Hadi Esmaeilzadeh

105 papers A* 32A 4B 3C 2Misc 2Journal 47Unranked 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	COLT: Lightweight Multi-LLM Collaboration through Shared MCTS Reasoning for Model Compilation. CoRR Annabelle Sujun Tang, Christopher Priebe, Lianhui Qin, Hadi Esmaeilzadeh
2025	J	`jnl`	Compiler Optimization via LLM Reasoning for Efficient Model Serving. CoRR Annabelle Sujun Tang, Christopher Priebe, Rohan Mahapatra, Lianhui Qin, Hadi Esmaeilzadeh
2025	A*	`conf`	In-Storage Acceleration of Retrieval Augmented Generation as a Service. ISCA Rohan Mahapatra, Harsha Santhanam, Christopher Priebe, Hanyang Xu, Hadi Esmaeilzadeh
2025	J	`jnl`	Performance Analysis of CNN Inference/Training with Convolution and Non-Convolution Operations on ASIC Accelerators. ACM Trans. Design Autom. Electr. Syst. Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Sean Kinzer, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang
2024	J	`jnl`	An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators. ACM Trans. Design Autom. Electr. Syst. Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Joon Kyung Kim, Sean Kinzer, Sayak Kundu, Rohan Mahapatra, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang, Ziqing Zeng
2024	A*	`conf`	Data Motion Acceleration: Chaining Cross-Domain Multi Accelerators. HPCA Shu-Ting Wang, Hanyang Xu, Amin Mamandipoor, Rohan Mahapatra, Byung Hoon Ahn, Soroush Ghodrati, Krishnan Kailas, Mohammad Alian, Hadi Esmaeilzadeh
2024	—	`conf`	In-Storage Domain-Specific Acceleration for Serverless Computing. ASPLOS (2) Rohan Mahapatra, Soroush Ghodrati, Byung Hoon Ahn, Sean Kinzer, Shu-Ting Wang, Hanyang Xu, Lavanya Karthikeyan, Hardik Sharma, Amir Yazdanbakhsh, Mohammad Alian, Hadi Esmaeilzadeh
2024	—	`conf`	Tandem Processor: Grappling with Emerging Operators in Neural Networks. ASPLOS (2) Soroush Ghodrati, Sean Kinzer, Hanyang Xu, Rohan Mahapatra, Yoonsung Kim, Byung Hoon Ahn, Dong Kai Wang, Lavanya Karthikeyan, Amir Yazdanbakhsh, Jongse Park, Nam Sung Kim, Hadi Esmaeilzadeh
2023	J	`jnl`	An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators. CoRR Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Joon Kyung Kim, Sean Kinzer, Sayak Kundu, Rohan Mahapatra, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang, Ziqing Zeng
2023	J	`jnl`	Domain-Specific Computational Storage for Serverless Computing. CoRR Rohan Mahapatra, Soroush Ghodrati, Byung Hoon Ahn, Sean Kinzer, Shu-Ting Wang, Hanyang Xu, Lavanya Karthikeyan, Hardik Sharma, Amir Yazdanbakhsh, Mohammad Alian, Hadi Esmaeilzadeh
2023	A*	`conf`	MESA: Microarchitecture Extensions for Spatial Architecture Generation. ISCA Dong Kai Wang, Jiaqi Lou, Naiyin Jin, Edwin Mascarenhas, Rohan Mahapatra, Sean Kinzer, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Nam Sung Kim
2023	J	`jnl`	Performance Analysis of DNN Inference/Training with Convolution and non-Convolution Operations. CoRR Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Sean Kinzer, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang
2023	J	`jnl`	Restoring the Broken Covenant Between Compilers and Deep Learning Accelerators. CoRR Sean Kinzer, Soroush Ghodrati, Rohan Mahapatra, Byung Hoon Ahn, Edwin Mascarenhas, Xiaolong Li, Janarbek Matai, Liang Zhang, Hadi Esmaeilzadeh
2022	J	`jnl`	Accelerating Attention through Gradient-Based Learned Runtime Pruning. CoRR Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang
2022	A*	`conf`	Accelerating attention through gradient-based learned runtime pruning. ISCA Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang
2022	J	`jnl`	FastStereoNet: A Fast Neural Architecture Search for Improving the Inference of Disparity Estimation on Resource-Limited Platforms. IEEE Trans. Syst. Man Cybern. Syst. Mohammad Loni, Ali Zoljodi, Amin Majd, Byung Hoon Ahn, Masoud Daneshtalab, Mikael Sjödin, Hadi Esmaeilzadeh
2022	A*	`conf`	Glimpse: mathematical embedding of hardware specification for neural compilation. DAC Byung Hoon Ahn, Sean Kinzer, Hadi Esmaeilzadeh
2022	—	`conf`	Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms. MLCAD Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Joon Kyung Kim, Sean Kinzer, Sayak Kundu, Rohan Mahapatra, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang, Ziqing Zeng
2022	J	`jnl`	Yin-Yang: Programming Abstractions for Cross-Domain Multi-Acceleration. IEEE Micro Joon Kyung Kim, Byung Hoon Ahn, Sean Kinzer, Soroush Ghodrati, Rohan Mahapatra, Brahmendra Reddy Yatham, Shu-Ting Wang, Dohee Kim, Parisa Sarikhani, Babak Mahmoudi, Divya Mahajan, Jongse Park, Hadi Esmaeilzadeh
2021	A*	`conf`	A Computational Stack for Cross-Domain Acceleration. HPCA Sean Kinzer, Joon Kyung Kim, Soroush Ghodrati, Brahmendra Reddy Yatham, Alric Althoff, Divya Mahajan, Sorin Lerner, Hadi Esmaeilzadeh
2021	J	`jnl`	Conscious AI. CoRR Hadi Esmaeilzadeh, Reza Vaezi
2021	A*	`conf`	Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy. WWW Fatemehsadat Mireshghallah, Mohammadkazem Taram, Ali Jalali, Ahmed Taha Elthakeb, Dean M. Tullsen, Hadi Esmaeilzadeh
2021	A	`conf`	VeriGOOD-ML: An Open-Source Flow for Automated ML Hardware Synthesis. ICCAD Hadi Esmaeilzadeh, Soroush Ghodrati, Jie Gu, Shiyu Guo, Andrew B. Kahng, Joon Kyung Kim, Sean Kinzer, Rohan Mahapatra, Susmita Dey Manasi, Edwin Mascarenhas, Sachin S. Sapatnekar, Ravi Varadarajan, Zhiang Wang, Hanyang Xu, Brahmendra Reddy Yatham, Ziqing Zeng
2020	J	`jnl`	A Principled Approach to Learning Stochastic Representations for Privacy in Deep Neural Inference. CoRR Fatemehsadat Mireshghallah, Mohammadkazem Taram, Ali Jalali, Ahmed Taha Elthakeb, Dean M. Tullsen, Hadi Esmaeilzadeh
2020	A*	`conf`	Bit-Parallel Vector Composability for Neural Acceleration. DAC Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh
2020	J	`jnl`	Bit-Parallel Vector Composability for Neural Acceleration. CoRR Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh
2020	A*	`conf`	Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation. ICLR Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
2020	J	`jnl`	Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation. CoRR Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
2020	A*	`conf`	Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. ICML Ahmed Taha Elthakeb, Prannoy Pilligundla, Fatemeh Mireshghallah, Alexander Cloninger, Hadi Esmaeilzadeh
2020	J	`jnl`	Gradient-Based Deep Quantization of Neural Networks through Sinusoidal Adaptive Regularization. CoRR Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Tarek Elgindi, Charles-Alban Deledalle, Hadi Esmaeilzadeh
2020	B	`conf`	Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic. PACT Soroush Ghodrati, Hardik Sharma, Sean Kinzer, Amir Yazdanbakhsh, Jongse Park, Nam Sung Kim, Doug Burger, Hadi Esmaeilzadeh
2020	—	`conf`	Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices. MLSys Byung Hoon Ahn, Jinwon Lee, Jamie Menjay Lin, Hsin-Pai Cheng, Jilei Hou, Hadi Esmaeilzadeh
2020	J	`jnl`	Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices. CoRR Byung Hoon Ahn, Jinwon Lee, Jamie Menjay Lin, Hsin-Pai Cheng, Jilei Hou, Hadi Esmaeilzadeh
2020	A*	`conf`	Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks. MICRO Soroush Ghodrati, Byung Hoon Ahn, Joon Kyung Kim, Sean Kinzer, Brahmendra Reddy Yatham, Navateja Alla, Hardik Sharma, Mohammad Alian, Eiman Ebrahimi, Nam Sung Kim, Cliff Young, Hadi Esmaeilzadeh
2020	J	`jnl`	Privacy in Deep Learning: A Survey. CoRR Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, Hadi Esmaeilzadeh
2020	J	`jnl`	ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks. IEEE Micro Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
2020	A*	`conf`	Shredder: Learning Noise Distributions to Protect Inference Privacy. ASPLOS Fatemehsadat Mireshghallah, Mohammadkazem Taram, Prakash Ramrakhyani, Ali Jalali, Dean M. Tullsen, Hadi Esmaeilzadeh
2019	A*	`conf`	AxMemo: hardware-compiler co-design for approximate code memoization. ISCA Zhenhong Liu, Amir Yazdanbakhsh, Dong Kai Wang, Hadi Esmaeilzadeh, Nam Sung Kim
2019	J	`jnl`	Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. CoRR Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh
2019	J	`jnl`	Machine Learning Acceleration. IEEE Micro Hadi Esmaeilzadeh, Jongse Park
2019	J	`jnl`	Mixed-Signal Charge-Domain Acceleration of Deep Neural networks through Interleaved Bit-Partitioned Arithmetic. CoRR Soroush Ghodrati, Hardik Sharma, Sean Kinzer, Amir Yazdanbakhsh, Kambiz Samadi, Nam Sung Kim, Doug Burger, Hadi Esmaeilzadeh
2019	J	`jnl`	Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation. CoRR Byung Hoon Ahn, Prannoy Pilligundla, Hadi Esmaeilzadeh
2019	J	`jnl`	Shredder: Learning Noise to Protect Privacy with Partial DNN Inference on the Edge. CoRR Fatemehsadat Mireshghallah, Mohammadkazem Taram, Prakash Ramrakhyani, Dean M. Tullsen, Hadi Esmaeilzadeh
2019	J	`jnl`	SinReQ: Generalized Sinusoidal Regularization for Automatic Low-Bitwidth Deep Quantized Training. CoRR Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh
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 Network-Centric Hardware/Algorithm Co-Design to Accelerate Distributed Training of Deep Neural Networks. MICRO Youjie Li, Jongse Park, Mohammad Alian, Yifan Yuan, Zheng Qu, Peitian Pan, Ren Wang, Alexander G. Schwing, Hadi Esmaeilzadeh, Nam Sung Kim
2018	A*	`conf`	Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network. ISCA Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Vikas Chandra, Hadi Esmaeilzadeh
2018	Misc	`conf`	FlexiGAN: An End-to-End Solution for FPGA Acceleration of Generative Adversarial Networks. FCCM Amir Yazdanbakhsh, Michael Brzozowski, Behnam Khaleghi, Soroush Ghodrati, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
2018	A*	`conf`	GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks. ISCA Amir Yazdanbakhsh, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
2018	J	`jnl`	GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks. CoRR Amir Yazdanbakhsh, Hajar Falahati, Philip J. Wolfe, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
2018	B	`conf`	In-DRAM near-data approximate acceleration for GPUs. PACT Amir Yazdanbakhsh, Choungki Song, Jacob Sacks, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh, Nam Sung Kim
2018	J	`jnl`	In-RDBMS Hardware Acceleration of Advanced Analytics. CoRR Divya Mahajan, Joon Kyung Kim, Jacob Sacks, Adel Ardalan, Arun Kumar, Hadi Esmaeilzadeh
2018	J	`jnl`	In-RDBMS Hardware Acceleration of Advanced Analytics. Proc. VLDB Endow. Divya Mahajan, Joon Kyung Kim, Jacob Sacks, Adel Ardalan, Arun Kumar, Hadi Esmaeilzadeh
2018	J	`jnl`	ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks. CoRR Ahmed T. Elthakeb, Prannoy Pilligundla, Amir Yazdanbakhsh, Sean Kinzer, Hadi Esmaeilzadeh
2018	A*	`conf`	RoboX: An End-to-End Solution to Accelerate Autonomous Control in Robotics. ISCA Jacob Sacks, Divya Mahajan, Richard Connor Lawson, Hadi Esmaeilzadeh
2018	J	`jnl`	SiMul: An Algorithm-Driven Approximate Multiplier Design for Machine Learning. IEEE Micro Zhenhong Liu, Amir Yazdanbakhsh, Taejoon Park, Hadi Esmaeilzadeh, Nam Sung Kim
2018	A*	`conf`	SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks. ISCA Vahideh Akhlaghi, Amir Yazdanbakhsh, Kambiz Samadi, Rajesh K. Gupta, Hadi Esmaeilzadeh
2017	J	`jnl`	AxBench: A Multiplatform Benchmark Suite for Approximate Computing. IEEE Des. Test Amir Yazdanbakhsh, Divya Mahajan, Hadi Esmaeilzadeh, Pejman Lotfi-Kamran
2017	J	`jnl`	Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks. CoRR Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Joon Kyung Kim, Vikas Chandra, Hadi Esmaeilzadeh
2017	A	`conf`	Proving Flow Security of Sequential Logic via Automatically-Synthesized Relational Invariants. CSF Hyoukjun Kwon, William Harris, Hadi Esmaeilzadeh
2017	A*	`conf`	Scale-out acceleration for machine learning. MICRO Jongse Park, Hardik Sharma, Divya Mahajan, Joon Kyung Kim, Preston Olds, Hadi Esmaeilzadeh
2016	J	`jnl`	A reconfigurable fabric for accelerating large-scale datacenter services. Commun. ACM Andrew Putnam, Adrian M. Caulfield, Eric S. Chung, Derek Chiou, Kypros Constantinides, John Demme, Hadi Esmaeilzadeh, Jeremy Fowers, Gopi Prashanth Gopal, Jan Gray, Michael Haselman, Scott Hauck, Stephen Heil, Amir Hormati, Joo-Young Kim, Sitaram Lanka, James R. Larus, Eric Peterson, Simon Pope, Aaron Smith, Jason Thong, Phillip Yi Xiao, Doug Burger
2016	A*	`conf`	AxGames: Towards Crowdsourcing Quality Target Determination in Approximate Computing. ASPLOS Jongse Park, Emmanuel Amaro, Divya Mahajan, Bradley Thwaites, Hadi Esmaeilzadeh
2016	—	`conf`	Error correction for approximate computing. Allerton Hang Zhang, Afshin Abdi, Faramarz Fekri, Hadi Esmaeilzadeh
2016	A*	`conf`	From high-level deep neural models to FPGAs. MICRO Hardik Sharma, Jongse Park, Divya Mahajan, Emmanuel Amaro, Joon Kyung Kim, Chenkai Shao, Asit Mishra, Hadi Esmaeilzadeh
2016	A	`conf`	Grater: An approximation workflow for exploiting data-level parallelism in FPGA acceleration. DATE Atieh Lotfi, Abbas Rahimi, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Rajesh K. Gupta
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`	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	A*	`conf`	TABLA: A unified template-based framework for accelerating statistical machine learning. HPCA Divya Mahajan, Jongse Park, Emmanuel Amaro, Hardik Sharma, Amir Yazdanbakhsh, Joon Kyung Kim, Hadi Esmaeilzadeh
2016	—	`conf`	The impact of 3D stacking on GPU-accelerated deep neural networks: An experimental study. 3DIC William Wahby, Thomas E. Sarvey, Hardik Sharma, Hadi Esmaeilzadeh, Muhannad S. Bakir
2016	A*	`conf`	Towards Statistical Guarantees in Controlling Quality Tradeoffs for Approximate Acceleration. ISCA Divya Mahajan, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh
2015	J	`jnl`	A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services. IEEE Micro Andrew Putnam, Adrian M. Caulfield, Eric S. Chung, Derek Chiou, Kypros Constantinides, John Demme, Hadi Esmaeilzadeh, Jeremy Fowers, Gopi Prashanth Gopal, Jan Gray, Michael Haselman, Scott Hauck, Stephen Heil, Amir Hormati, Joo-Young Kim, Sitaram Lanka, James R. Larus, Eric Peterson, Simon Pope, Aaron Smith, Jason Thong, Phillip Yi Xiao, Doug Burger
2015	Misc	`conf`	Approximate acceleration: A path through the era of dark silicon and big data. CASES Hadi Esmaeilzadeh
2015	J	`jnl`	Axilog: Abstractions for Approximate Hardware Design and Reuse. IEEE Micro Divya Mahajan, Kartik Ramkrishnan, Rudra Jariwala, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Anandhavel Nagendrakumar, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan
2015	A	`conf`	Axilog: language support for approximate hardware design. DATE Amir Yazdanbakhsh, Divya Mahajan, Bradley Thwaites, Jongse Park, Anandhavel Nagendrakumar, Sindhuja Sethuraman, Kartik Ramkrishnan, Nishanthi Ravindran, Rudra Jariwala, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan
2015	—	`conf`	FlexJava: language support for safe and modular approximate programming. ESEC/SIGSOFT FSE Jongse Park, Hadi Esmaeilzadeh, Xin Zhang, Mayur Naik, William Harris
2015	A*	`conf`	Neural acceleration for GPU throughput processors. MICRO Amir Yazdanbakhsh, Jongse Park, Hardik Sharma, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh
2015	J	`jnl`	Neural acceleration for general-purpose approximate programs. Commun. ACM Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug Burger
2015	A*	`conf`	SNNAP: Approximate computing on programmable SoCs via neural acceleration. HPCA Thierry Moreau, Mark Wyse, Jacob Nelson, Adrian Sampson, Hadi Esmaeilzadeh, Luis Ceze, Mark Oskin
2014	A*	`conf`	A reconfigurable fabric for accelerating large-scale datacenter services. ISCA Andrew Putnam, Adrian M. Caulfield, Eric S. Chung, Derek Chiou, Kypros Constantinides, John Demme, Hadi Esmaeilzadeh, Jeremy Fowers, Gopi Prashanth Gopal, Jan Gray, Michael Haselman, Scott Hauck, Stephen Heil, Amir Hormati, Joo-Young Kim, Sitaram Lanka, James R. Larus, Eric Peterson, Simon Pope, Aaron Smith, Jason Thong, Phillip Yi Xiao, Doug Burger
2014	A*	`conf`	General-purpose code acceleration with limited-precision analog computation. ISCA Renée St. Amant, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh, Arjang Hassibi, Luis Ceze, Doug Burger
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	—	`—`	Approximate Acceleration for a Post Multicore Era. Hadi Esmaeilzadeh
2013	A*	`conf`	How to implement effective prediction and forwarding for fusable dynamic multicore architectures. HPCA Behnam Robatmili, Dong Li, Hadi Esmaeilzadeh, Madhu Saravana Sibi Govindan, Aaron Smith, Andrew Putnam, Doug Burger, Stephen W. Keckler
2013	J	`jnl`	Multicore Model from Abstract Single Core Inputs. IEEE Comput. Archit. Lett. Emily R. Blem, Hadi Esmaeilzadeh, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
2013	J	`jnl`	Neural Acceleration for General-Purpose Approximate Programs. IEEE Micro Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug Burger
2013	J	`jnl`	Power challenges may end the multicore era. Commun. ACM Hadi Esmaeilzadeh, Emily R. Blem, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
2012	A*	`conf`	Architecture support for disciplined approximate programming. ASPLOS Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug Burger
2012	J	`jnl`	Dark Silicon and the End of Multicore Scaling. IEEE Micro Hadi Esmaeilzadeh, Emily R. Blem, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
2012	J	`jnl`	Looking back and looking forward: power, performance, and upheaval. Commun. ACM Hadi Esmaeilzadeh, Ting Cao, Xi Yang, Stephen M. Blackburn, Kathryn S. McKinley
2012	A*	`conf`	Neural Acceleration for General-Purpose Approximate Programs. MICRO Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug Burger
2012	J	`jnl`	Power Limitations and Dark Silicon Challenge the Future of Multicore. ACM Trans. Comput. Syst. Hadi Esmaeilzadeh, Emily R. Blem, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
2012	J	`jnl`	What is Happening to Power, Performance, and Software? IEEE Micro Hadi Esmaeilzadeh, Ting Cao, Xi Yang, Stephen M. Blackburn, Kathryn S. McKinley
2011	A*	`conf`	Dark silicon and the end of multicore scaling. ISCA Hadi Esmaeilzadeh, Emily R. Blem, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
2011	A*	`conf`	Looking back on the language and hardware revolutions: measured power, performance, and scaling. ASPLOS Hadi Esmaeilzadeh, Ting Cao, Xi Yang, Stephen M. Blackburn, Kathryn S. McKinley
2006	J	`jnl`	A parameterized graph-based framework for high-level test synthesis. Integr. Saeed Safari, Amir-Hossein Jahangir, Hadi Esmaeilzadeh
2006	C	`conf`	DCim++: a C++ library for object oriented hardware design and distributed simulation. ISCAS Hadi Esmaeilzadeh, A. Moghimi, Eiman Ebrahimi, Caro Lucas, Zainalabedin Navabi, A. M. Fakhraie
2006	C	`conf`	Neural network stream processing core (NnSP) for embedded systems. ISCAS Hadi Esmaeilzadeh, Pooya Saeedi, Babak Nadjar Araabi, Caro Lucas, Seid Mehdi Fakhraie
2005	—	`conf`	ISC: Reconfigurable Scan-Cell Architecture for Low Power Testing. Asian Test Symposium Hadi Esmaeilzadeh, Saeed Shamshiri, Pooya Saeedi, Zainalabedin Navabi
2005	J	`jnl`	Instruction-level test methodology for CPU core self-testing. ACM Trans. Design Autom. Electr. Syst. Saeed Shamshiri, Hadi Esmaeilzadeh, Zainalabedin Navabi
2004	—	`conf`	Instruction level test methodology for CPU core software-based self-testing. HLDVT Saeed Shamshiri, Hadi Esmaeilzadeh, Zainalabedin Navabi
2004	—	`conf`	Memetic Algorithm Based Path Planning for a Mobile Robot. International Conference on Computational Intelligence Neda Shahidi, Hadi Esmaeilzadeh, Marziye Abdollahi, Caro Lucas
2004	—	`conf`	Test Instruction Set (TIS) for High Level Self-Testing of CPU Cores. Asian Test Symposium Saeed Shamshiri, Hadi Esmaeilzadeh, Zainalabedin Navabi
2003	—	`conf`	A novel improvement technique for high-level test synthesis. ISCAS (5) Saeed Safari, Hadi Esmaeilzadeh, Amir-Hossein Jahangir
2003	—	`conf`	Testability Improvement During High-Level Synthesis. Asian Test Symposium Saeed Safari, Hadi Esmaeilzadeh, Amir-Hossein Jahangir