Nandita Vijaykumar, Abhilasha Jain, Diptesh Majumdar, Kevin Hsieh, Gennady Pekhimenko, Eiman Ebrahimi, Nastaran Hajinazar, Phillip B. Gibbons, Onur Mutlu
A Case for Richer Cross-Layer Abstractions: Bridging the Semantic Gap with Expressive Memory. ISCA (2018)
Bojian Zheng, Akshay Nair, Qiongsi Wu, Nandita Vijaykumar, Gennady Pekhimenko
EcoRNN: Fused LSTM RNN Implementation with Data Layout Optimization. CoRR (2018)
Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Anand Jayarajan, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko
Benchmarking and Analyzing Deep Neural Network Training. IISWC (2018)
Hasan Hassan, Gennady Pekhimenko, Nandita Vijaykumar, Vivek Seshadri, Donghyuk Lee, Oguz Ergin, Onur Mutlu
Exploiting Row-Level Temporal Locality in DRAM to Reduce the Memory Access Latency. CoRR (2018)
Nandita Vijaykumar, Kevin Hsieh, Gennady Pekhimenko, Samira Manabi Khan, Ashish Shrestha, Saugata Ghose, Adwait Jog, Phillip B. Gibbons, Onur Mutlu
Decoupling GPU Programming Models from Resource Management for Enhanced Programming Ease, Portability, and Performance. CoRR (2018)
Gennady Pekhimenko, Ettore Tiotto
Compiler-driven performance workshop. CASCON (2018)
Hasan Hassan, Nandita Vijaykumar, Samira Manabi Khan, Saugata Ghose, Kevin K. Chang, Gennady Pekhimenko, Donghyuk Lee, Oguz Ergin, Onur Mutlu
SoftMC: Practical DRAM Characterization Using an FPGA-Based Infrastructure. CoRR (2018)
Donghyuk Lee, Yoongu Kim, Gennady Pekhimenko, Samira Manabi Khan, Vivek Seshadri, Kevin K. Chang, Onur Mutlu
Adaptive-Latency DRAM: Reducing DRAM Latency by Exploiting Timing Margins. CoRR (2018)
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
RowClone: Accelerating Data Movement and Initialization Using DRAM. CoRR (2018)
Hongyu Zhu, Mohamed Akrout, Bojian Zheng, Andrew Pelegris, Amar Phanishayee, Bianca Schroeder, Gennady Pekhimenko
TBD: Benchmarking and Analyzing Deep Neural Network Training. CoRR (2018)
Gennady Pekhimenko, Chuanxiong Guo, Myeongjae Jeon, Peng Huang, Lidong Zhou
TerseCades: Efficient Data Compression in Stream Processing. USENIX Annual Technical Conference (2018)
Animesh Jain, Amar Phanishayee, Jason Mars, Lingjia Tang, Gennady Pekhimenko
Gist: Efficient Data Encoding for Deep Neural Network Training. ISCA (2018)
Kevin K. Chang, Abhijith Kashyap, Hasan Hassan, Saugata Ghose, Kevin Hsieh, Donghyuk Lee, Tianshi Li, Gennady Pekhimenko, Samira Manabi Khan, Onur Mutlu
Flexible-Latency DRAM: Understanding and Exploiting Latency Variation in Modern DRAM Chips. CoRR (2018)
Hasan Hassan, Nandita Vijaykumar, Samira Manabi Khan, Saugata Ghose, Kevin K. Chang, Gennady Pekhimenko, Donghyuk Lee, Oguz Ergin, Onur Mutlu
SoftMC: A Flexible and Practical Open-Source Infrastructure for Enabling Experimental DRAM Studies. HPCA (2017)
Donghyuk Lee, Samira Manabi Khan, Lavanya Subramanian, Saugata Ghose, Rachata Ausavarungnirun, Gennady Pekhimenko, Vivek Seshadri, Onur Mutlu
Design-Induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms. SIGMETRICS (Abstracts) (2017)
Donghyuk Lee, Samira Manabi Khan, Lavanya Subramanian, Saugata Ghose, Rachata Ausavarungnirun, Gennady Pekhimenko, Vivek Seshadri, Onur Mutlu
Design-Induced Latency Variation in Modern DRAM Chips: Characterization, Analysis, and Latency Reduction Mechanisms. Proc. ACM Meas. Anal. Comput. Syst. 1 (1) (2017)
Hongyu Miao, Heejin Park, Myeongjae Jeon, Gennady Pekhimenko, Kathryn S. McKinley, Felix Xiaozhu Lin
StreamBox: Modern Stream Processing on a Multicore Machine. USENIX Annual Technical Conference (2017)
Amir Yazdanbakhsh, Gennady Pekhimenko, Bradley Thwaites, Hadi Esmaeilzadeh, Onur Mutlu, Todd C. Mowry
RFVP: Rollback-Free Value Prediction with Safe-to-Approximate Loads. ACM Trans. Archit. Code Optim. 12 (4) (2016)
Hasan Hassan, Gennady Pekhimenko, Nandita Vijaykumar, Vivek Seshadri, Donghyuk Lee, Oguz Ergin, Onur Mutlu
ChargeCache: Reducing DRAM latency by exploiting row access locality. HPCA (2016)
Donghyuk Lee, Yoongu Kim, Gennady Pekhimenko, Samira Manabi Khan, Vivek Seshadri, Kevin Kai-Wei Chang, Onur Mutlu
Adaptive-Latency DRAM (AL-DRAM). CoRR (2016)
Amir Yazdanbakhsh, Bradley Thwaites, Hadi Esmaeilzadeh, Gennady Pekhimenko, Onur Mutlu, Todd C. Mowry
Mitigating the Memory Bottleneck With Approximate Load Value Prediction. IEEE Des. Test 33 (1) (2016)
Gennady Pekhimenko, Evgeny Bolotin, Nandita Vijaykumar, Onur Mutlu, Todd C. Mowry, Stephen W. Keckler
A case for toggle-aware compression for GPU systems. HPCA (2016)
Donghyuk Lee, Saugata Ghose, Gennady Pekhimenko, Samira Manabi Khan, Onur Mutlu
Simultaneous Multi-Layer Access: Improving 3D-Stacked Memory Bandwidth at Low Cost. ACM Trans. Archit. Code Optim. 12 (4) (2016)
Nandita Vijaykumar, Gennady Pekhimenko, Adwait Jog, Saugata Ghose, Abhishek Bhowmick, Rachata Ausavarungnirun, Chita R. Das, Mahmut T. Kandemir, Todd C. Mowry, Onur Mutlu
A Framework for Accelerating Bottlenecks in GPU Execution with Assist Warps. CoRR (2016)
Kevin K. Chang, Abhijith Kashyap, Hasan Hassan, Saugata Ghose, Kevin Hsieh, Donghyuk Lee, Tianshi Li, Gennady Pekhimenko, Samira Manabi Khan, Onur Mutlu
Understanding Latency Variation in Modern DRAM Chips: Experimental Characterization, Analysis, and Optimization. SIGMETRICS (2016)
Donghyuk Lee, Samira Manabi Khan, Lavanya Subramanian, Rachata Ausavarungnirun, Gennady Pekhimenko, Vivek Seshadri, Saugata Ghose, Onur Mutlu
Reducing DRAM Latency by Exploiting Design-Induced Latency Variation in Modern DRAM Chips. CoRR (2016)
Hongyi Xin, Sunny Nahar, Richard Zhu, John Emmons, Gennady Pekhimenko, Carl Kingsford, Can Alkan, Onur Mutlu
Optimal seed solver: optimizing seed selection in read mapping. Bioinform. 32 (11) (2016)

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Publication Activity (10 Years)

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Gennady Pekhimenko