Hadi Esmaeilzadeh

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 65

Top Topics

Benchmark Suite

Feature Representations

Disparity Estimation

Top Venues

Publications

Shu-Ting Wang, Hanyang Xu, Amin Mamandipoor, Rohan Mahapatra, Byung Hoon Ahn, Soroush Ghodrati, Krishnan Kailas, Mohammad Alian, Hadi Esmaeilzadeh
Data Motion Acceleration: Chaining Cross-Domain Multi Accelerators. HPCA (2024)
Rohan Mahapatra, Soroush Ghodrati, Byung Hoon Ahn, Sean Kinzer, Shu-Ting Wang, Hanyang Xu, Lavanya Karthikeyan, Hardik Sharma, Amir Yazdanbakhsh, Mohammad Alian, Hadi Esmaeilzadeh
In-Storage Domain-Specific Acceleration for Serverless Computing. ASPLOS (2) (2024)
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
Tandem Processor: Grappling with Emerging Operators in Neural Networks. ASPLOS (2) (2024)
Dong Kai Wang, Jiaqi Lou, Naiyin Jin, Edwin Mascarenhas, Rohan Mahapatra, Sean Kinzer, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Nam Sung Kim
MESA: Microarchitecture Extensions for Spatial Architecture Generation. ISCA (2023)
Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng, Sean Kinzer, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang
Performance Analysis of DNN Inference/Training with Convolution and non-Convolution Operations. CoRR (2023)
Rohan Mahapatra, Soroush Ghodrati, Byung Hoon Ahn, Sean Kinzer, Shu-Ting Wang, Hanyang Xu, Lavanya Karthikeyan, Hardik Sharma, Amir Yazdanbakhsh, Mohammad Alian, Hadi Esmaeilzadeh
Domain-Specific Computational Storage for Serverless Computing. CoRR (2023)
Sean Kinzer, Soroush Ghodrati, Rohan Mahapatra, Byung Hoon Ahn, Edwin Mascarenhas, Xiaolong Li, Janarbek Matai, Liang Zhang, Hadi Esmaeilzadeh
Restoring the Broken Covenant Between Compilers and Deep Learning Accelerators. CoRR (2023)
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
An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators. CoRR (2023)
Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang
Accelerating Attention through Gradient-Based Learned Runtime Pruning. CoRR (2022)
Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang
Accelerating attention through gradient-based learned runtime pruning. ISCA (2022)
Mohammad Loni, Ali Zoljodi, Amin Majd, Byung Hoon Ahn, Masoud Daneshtalab, Mikael Sjödin, Hadi Esmaeilzadeh
FastStereoNet: A Fast Neural Architecture Search for Improving the Inference of Disparity Estimation on Resource-Limited Platforms. IEEE Trans. Syst. Man Cybern. Syst. 52 (8) (2022)
Byung Hoon Ahn, Sean Kinzer, Hadi Esmaeilzadeh
Glimpse: mathematical embedding of hardware specification for neural compilation. DAC (2022)
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
Physically Accurate Learning-based Performance Prediction of Hardware-accelerated ML Algorithms. MLCAD (2022)
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
Yin-Yang: Programming Abstractions for Cross-Domain Multi-Acceleration. IEEE Micro 42 (5) (2022)
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
VeriGOOD-ML: An Open-Source Flow for Automated ML Hardware Synthesis. ICCAD (2021)
Hadi Esmaeilzadeh, Reza Vaezi
Conscious AI. CoRR (2021)
Sean Kinzer, Joon Kyung Kim, Soroush Ghodrati, Brahmendra Reddy Yatham, Alric Althoff, Divya Mahajan, Sorin Lerner, Hadi Esmaeilzadeh
A Computational Stack for Cross-Domain Acceleration. HPCA (2021)
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Ali Jalali, Ahmed Taha Elthakeb, Dean M. Tullsen, Hadi Esmaeilzadeh
Not All Features Are Equal: Discovering Essential Features for Preserving Prediction Privacy. WWW (2021)
Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation. CoRR (2020)
Ahmed Taha Elthakeb, Prannoy Pilligundla, Fatemeh Mireshghallah, Alexander Cloninger, Hadi Esmaeilzadeh
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. ICML (2020)
Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
ReLeQ : A Reinforcement Learning Approach for Automatic Deep Quantization of Neural Networks. IEEE Micro 40 (5) (2020)
Byung Hoon Ahn, Prannoy Pilligundla, Amir Yazdanbakhsh, Hadi Esmaeilzadeh
Chameleon: Adaptive Code Optimization for Expedited Deep Neural Network Compilation. ICLR (2020)
Ahmed T. Elthakeb, Prannoy Pilligundla, Fatemehsadat Mireshghallah, Tarek Elgindi, Charles-Alban Deledalle, Hadi Esmaeilzadeh
Gradient-Based Deep Quantization of Neural Networks through Sinusoidal Adaptive Regularization. CoRR (2020)
Byung Hoon Ahn, Jinwon Lee, Jamie Menjay Lin, Hsin-Pai Cheng, Jilei Hou, Hadi Esmaeilzadeh
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices. CoRR (2020)
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Ali Jalali, Ahmed Taha Elthakeb, Dean M. Tullsen, Hadi Esmaeilzadeh
A Principled Approach to Learning Stochastic Representations for Privacy in Deep Neural Inference. CoRR (2020)
Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh
Bit-Parallel Vector Composability for Neural Acceleration. CoRR (2020)
Byung Hoon Ahn, Jinwon Lee, Jamie Menjay Lin, Hsin-Pai Cheng, Jilei Hou, Hadi Esmaeilzadeh
Ordering Chaos: Memory-Aware Scheduling of Irregularly Wired Neural Networks for Edge Devices. MLSys (2020)
Soroush Ghodrati, Hardik Sharma, Sean Kinzer, Amir Yazdanbakhsh, Jongse Park, Nam Sung Kim, Doug Burger, Hadi Esmaeilzadeh
Mixed-Signal Charge-Domain Acceleration of Deep Neural Networks through Interleaved Bit-Partitioned Arithmetic. PACT (2020)
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Prakash Ramrakhyani, Ali Jalali, Dean M. Tullsen, Hadi Esmaeilzadeh
Shredder: Learning Noise Distributions to Protect Inference Privacy. ASPLOS (2020)
Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh
Bit-Parallel Vector Composability for Neural Acceleration. DAC (2020)
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, Hadi Esmaeilzadeh
Privacy in Deep Learning: A Survey. CoRR (2020)
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
Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks. MICRO (2020)
Byung Hoon Ahn, Prannoy Pilligundla, Hadi Esmaeilzadeh
Reinforcement Learning and Adaptive Sampling for Optimized DNN Compilation. CoRR (2019)
Fatemehsadat Mireshghallah, Mohammadkazem Taram, Prakash Ramrakhyani, Dean M. Tullsen, Hadi Esmaeilzadeh
Shredder: Learning Noise to Protect Privacy with Partial DNN Inference on the Edge. CoRR (2019)
Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh
SinReQ: Generalized Sinusoidal Regularization for Automatic Low-Bitwidth Deep Quantized Training. CoRR (2019)
Soroush Ghodrati, Hardik Sharma, Sean Kinzer, Amir Yazdanbakhsh, Kambiz Samadi, Nam Sung Kim, Doug Burger, Hadi Esmaeilzadeh
Mixed-Signal Charge-Domain Acceleration of Deep Neural networks through Interleaved Bit-Partitioned Arithmetic. CoRR (2019)
Hadi Esmaeilzadeh, Jongse Park
Machine Learning Acceleration. IEEE Micro 39 (5) (2019)
Zhenhong Liu, Amir Yazdanbakhsh, Dong Kai Wang, Hadi Esmaeilzadeh, Nam Sung Kim
AxMemo: hardware-compiler co-design for approximate code memoization. ISCA (2019)
Ahmed T. Elthakeb, Prannoy Pilligundla, Hadi Esmaeilzadeh
Divide and Conquer: Leveraging Intermediate Feature Representations for Quantized Training of Neural Networks. CoRR (2019)
Jacob Sacks, Divya Mahajan, Richard Connor Lawson, Hadi Esmaeilzadeh
RoboX: An End-to-End Solution to Accelerate Autonomous Control in Robotics. ISCA (2018)
Amir Yazdanbakhsh, Hajar Falahati, Philip J. Wolfe, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks. CoRR (2018)
Divya Mahajan, Joon Kyung Kim, Jacob Sacks, Adel Ardalan, Arun Kumar, Hadi Esmaeilzadeh
In-RDBMS Hardware Acceleration of Advanced Analytics. Proc. VLDB Endow. 11 (11) (2018)
Divya Mahajan, Joon Kyung Kim, Jacob Sacks, Adel Ardalan, Arun Kumar, Hadi Esmaeilzadeh
In-RDBMS Hardware Acceleration of Advanced Analytics. CoRR (2018)
Youjie Li, Jongse Park, Mohammad Alian, Yifan Yuan, Zheng Qu, Peitian Pan, Ren Wang, Alexander G. Schwing, Hadi Esmaeilzadeh, Nam Sung Kim
A Network-Centric Hardware/Algorithm Co-Design to Accelerate Distributed Training of Deep Neural Networks. MICRO (2018)
Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Vikas Chandra, Hadi Esmaeilzadeh
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Network. ISCA (2018)
Amir Yazdanbakhsh, Choungki Song, Jacob Sacks, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh, Nam Sung Kim
In-DRAM near-data approximate acceleration for GPUs. PACT (2018)
Ahmed T. Elthakeb, Prannoy Pilligundla, Amir Yazdanbakhsh, Sean Kinzer, Hadi Esmaeilzadeh
ReLeQ: A Reinforcement Learning Approach for Deep Quantization of Neural Networks. CoRR (2018)
Amir Yazdanbakhsh, Michael Brzozowski, Behnam Khaleghi, Soroush Ghodrati, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
FlexiGAN: An End-to-End Solution for FPGA Acceleration of Generative Adversarial Networks. FCCM (2018)
Vahideh Akhlaghi, Amir Yazdanbakhsh, Kambiz Samadi, Rajesh K. Gupta, Hadi Esmaeilzadeh
SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks. ISCA (2018)
Amir Yazdanbakhsh, Kambiz Samadi, Nam Sung Kim, Hadi Esmaeilzadeh
GANAX: A Unified MIMD-SIMD Acceleration for Generative Adversarial Networks. ISCA (2018)
Zhenhong Liu, Amir Yazdanbakhsh, Taejoon Park, Hadi Esmaeilzadeh, Nam Sung Kim
SiMul: An Algorithm-Driven Approximate Multiplier Design for Machine Learning. IEEE Micro 38 (4) (2018)
Jongse Park, Hardik Sharma, Divya Mahajan, Joon Kyung Kim, Preston Olds, Hadi Esmaeilzadeh
Scale-out acceleration for machine learning. MICRO (2017)
Hyoukjun Kwon, William Harris, Hadi Esmaeilzadeh
Proving Flow Security of Sequential Logic via Automatically-Synthesized Relational Invariants. CSF (2017)
Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Joon Kyung Kim, Vikas Chandra, Hadi Esmaeilzadeh
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks. CoRR (2017)
Amir Yazdanbakhsh, Divya Mahajan, Hadi Esmaeilzadeh, Pejman Lotfi-Kamran
AxBench: A Multiplatform Benchmark Suite for Approximate Computing. IEEE Des. Test 34 (2) (2017)
Hardik Sharma, Jongse Park, Divya Mahajan, Emmanuel Amaro, Joon Kyung Kim, Chenkai Shao, Asit Mishra, Hadi Esmaeilzadeh
From high-level deep neural models to FPGAs. MICRO (2016)
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)
Jongse Park, Emmanuel Amaro, Divya Mahajan, Bradley Thwaites, Hadi Esmaeilzadeh
AxGames: Towards Crowdsourcing Quality Target Determination in Approximate Computing. ASPLOS (2016)
Divya Mahajan, Jongse Park, Emmanuel Amaro, Hardik Sharma, Amir Yazdanbakhsh, Joon Kyung Kim, Hadi Esmaeilzadeh
TABLA: A unified template-based framework for accelerating statistical machine learning. HPCA (2016)
Atieh Lotfi, Abbas Rahimi, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Rajesh K. Gupta
Grater: An approximation workflow for exploiting data-level parallelism in FPGA acceleration. DATE (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)
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
A reconfigurable fabric for accelerating large-scale datacenter services. Commun. ACM 59 (11) (2016)
William Wahby, Thomas E. Sarvey, Hardik Sharma, Hadi Esmaeilzadeh, Muhannad S. Bakir
The impact of 3D stacking on GPU-accelerated deep neural networks: An experimental study. 3DIC (2016)
Hang Zhang, Afshin Abdi, Faramarz Fekri, Hadi Esmaeilzadeh
Error correction for approximate computing. Allerton (2016)
Divya Mahajan, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh
Towards Statistical Guarantees in Controlling Quality Tradeoffs for Approximate Acceleration. ISCA (2016)
Jongse Park, Hadi Esmaeilzadeh, Xin Zhang, Mayur Naik, William Harris
FlexJava: language support for safe and modular approximate programming. ESEC/SIGSOFT FSE (2015)
Thierry Moreau, Mark Wyse, Jacob Nelson, Adrian Sampson, Hadi Esmaeilzadeh, Luis Ceze, Mark Oskin
SNNAP: Approximate computing on programmable SoCs via neural acceleration. HPCA (2015)
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
A Reconfigurable Fabric for Accelerating Large-Scale Datacenter Services. IEEE Micro 35 (3) (2015)
Amir Yazdanbakhsh, Divya Mahajan, Bradley Thwaites, Jongse Park, Anandhavel Nagendrakumar, Sindhuja Sethuraman, Kartik Ramkrishnan, Nishanthi Ravindran, Rudra Jariwala, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan
Axilog: language support for approximate hardware design. DATE (2015)
Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug Burger
Neural acceleration for general-purpose approximate programs. Commun. ACM 58 (1) (2015)
Divya Mahajan, Kartik Ramkrishnan, Rudra Jariwala, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Anandhavel Nagendrakumar, Abbas Rahimi, Hadi Esmaeilzadeh, Kia Bazargan
Axilog: Abstractions for Approximate Hardware Design and Reuse. IEEE Micro 35 (5) (2015)
Amir Yazdanbakhsh, Jongse Park, Hardik Sharma, Pejman Lotfi-Kamran, Hadi Esmaeilzadeh
Neural acceleration for GPU throughput processors. MICRO (2015)
Hadi Esmaeilzadeh
Approximate acceleration: A path through the era of dark silicon and big data. CASES (2015)
Renée St. Amant, Amir Yazdanbakhsh, Jongse Park, Bradley Thwaites, Hadi Esmaeilzadeh, Arjang Hassibi, Luis Ceze, Doug Burger
General-purpose code acceleration with limited-precision analog computation. ISCA (2014)
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
A reconfigurable fabric for accelerating large-scale datacenter services. ISCA (2014)
Bradley Thwaites, Gennady Pekhimenko, Hadi Esmaeilzadeh, Amir Yazdanbakhsh, Onur Mutlu, Jongse Park, Girish Mururu, Todd C. Mowry
Rollback-free value prediction with approximate loads. PACT (2014)
Emily R. Blem, Hadi Esmaeilzadeh, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
Multicore Model from Abstract Single Core Inputs. IEEE Comput. Archit. Lett. 12 (2) (2013)
Behnam Robatmili, Dong Li, Hadi Esmaeilzadeh, Madhu Saravana Sibi Govindan, Aaron Smith, Andrew Putnam, Doug Burger, Stephen W. Keckler
How to implement effective prediction and forwarding for fusable dynamic multicore architectures. HPCA (2013)
Hadi Esmaeilzadeh, Emily R. Blem, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
Power challenges may end the multicore era. Commun. ACM 56 (2) (2013)
Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug Burger
Neural Acceleration for General-Purpose Approximate Programs. IEEE Micro 33 (3) (2013)
Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug Burger
Neural Acceleration for General-Purpose Approximate Programs. MICRO (2012)
Hadi Esmaeilzadeh, Emily R. Blem, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
Dark Silicon and the End of Multicore Scaling. IEEE Micro 32 (3) (2012)
Hadi Esmaeilzadeh, Emily R. Blem, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
Power Limitations and Dark Silicon Challenge the Future of Multicore. ACM Trans. Comput. Syst. 30 (3) (2012)
Hadi Esmaeilzadeh, Adrian Sampson, Luis Ceze, Doug Burger
Architecture support for disciplined approximate programming. ASPLOS (2012)
Hadi Esmaeilzadeh, Ting Cao, Xi Yang, Stephen M. Blackburn, Kathryn S. McKinley
Looking back and looking forward: power, performance, and upheaval. Commun. ACM 55 (7) (2012)
Hadi Esmaeilzadeh, Ting Cao, Xi Yang, Stephen Blackburn, Kathryn S. McKinley
What is Happening to Power, Performance, and Software? IEEE Micro 32 (3) (2012)
Hadi Esmaeilzadeh, Emily R. Blem, Renée St. Amant, Karthikeyan Sankaralingam, Doug Burger
Dark silicon and the end of multicore scaling. ISCA (2011)
Hadi Esmaeilzadeh, Ting Cao, Xi Yang, Stephen M. Blackburn, Kathryn S. McKinley
Looking back on the language and hardware revolutions: measured power, performance, and scaling. ASPLOS (2011)
Saeed Safari, Amir-Hossein Jahangir, Hadi Esmaeilzadeh
A parameterized graph-based framework for high-level test synthesis. Integr. 39 (4) (2006)
Hadi Esmaeilzadeh, A. Moghimi, Eiman Ebrahimi, Caro Lucas, Zainalabedin Navabi, A. M. Fakhraie
DCim++: a C++ library for object oriented hardware design and distributed simulation. ISCAS (2006)
Hadi Esmaeilzadeh, Pooya Saeedi, Babak Nadjar Araabi, Caro Lucas, Seid Mehdi Fakhraie
Neural network stream processing core (NnSP) for embedded systems. ISCAS (2006)
Saeed Shamshiri, Hadi Esmaeilzadeh, Zainalabedin Navabi
Instruction-level test methodology for CPU core self-testing. ACM Trans. Design Autom. Electr. Syst. 10 (4) (2005)
Hadi Esmaeilzadeh, Saeed Shamshiri, Pooya Saeedi, Zainalabedin Navabi
ISC: Reconfigurable Scan-Cell Architecture for Low Power Testing. Asian Test Symposium (2005)
Saeed Shamshiri, Hadi Esmaeilzadeh, Zainalabedin Navabi
Test Instruction Set (TIS) for High Level Self-Testing of CPU Cores. Asian Test Symposium (2004)
Neda Shahidi, Hadi Esmaeilzadeh, Marziye Abdollahi, Caro Lucas
Memetic Algorithm Based Path Planning for a Mobile Robot. International Conference on Computational Intelligence (2004)
Saeed Shamshiri, Hadi Esmaeilzadeh, Zainalabedin Navabi
Instruction level test methodology for CPU core software-based self-testing. HLDVT (2004)
Saeed Safari, Hadi Esmaeilzadeh, Amir-Hossein Jahangir
A novel improvement technique for high-level test synthesis. ISCAS (5) (2003)
Saeed Safari, Hadi Esmaeilzadeh, Amir-Hossein Jahangir
Testability Improvement During High-Level Synthesis. Asian Test Symposium (2003)