Efficient-Domain-Soecial-Accelerator-Resources

Deep Learning

ASIC

Diannao: A small-footprint high-throughput accelerator for ubiquitous machine-learning.
T Chen, Z Du, N Sun, J Wang, C Wu, Y Chen, et al.
ACM SIGARCH Computer Architecture News 42 (1), 269-284, 2014. [Paper]

Dadiannao: A machine-learning supercomputer.
Y Chen, T Luo, S Liu, S Zhang, L He, J Wang, L Li, T Chen, Z Xu, N Sun, O Temam.
2014 47th Annual IEEE/ACM International Symposium on Microarchitecture, 2014. [Paper]

Tpu v4: An optically reconfigurable supercomputer for machine learning with hardware support for embeddings.
N Jouppi, G Kurian, S Li, P Ma, R Nagarajan, L Nai, N Patil, S Subramanian, A Swing, et al.
Proceedings of the 50th Annual International Symposium on Computer Architecture, 2023. [Paper]

FPGA

Optimizing FPGA-based accelerator design for deep convolutional neural networks.
C Zhang, P Li, G Sun, Y Guan, B Xiao, J Cong.
Proceedings of the 2015 ACM/SIGDA international symposium on field-programmable gate arrays, 2015. [Paper]

Towards High-accuracy and Real-time Two-stage Small Object Detection on FPGA.
S Li, Z Zhu, H Sun, X Ning, G Dai, Y Hu, H Yang, Y Wang.
IEEE Transactions on Circuits and Systems for Video Technology, 2024. [Paper]

Flightllm: Efficient large language model inference with a complete mapping flow on fpgas.
S Zeng, J Liu, G Dai, X Yang, T Fu, H Wang, W Ma, H Sun, S Li, Z Huang, Y Dai, J Li, Z Wang, et al.
Proceedings of the 2015 ACM/SIGDA international symposium on field-programmable gate arrays, 2024. [Paper]

Finance

Deeplob: Deep convolutional neural networks for limit order books.
Z Zhang, S Zohren, S Roberts.
IEEE Transactions on Signal Processing, 2019. [Paper]

LightTrader: A standalone high-frequency trading system with deep learning inference accelerators and proactive scheduler.
S Yoo, H Kim, J Kim, S Park, JY Kim.
2023 IEEE International Symposium on High-Performance Computer Architecture, 2023. [Paper]

Cross-contextual Sequential Optimization via Deep Reinforcement Learning for Algorithmic Trading.
K Pan, Y Hu, L Han, H Sun, D Cheng, Y Liang.
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management, 2024. [Paper]