In-memory database acceleration on FPGAs: a survey

J Fang, YTB Mulder, J Hidders, J Lee, HP Hofstee - The VLDB Journal, 2020 - Springer
While FPGAs have seen prior use in database systems, in recent years interest in using
FPGA to accelerate databases has declined in both industry and academia for the following …

A survey of deep learning techniques for autonomous driving

S Grigorescu, B Trasnea, T Cocias… - Journal of field …, 2020 - Wiley Online Library
The last decade witnessed increasingly rapid progress in self‐driving vehicle technology,
mainly backed up by advances in the area of deep learning and artificial intelligence (AI) …

Spatten: Efficient sparse attention architecture with cascade token and head pruning

H Wang, Z Zhang, S Han - 2021 IEEE International Symposium …, 2021 - ieeexplore.ieee.org
The attention mechanism is becoming increasingly popular in Natural Language Processing
(NLP) applications, showing superior performance than convolutional and recurrent …

Mix and match: A novel fpga-centric deep neural network quantization framework

SE Chang, Y Li, M Sun, R Shi, HKH So… - … Symposium on High …, 2021 - ieeexplore.ieee.org
Deep Neural Networks (DNNs) have achieved extraordinary performance in various
application domains. To support diverse DNN models, efficient implementations of DNN …

Hbm connect: High-performance hls interconnect for fpga hbm

Y Choi, Y Chi, W Qiao, N Samardzic… - The 2021 ACM/SIGDA …, 2021 - dl.acm.org
With the recent release of High Bandwidth Memory (HBM) based FPGA boards, developers
can now exploit unprecedented external memory bandwidth. This allows more memory …