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HyBNN: Quantifying and Optimizing Hardware Efficiency of Binary Neural Networks
TRETS 2023
Geng Yang, Jie Lei, Zhenman Fang, Yunsong Li, Jiaqing Zhang, Weiying Xie.
Accepted by ACM Transactions on Reconfigurable Technology and Systems (TRETS 2023), FPT 2023 Journal Track.
J15
CHIP-KNNv2: A Configurable and High-Performance K-Nearest Neighbors Accelerator on HBM-based FPGAs
TRETS 2023
Kenny Liu, Alec Lu, Kartik Samtani, Zhenman Fang, and Licheng Guo
ACM Transactions on Reconfigurable Technology and Systems (TRETS 2023), Volume 16, Issue 4, Dec 2023, Article No.: 62, pp 1–26.
J14
TAPA: A Scalable Task-Parallel Dataflow Programming Framework for Modern FPGAs with Co-Optimization of HLS and Physical Design
TRETS 2023
Licheng Guo, Yuze Chi, Jason Lau, Linghao Song, Xingyu Tian, Moazin Khatti, Weikang Qiao, Jie Wang, Ecenur Ustun, Zhenman Fang, Zhiru Zhang, and Jason Cong
ACM Transactions on Reconfigurable Technology and Systems (TRETS 2023), Volume 16, Issue 4, Dec 2023, Article No.: 63, pp 1–31.
J13
SASA: A Scalable and Automatic Stencil Acceleration Framework for Optimized Hybrid Spatial and Temporal Parallelism on HBM-based FPGAs
TRETS 2023
Xingyu Tian, Zhifan Ye, Alec Lu, Licheng Guo, Yuze Chi, and Zhenman Fang
ACM Transactions on Reconfigurable Technology and Systems (TRETS 2023), Volume 16, Issue 2, Apr 2023, Article No.: 28, pp 1–33.
J12
SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing Imagery
TGRS 2023
Jiaqing Zhang, Jie Lei, Weiying Xie, Zhenman Fang, Yunsong Li, Qian Du
IEEE Transactions on Geoscience and Remote Sensing (TGRS 2023), vol. 61, pp. 1-15, Mar 2023, Art no. 5605415.
J11
TopSort: A High-Performance Two-Phase Sorting Accelerator Optimized on HBM-based FPGAs
TETC 2023
Weikang Qiao, Licheng Guo, Zhenman Fang, Mau-Chung Frank Chang, and Jason Cong
IEEE Transactions on Emerging Topics in Computing (TETC 2023 Invited Paper), vol. 11, no. 2, pp. 404-419, 1 April-June 2023.
J10
Algorithm/Hardware Co-Design for Real-Time On-Satellite CNN based Ship Detection in SAR Imagery
TGRS 2022
Geng Yang, Jie Lei, Weiying Xie, Zhenman Fang, Yunsong Li, Jiaxvan Wang, Xin Zhang
The IEEE Transactions on Geoscience and Remote Sensing (TGRS 2022), vol. 60, pp. 1-18, Mar 2022, Art no. 5226018.
J9
Demystifying the Soft and Hardened Memory Systems of Modern FPGAs for Software Programmers through Microbenchmarking
TRETS 2022
Alec Lu, Zhenman Fang, and Lesley Shannon
The ACM Transactions on Reconfigurable Technology and Systems (TRETS 2022), Volume 15, Issue 4, December 2022, Article No.: 43, pp 1–33.
J8
SyncNN: Evaluating and Accelerating Spiking Neural Networks on FPGAs
TRETS 2022
Sathish Panchapakesan, Zhenman Fang, and Jian Li.
The ACM Transactions on Reconfigurable Technology and Systems (TRETS 2022), Volume 15, Issue 4, December 2022, Article No.: 48, pp 1–27.
J7
Quick-Div: Rethinking Integer Divider Design for FPGA-based Soft-Processors
TRETS 2022
Eric Matthews, Alec Lu, Zhenman Fang, and Lesley Shannon
ACM Transactions on Reconfigurable Technology and Systems (TRETS 2022), Volume 15, Issue 3, September 2022, Article No.: 32, pp 1–27.
J6
[Invited paper] Programming and Synthesis for Software-defined FPGA Acceleration: Status and Future Prospects
TRETS 2021
Yi-Hsiang Lai, Ecenur Ustun, Shaojie Xiang, Zhenman Fang, Hongbo Rong, Zhiru Zhang
ACM Transactions on Reconfigurable Technology and Systems (TRETS 2021), Volume 14, Issue 4, December 2021, Article No.: 17, pp 1–39.
Efficient Learned Image Compression with Selective Kernel Residual Module and Channel-wise Causal Context Model
ICASSP 2024
Haisheng Fu, Feng Liang, Jie Liang, Zhenman Fang, Guohe Zhang, Jingning Han.
The 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, April 2024, pp. 4040-4044.
C34
Learned Image Compression with Dual-Branch Encoder and Conditional Information Coding
DCC 2024
Haisheng Fu, Feng Liang, Jie Liang, Zhenman Fang, Guohe Zhang, Jingning Han.
The 2024 IEEE Data Compression Conference (DCC 2024), Snowbird, Utah, March 2024.
C33
HiSpMV: Hybrid Row Distribution and Vector Buffering for Imbalanced SpMV Acceleration on FPGAs
FPGA 2024
Manoj Bheemasandra Rajashekar, Xingyu Tian, Zhenman Fang.
The 32nd ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2024), Monterey, CA, Mar 2023, pp. 154-164. This paper received the highest review score among all FPGA 2024 submissions, tied with two other papers.
Acceptance Rate: 23.6%, 21 out of 89.
C32
PASTA: Programming and Automation Support for Scalable Task-Parallel HLS Programs on Modern Multi-Die FPGAs
FCCM 2023
Moazin Khatti, Xingyu Tian, Yuze Chi, Licheng Guo, Jason Cong, Zhenman Fang.
The 31st IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM 2023), Marina Del Rey, CA, May 2023, pp. 12-22.
Acceptance Rate: 21.4%, 15 out of 70.
C31
SQL2FPGA: Automatic Acceleration of SQL Query Processing on Modern CPU-FPGA Platforms
FCCM 2023
Alec Lu, Zhenman Fang.
The 31st IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM 2023), Marina Del Rey, CA, May 2023, pp. 184-194.
Acceptance Rate: 21.4%, 15 out of 70.
C30
ESRU: Extremely Low-Bit and Hardware-Efficient Stochastic Rounding Unit Design for 8-Bit DNN Training
DATE 2023
Sung-En Chang, Geng Yuan, Alec Lu, Mengshu Sun, Yanyu Li, Xiaolong Ma, Zhengang Li, YanyueXie, Minghai Qin, Xue Lin, Zhenman Fang, and Yanzhi Wang.
Design, Automation and Test in Europe Conference (DATE 2023), Antwerp, Belgium, Apr 2023, pp. 1-6.
Acceptance Rate: 25%.
C29
HeatViT: Hardware-Efficient Adaptive Token Pruning for Vision Transformers
HPCA 2023
Peiyan Dong, Mengshu Sun, Alec Lu, Yanyue Xie, Kenneth Liu, Zhenglun Kong, Xin Meng, Zhengang Li, Xue Lin, Zhenman Fang, and Yanzhi Wang.
The 29th IEEE International Symposium on High-Performance Computer Architecture (HPCA 2023), Montreal, QC, Canada, Feb-Mar 2023, pp. 442-455.
Acceptance Rate: 25%, 91 out of 360.
C28
You Already Have It: A Generator-Free Low-Precision DNN Training Framework using Stochastic Rounding
ECCV 2022
Geng Yuan, Sung-En Chang, Qing Jin, Alec Lu, Yanyu Li, Yushu Wu, Zhenglun Kong, Yanyue Xie, Peiyan Dong, Minghai Qin, Xiaolong Ma, Xulong Tang, Zhenman Fang, and Yanzhi Wang.
The European Conference on Computer Vision (ECCV 2022), Tel Aviv, Israel, Oct 2022. Lecture Notes in Computer Science, vol 13672, pp. 34–51.
Acceptance Rate: 28%, 1,645 out of 5,804.
C27
Blind Data Adversarial Bit-flip Attack against Deep Neural Networks
DSD 2022
Behnam Ghavami, Mani Sadati, Mohammad Shahidzadeh, Zhenman Fang and Lesley Shannon.
The Euromicro Conference on Digital Systems Design (DSD 2022), Virtual Conference, Aug-Sept 2022, pp. 899-904.
C26
A Majority-based Approximate Adder for FPGAs
DSD 2022
Behnam Ghavami, Mahdi Sajedi, Mohsen Raji, Zhenman Fang and Lesley Shannon.
The Euromicro Conference on Digital Systems Design (DSD 2022), Virtual Conference, Aug-Sept 2022, pp. 53-59.
C25
Auto-ViT-Acc: FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization
FPL 2022
Zhengang Li, Mengshu Sun, Alec Lu, Haoyu Ma, Geng Yuan, Yanyue Xie, Hao Tang, Yanyu Li, Miriam Leeser, Zhangyang Wang, Xue Lin, Zhenman Fang.
The 32nd International Conference on Field-Programmable Logic and Applications (FPL 2022), Belfast, UK, Aug-Sept 2022, pp. 109-116.
Acceptance Rate: 25.6%, 33 out of 129.
C24
Stealthy Attack on Algorithmic-Protected DNNs via Smart Bit Flipping
ISQED 2022
Behnam Ghavami, Sayed Hamid Reza Mousavi, Zhenman Fang, Lesley Shannon.
The 23nd International Symposium on Quality Electronic Design (ISQED 2022), Virtual Conference, Apr 2022, pp. 358-364.
C23
FILM-QNN: Efficient FPGA Acceleration of Deep Neural Networks with Intra-Layer, Mixed-Precision Quantization
FPGA 2022
Mengshu Sun, Zhengang Li, Alec Lu, Yanyu Li, Sung-En Chang, Xiaolong Ma, Xue Lin, and Zhenman Fang.
The 32nd ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2022), Virtual Conference, Feb/Mar 2022, pp. 134–145.
Acceptance Rate: 20.8%, 15 out of 72.
C22
FitAct: Error Resilient Deep Neural Networks via Fine-Grained Post-Trainable Activation Functions
DATE 2022
Behnam Ghavami, Mani Sadati, Zhenman Fang, and Lesley Shannon.
The Design, Automation and Test in Europe Conference (DATE 2022), Virtual Conference, Mar 2022, pp. 1239-1244.
Acceptance Rate: 25%.
C21
SyncNN: Evaluating and Accelerating Spiking Neural Networks on FPGAs
FPL 2021
Sathish Panchapakesan, Zhenman Fang, and Jian Li.
The 31st International Conference on Field-Programmable Logic and Applications (FPL 2021), Virtual Conference, Sept 2021, pp. 286-293.
Acceptance Rate: 22.2%, 32 out of 144.
C20
Demystifying the Memory System of Modern Datacenter FPGAs for Software Programmers through Microbenchmarking
FPGA 2021
Alec Lu, Zhenman Fang, Weihua Liu, and Lesley Shannon
The 29th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2021) , Virtual Conference, Mar 2021, pp. 105–115. This is one of the top papers at FPGA 2021 that are highlighted in the FPGA 2021 Special Issue in ACM TRETS.
Acceptance Rate: 19.8%, 22 out of 111.
C19
CHIP-KNN: A Configurable and High-Performance K-Nearest Neighbors Accelerator on Cloud FPGAs
FPT 2020
Alec Lu, Zhenman Fang, Nazanin Farahpour, and Lesley Shannon
The 2020 The International Conference on Field-Programmable Technology (FPT 2020), Virtual Conference, Dec 2020, pp. 139-147.
Acceptance Rate: 24.7%, 21 out of 85.
C18
Reconfigurable Accelerator Compute Hierarchy: A Case Study Using Content-Based Image Retrieval
IISWC 2020
Nazanin Farahpour, Yuchen Hao, Zhenman Fang and Glenn Reinman
The 2020 IEEE International Symposium on Workload Characterization (IISWC 2020), Virtual Conference, Oct 2020, pp. 276-287.
Acceptance Rate: 37.1%, 26 out of 70.
C17
Aadam: A Fast, Accurate, and Versatile Aging-Aware Cell Library Delay Model using Feed-Forward Neural Network
ICCAD 2020
Seyed Milad Ebrahimipour, Behnam Ghavami, Hamdi Mousavi, Mohsen Raji, Zhenman Fang and Lesley Shannon
The 2020 International Conference On Computer Aided Design (ICCAD 2020), Virtual Conference, Nov 2020, pp. 1-9.
Acceptance Rate: 27.0%, 127 out of 470.
C16
Algorithm-Hardware Co-design for BQSR Acceleration in Genome Analysis ToolKit
FCCM 2020
Michael Lo, Zhenman Fang, Jie Wang, Peipei Zhou, Mau-Chung Frank Chang and Jason Cong
The 28th IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM 2020), Fayetteville, AR, USA, May 2020, pp. 157-166.
Acceptance Rate: 20.7%, 19 out of 92.
C15
[Invited paper] Understanding Performance Gains of Accelerator-Rich Architectures
ASAP 2019
Zhenman Fang, Farnoosh Javadi, Jason Cong, Glenn Reinman
The 30th IEEE International Conference on Application-specific Systems, Architectures and Processors (ASAP 2019), New York NY, Jul 2019, pp. 239-246.
C14
Rethinking Integer Divider Design for FPGA-based Soft-Processors
FCCM 2019
Eric Matthews, Alec Lu, Lesley Shannon, Zhenman Fang
The 27th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2019), San Diego CA, Apr 2019, pp. 289-291.
Acceptance Rate: 25.8%, 31 out of 120.
C13
High-Throughput Lossless Compression on Tightly-Coupled CPU-FPGA Platforms
FCCM 2018
Weikang Qiao, Jieqiong Du, Zhenman Fang, Jason Cong, Mau-Chung Frank Chang
The 26th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2018), Boulder CO, May 2018, pp. 37-44.
Acceptance Rate: 20.8%, 22 out of 106.
C12
Doppio: I/O-Aware Performance Analysis, Modeling and Optimization for In-Memory Computing Framework
ISPASS 2018 Best Paper Nominee
Peipei Zhou, Zhenyuan Ruan, Zhenman Fang, Jason Cong, Megan Shand, David Roazen
The 2018 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS 2018 Best Paper Nominee), Belfast, Northern Ireland, UK, Apr 2018, pp. 22-32.
Acceptance Rate: 31.3%, 21 out of 67. Best paper nominee rate: 6.0%, 4 out of 67.
C11
AIM: Accelerating Computational Genomics through Scalable and Noninvasive Accelerator-Interposed Memory
MEMSYS 2017 Best Paper
Jason Cong, Zhenman Fang, Michael Gill, Farnoosh Javadi, Glenn Reinman
The International Symposium on Memory Systems (MEMSYS 2017 Best Paper Award), Alexandria, VA, Oct 2017, pp. 3-14.
Acceptance Rate: N/A. Best paper award rate: << 2.4%, 1 out of 42 accepted papers.
Jason Cong, Zhenman Fang, Yuchen Hao, Glenn Reinman
The 23rd IEEE Symposium on High Performance Computer Architecture (HPCA 2017 Best Paper Nominee), Austin TX, Feb 2017, pp. 37-48.
Acceptance Rate: 22.3%, 50 out of 224. Best paper nominee rate: 1.8%, 4 out of 224.
C9
Caffeine: Towards Uniformed Representation and Acceleration for Deep Convolutional Neural Networks
ICCAD 2016
Chen Zhang, Zhenman Fang, Peipei Zhou, Peichen Pan, Jason Cong
The 2016 IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2016), Austin TX, Nov 2016, pp. 1-8.
Acceptance Rate: 23.7%, 97 out of 409.
C8
Programming and Runtime Support to Blaze FPGA Accelerator Deployment at Datacenter Scale
ACM SoCC 2016
Muhuan Huang, Di Wu, Cody Hao Yu, Zhenman Fang, Matteo Interlandi, Tyson Condie, Jason Cong
The ACM Symposium on Cloud Computing (ACM SoCC 2016), Santa Clara, CA, Oct 2016, pp. 456-469.
Acceptance Rate: 25.2%, 38 out of 151.
C7
When Apache Spark Meets FPGAs: A Case Study for Next-Generation DNA Sequencing Acceleration
HotCloud 2016
Yu-Ting Chen, Jason Cong, Zhenman Fang, Jie Lei, Peng Wei
The 8th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 2016), Denver CO, Jun 2016, pp. 64-70.
Acceptance Rate: 30.9%, 21 out of 68.
C6
A Quantitative Analysis on Microarchitectures of Modern CPU-FPGA Platforms
DAC 2016
Young-kyu Choi, Jason Cong, Zhenman Fang, Yuchen Hao, Glenn Reinman, Peng Wei
53rd Design Automation Conference (DAC 2016), Austin TX, Jun 2016, pp. 1-6.
Acceptance Rate: 22.6%, 152 out of 674.
C5
PARADE: A Cycle-Accurate Full-System Simulation Platform for Accelerator-Rich Architectural Design and Exploration
ICCAD 2015
Jason Cong, Zhenman Fang, Michael Gill, Glenn Reinman
2015 IEEE/ACM International Conference on Computer-Aided Design (ICCAD 2015), Austin TX, Nov 2015, pp. 380-387.
Acceptance Rate: 24.6%, 94 out of 382.
C4
Multi-Stage Coordinated Prefetching for Present-day Processors
ICS 2014
Sanyam Mehta, Zhenman Fang, Antonia Zhai, Pen-Chung Yew
Proceedings of the 28th International Conference on Supercomputing (ICS 2014), Munich, Germany, Jun 2014, pp. 73-82.
Acceptance Rate: 21.3%, 34 out of 160.
C3
Transformer: A Functional-Driven Cycle-Accurate Multicore Simulator
DAC 2012
Zhenman Fang, Qinghao Min, Keyong Zhou, Yi Lu, Yibin Hu, Weihua Zhang, Haibo Chen, Jian Li, Binyu Zang
The 49th Design Automation Conference (DAC 2012), San Francisco CA, Jun 2012, pp. 106-114.
Acceptance Rate: 22.7%, 168 out of 741.
C2
Improving Dynamic Prediction Accuracy Through Multi-Level Phase Analysis
LCTES 2012
Zhenman Fang, Jiaxin Li, Weihua Zhang, Yi Li, Haibo Chen, Binyu Zang
Proceedings of the 2012 ACM SIGPLAN/SIGBED Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES 2012), Beijing, China, Jun 2012, pp. 89-98.
Acceptance Rate: 22.7%, 15 out of 66.
C1
A Comprehensive Analysis and Parallelization of an Image Retrieval Algorithm
ISPASS 2011
Zhenman Fang, Donglei Yang, Weihua Zhang, Haibo Chen, Binyu Zang
The 2011 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS 2011), Austin TX, Apr 2011, pp. 154-164.
Acceptance Rate: 37.5%, 24 out of 64.
MAPLE: A Machine Learning based Aging-Aware FPGA Architecture Exploration Framework
FPL 2021 Short Paper
Behnam Ghavami, Milad Ebrahimi, Zhenman Fang, Lesley Shannon
The 31st International Conference on Field-Programmable Logic and Applications (FPL 2021 Short Paper), Virtual Conference, Sept 2021, pp. 369-373.
Acceptance Rate: 37.5%, 54 out of 144.
SC4
FPGA-based Near Data Processing Platform Selection Using Fast Performance Modeling
LCTES 2020 Short WIP Paper
Nazanin Farahpour, Zhenman Fang, and Glenn Reinman
The 21st ACM SIGPLAN/SIGBED International Conference on Languages, Compilers, and Tools for Embedded Systems (LCTES 2020 Short WIP Paper), June 2020, pp. 151-155.
Mau-Chung Frank Chang, Jason Cong, Zhenman Fang, Weikang Qiao
The 27th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2019 short paper), San Diego CA, Apr 2019, pp. 96-99.
Acceptance Rate: 17.9%, 7 out of 39.
Jason Cong, Zhenman Fang, Michael Lo, Hanrui Wang, Jingxian Xu, Shaochong Zhang
The 26th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2018 short paper), Boulder CO, May 2018, pp. 172-175.
Acceptance Rate: 14.6%, 7 out of 48.
SC1
Energy Efficiency of Fully Pipelining: A Case Study for Matrix Multiplication
FCCM 2016 Short Paper
Peipei Zhou, HyunSeok Park, Zhenman Fang, Jason Cong, Andre DeHon
The 24th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2016 short paper), Washington DC, May 2016, pp. 172-175.
Acceptance Rate: 24.1%, 32 out of 133.
Heterogeneous instantiation of high-level language callable library for hardware core
Zhenman Fang, James L Hwang, Alfred Huang, Michael Gill, Tom Shui
US patent: 10762265 B1. Publication date: Sept 1, 2020.
P2
Automatic creation of high-level language callable library for a hardware core
Zhenman Fang, James L Hwang, Samuel A Skalicky, Tom Shui, Michael Gill, Welson Sun, Alfred Huang, Jorge E Carrillo, Chen Pan
US patent: 10755013 B1. Publication date: Aug 25, 2020.
P1
Image/video feature extraction parallel algorithm based on multi-core system structure
Weihua Zhang, Zhenman Fang, Donglei Yang, Binyu Zang
China patent: CN102495725 A. Publication date: Jun 13, 2012.
E4SA: An Ultra-Efficient Systolic Array Architecture for 4-Bit Convolutional Neural Networks
FPGA 2024 poster
Geng Yang, Jie Lei, Zhenman Fang, Jiaqing Zhang, Junrong Zhang, Weiying Xie, Yunsong Li.
The 32nd ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2024 poster), Monterey, CA, Mar 2023.
A14
HyBNN: Quantifying and Optimizing Hardware Efficiency of Binary Neural Networks
FCCM 2023 poster
Geng Yang, Jie Lei, Zhenman Fang, Yunsong Li, Jiaqing Zhang, Weiying Xie
The 31st IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM 2023 poster), Marina Del Rey, CA, May 2023, pp. 203.
A13
FPGA-Aware Automatic Acceleration Framework for Vision Transformer with Mixed-Scheme Quantization
DAC 2022 LBR
Mengshu Sun, Zhengang Li, Alec Lu, Haoyu Ma, Geng Yuan, Yanyue Xie, Hao Tang, Yanyu Li, Miriam Leeser, Zhangyang Wang, Xue Lin, and Zhenman Fang.
In Proceedings of the 59th ACM/IEEE Design Automation Conference (DAC 2022 Late Breaking Results), San Francisco, CA, USA, Jul 2022, pp. 1394–1395.
A12
Hardware-Efficient Stochastic Rounding Unit Design for DNN Training
DAC 2022 LBR
Sung-En Chang, Geng Yuan, Alec Lu, Mengshu Sun, Yanyu Li, Xiaolong Ma, Zhengang Li, Yanyue Xie, Minghai Qin, Xue Lin, Zhenman Fang, and Yanzhi Wang.
In Proceedings of the 59th ACM/IEEE Design Automation Conference (DAC 2022 Late Breaking Results), San Francisco, CA, USA, Jul 2022, pp. 1396–1397.
A11
You Already Have It: A Generator-Free Low-Precision DNN Training Framework using Stochastic Rounding
DAC 2022 WIP
Geng Yuan, Sung-En Chang, Qing Jin, Alec Lu, Yanyu Li, Yushu Wu, Zhenglun Kong, Yanyue Xie, Peiyan Dong, Xiaolong Ma, Xulong Tang, Minghai Qin, Zhenman Fang, and Yanzhi Wang.
The 59th ACM/IEEE Design Automation Conference 2022 (DAC 2022 WIP), San Francisco, CA, USA, Jul 2022.
A10
TopSort: A High-Performance Two-Phase Sorting Accelerator Optimized on HBM-based FPGAs
FCCM 2022 poster
Weikang Qiao, Licheng Guo, Zhenman Fang, Mau-Chung Frank Chang and Jason Cong
The 30th IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM 2022 poster), New York City, NY, USA, May 2020.
A9
Stealth Attack on Protected DNNs: Compromising Robustness without Losing Accuracy via Smart Bit Flipping
DAC 2021 WIP
Behnam Ghavami, Sayed Hamid Reza Mousavi, Zhenman Fang and Lesley Shannon
The Design Automation Conference 2021 (DAC 2021 WIP), San Francisco, CA, USA, Dec 2021.
A8
LEAP: A Deep Learning based Aging-Aware Architecture Exploration Framework for FPGAs
FPGA 2021 poster
Behnam Ghavami, S. Milad Ebrahimipour, Zhenman Fang and Lesley Shannon
The 29th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2021 poster) , Virtual Conference, Mar 2021.
Sathish Panchapakesan, Zhenman Fang and Nitin Chandrachoodan
The 28th IEEE International Symposium On Field-Programmable Custom Computing Machines (FCCM 2020 poster), Fayetteville, AR, USA, May 2020.
A6
K-Flow: A Dynamic Job Scheduling Framework to Optimize Dataflow Execution on CPU-FPGA Platforms
FPGA 2018 poster
Jason Cong, Zhenman Fang, Yao Hu and Di Wu
The 26th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2018 poster), 2018.
A5
Understanding Performance Differences of FPGAs and GPUs
FPGA 2018 poster
Jason Cong, Zhenman Fang, Michael Lo, Hanrui Wang, Jingxian Xu, Shaochong Zhang
The 26th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2018 poster), 2018.
A4
High-Throughput Lossless Compression on Tightly-Coupled CPU-FPGA Platforms
FPGA 2018 poster
Weikang Qiao, Jieqiong Du, Zhenman Fang, Jason Cong, Mau-Chung Frank Chang
The 26th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2018 poster), 2018.
A3
CPU-FPGA Co-Optimization for Big Data Applications: A Case Study of In-Memory Samtool Sorting
FPGA 2017 poster
Jason Cong, Zhenman Fang, Muhuang Huang, Libo Wang, Di Wu
The 25th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2017 poster), 2017.
A2
When Spark Meets FPGAs: A Case Study for Next-Generation DNA Sequencing Acceleration
FCCM 2016 poster
Yu-Ting Chen, Jason Cong, Zhenman Fang, Jie Lei, Peng Wei
The 24th IEEE International Symposium on Field-Programmable Custom Computing Machines (FCCM 2016 poster), 2016.
A1
ARAPrototyper: Enabling Rapid Prototyping and Evaluation for the Accelerator-Rich Architecture
FPGA 2016 Poster
Yu-Ting Chen, Jason Cong, Zhenman Fang, Peipei Zhou
The 24th ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 16 poster), 2016.