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Atefeh Sohrabizadeh
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2020 – today
- 2024
- [i7]Zongyue Qin, Yunsheng Bai, Atefeh Sohrabizadeh, Zijian Ding, Ziniu Hu, Yizhou Sun, Jason Cong:
Cross-Modality Program Representation Learning for Electronic Design Automation with High-Level Synthesis. CoRR abs/2406.09606 (2024) - 2023
- [j3]Yuze Chi, Weikang Qiao, Atefeh Sohrabizadeh, Jie Wang, Jason Cong:
Democratizing Domain-Specific Computing. Commun. ACM 66(1): 74-85 (2023) - [j2]Suhail Basalama
, Atefeh Sohrabizadeh
, Jie Wang
, Licheng Guo
, Jason Cong
:
FlexCNN: An End-to-end Framework for Composing CNN Accelerators on FPGA. ACM Trans. Reconfigurable Technol. Syst. 16(2): 23:1-23:32 (2023) - [c12]Atefeh Sohrabizadeh, Yunsheng Bai, Yizhou Sun, Jason Cong:
Robust GNN-Based Representation Learning for HLS. ICCAD 2023: 1-9 - [c11]Yunsheng Bai, Atefeh Sohrabizadeh, Zongyue Qin, Ziniu Hu, Yizhou Sun, Jason Cong:
Towards a Comprehensive Benchmark for High-Level Synthesis Targeted to FPGAs. NeurIPS 2023 - [i6]Shichang Zhang, Atefeh Sohrabizadeh, Cheng Wan, Zijie Huang, Ziniu Hu, Yewen Wang, Yingyan Lin, Jason Cong, Yizhou Sun:
A Survey on Graph Neural Network Acceleration: Algorithms, Systems, and Customized Hardware. CoRR abs/2306.14052 (2023) - 2022
- [j1]Atefeh Sohrabizadeh
, Cody Hao Yu, Min Gao, Jason Cong:
AutoDSE: Enabling Software Programmers to Design Efficient FPGA Accelerators. ACM Trans. Design Autom. Electr. Syst. 27(4): 32:1-32:27 (2022) - [c10]Atefeh Sohrabizadeh, Yuze Chi, Jason Cong:
StreamGCN: Accelerating Graph Convolutional Networks with Streaming Processing. CICC 2022: 1-8 - [c9]Atefeh Sohrabizadeh, Yunsheng Bai, Yizhou Sun, Jason Cong:
Automated accelerator optimization aided by graph neural networks. DAC 2022: 55-60 - [c8]Yunsheng Bai, Atefeh Sohrabizadeh, Yizhou Sun, Jason Cong:
Improving GNN-based accelerator design automation with meta learning. DAC 2022: 1347-1350 - [c7]Suhail Basalama, Atefeh Sohrabizadeh, Jie Wang, Jason Cong:
A Versatile Systolic Array for Transposed and Dilated Convolution on FPGA. FCCM 2022: 1-2 - [c6]Atefeh Sohrabizadeh, Yunsheng Bai, Yizhou Sun, Jason Cong:
Automated Accelerator Optimization Aided by Graph Neural Networks. FPGA 2022: 50 - [c5]Linghao Song
, Yuze Chi, Atefeh Sohrabizadeh, Young-kyu Choi
, Jason Lau
, Jason Cong:
Sextans: A Streaming Accelerator for General-Purpose Sparse-Matrix Dense-Matrix Multiplication. FPGA 2022: 65-77 - [c4]Atefeh Sohrabizadeh, Yuze Chi, Jason Cong:
SPA-GCN: Efficient and Flexible GCN Accelerator with Application for Graph Similarity Computation. FPGA 2022: 156 - [c3]Sihao Liu, Jian Weng, Dylan Kupsh, Atefeh Sohrabizadeh, Zhengrong Wang, Licheng Guo, Jiuyang Liu, Maxim Zhulin, Rishabh Mani, Lucheng Zhang, Jason Cong, Tony Nowatzki:
OverGen: Improving FPGA Usability through Domain-specific Overlay Generation. MICRO 2022: 35-56 - [i5]Yuze Chi, Weikang Qiao, Atefeh Sohrabizadeh, Jie Wang, Jason Cong:
Democratizing Domain-Specific Computing. CoRR abs/2209.02951 (2022) - 2021
- [c2]Atefeh Sohrabizadeh, Cody Hao Yu, Min Gao, Jason Cong:
AutoDSE: Enabling Software Programmers Design Efficient FPGA Accelerators. FPGA 2021: 147 - [i4]Linghao Song, Yuze Chi, Atefeh Sohrabizadeh, Young-kyu Choi, Jason Lau, Jason Cong:
Sextans: A Streaming Accelerator for General-Purpose Sparse-Matrix Dense-Matrix Multiplication. CoRR abs/2109.11081 (2021) - [i3]Atefeh Sohrabizadeh, Yuze Chi, Jason Cong:
SPA-GCN: Efficient and Flexible GCN Accelerator with an Application for Graph Similarity Computation. CoRR abs/2111.05936 (2021) - [i2]Atefeh Sohrabizadeh, Yunsheng Bai, Yizhou Sun, Jason Cong:
Enabling Automated FPGA Accelerator Optimization Using Graph Neural Networks. CoRR abs/2111.08848 (2021) - 2020
- [c1]Atefeh Sohrabizadeh, Jie Wang, Jason Cong:
End-to-End Optimization of Deep Learning Applications. FPGA 2020: 133-139 - [i1]Atefeh Sohrabizadeh, Cody Hao Yu, Min Gao, Jason Cong:
AutoDSE: Enabling Software Programmers Design Efficient FPGA Accelerators. CoRR abs/2009.14381 (2020)
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