Performances improvement of FPGA using novel multilevel hierarchical interconnection structure

By Mu Li, Kun Chang, Tao Wang, Lequan Liu, Huabin Zhang, Peng Li, Jinhua Ye. 2006

67 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering, Hardware and Architecture

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. P. Heng
2. Sergey Levine
3. Karol Hausman
4. C. Pal
5. Vikash Kumar
6. Abhishek Gupta
7. Michal Drozdzal
8. Qi-Yan Dou

In Electrical and Electronic Engineering

1. Abhishek Gupta
2. Vikash Kumar
3. Karol Hausman
4. Corey Lynch
5. Sergey Levine
6. C. Pal
7. Chelsea Finn
8. Aviral Kumar

In Hardware and Architecture

1. Hao Chen

Citations in the corpus

• Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning (2019, methodology): “As we show in our experiments, this bi-level initialization is significantly more amenable to RRF than learning the high level from scratch as described in [7, 15, 22], and allows us to avoid the expensive goal labeling that is required in [27].”
• The Liver Tumor Segmentation Benchmark (LiTS) (2019, methodology): “However, deformation limitations prevent SSMs capturing of the high variability of the liver shapes.”