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ORCIDSoroush Ghodrati
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2020 – today
- 2025
[j3]Hadi Esmaeilzadeh
, Soroush Ghodrati, Andrew B. Kahng, Sean Kinzer, Susmita Dey Manasi, Sachin S. Sapatnekar, Zhiang Wang:
Performance Analysis of CNN Inference/Training with Convolution and Non-Convolution Operations on ASIC Accelerators. ACM Trans. Design Autom. Electr. Syst. 30(1): 1-34 (2025)- 2024
- [j2]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. ACM Trans. Design Autom. Electr. Syst. 29(4): 1-33 (2024) - [c13]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: 530-548 - [c12]Phitchaya Mangpo Phothilimthana, Saurabh Kadekodi, Soroush Ghodrati, Selene Moon, Martin Maas:
Thesios: Synthesizing Accurate Counterfactual I/O Traces from I/O Samples. ASPLOS (3) 2024: 1016-1032 - [c11]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: 1165-1182 - [c10]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: 1043-1062 - 2023
- [b1]Soroush Ghodrati:
Architecting Machines for Green Intelligence. University of California, San Diego, USA, 2023 - [c9]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: 49:1-49:14 - [i7]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 abs/2303.03483 (2023) - [i6]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 abs/2306.16767 (2023) - [i5]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 abs/2308.12120 (2023) - [i4]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 abs/2310.17912 (2023) - 2022
- [j1]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): 89-98 (2022) - [c8]Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang:
Accelerating attention through gradient-based learned runtime pruning. ISCA 2022: 902-915 - [c7]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: 119-126 - [i3]Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh, Hadi Esmaeilzadeh, Mingu Kang:
Accelerating Attention through Gradient-Based Learned Runtime Pruning. CoRR abs/2204.03227 (2022) - 2021
- [c6]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: 54-70 - [c5]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: 1-7 - 2020
- [c4]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: 399-411 - [c3]Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh:
Bit-Parallel Vector Composability for Neural Acceleration. DAC 2020: 1-6 - [c2]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: 681-697 - [i2]Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh:
Bit-Parallel Vector Composability for Neural Acceleration. CoRR abs/2004.05333 (2020)
2010 – 2019
- 2019
- [i1]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 abs/1906.11915 (2019) - 2018
- [c1]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: 65-72
Coauthor Index
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