Runbin Shi
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
12
Venues
11
Active years
2015–2026
Best venue rank
A*
Where they publish
Papers
12 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | SIGMOD | CoddSpeed: Hardware Accelerated Query Processing in Microsoft Fabric. | Matteo Interlandi, Nicolas Bruno, Brandon Haynes, Carlo Curino, Rathijit Sen, Yinan Li, Kaushik Rajan, Bailu Ding, Lukas M. Maas, Wei Cui, Kevin Gaffney, Mingsheng Hong, Brian Kroth, Sampath Rajendra, Peng Cheng, Surajit Chaudhuri, Johannes Gehrke, Raghu Ramakrishnan, Lidong Zhou, Momin Al-Ghosien, Craig Peeper, Marius Dumitru, Conor Cunningham, Kevin Bocksrocker, Prasanna Sundar, Ron Boskovic, YongChul Kwon, Marko Zivanovic, Runbin Shi, Krystian Sakowski, Denis Lamtsov, Josep Aguilar-Saborit, Krish Srinivasan, Adarsh Kapil, Andrew Putnam, Anudeep Kambapu, Aparna Konduri, Aaron Landy, Aaron Moore, Aaron Pitman, Artem Oks, Ashit Gosalia, Babu Kandimalla, Blake Pelton, Bogdan Crivat, Csar A. Galindo-Legaria, Chidamber Kulkarni, Jess Camacho-Rodrguez, Evgeny Babin, Hans Lehnert Marino, Igor Konev, Israel Arroyo, Luis Pearanda, Mandar Datar, Morten Borup Petersen, Nicholas Simmons, Parminder Poonian, Pravija Danda, Rob Rydberg, Esteban Calvo Vargas, Ronak Bajaj, Sai Sumanth Kammal Shetty, Sharanya Bhat, Zach Iracheta |
| 2023 | SC | Co-design Hardware and Algorithm for Vector Search. | Wenqi Jiang, Shigang Li, Yu Zhu, Johannes de Fine Licht, Zhenhao He, Runbin Shi, Cdric Renggli, Shuai Zhang, Theodoros Rekatsinas, Torsten Hoefler, Gustavo Alonso |
| 2021 | HPCA | Mix and Match: A Novel FPGA-Centric Deep Neural Network Quantization Framework. | Sung-En Chang, Yanyu Li, Mengshu Sun, Runbin Shi, Hayden K. H. So, Xuehai Qian, Yanzhi Wang, Xue Lin |
| 2020 | DAC | FTDL: A Tailored FPGA-Overlay for Deep Learning with High Scalability. | Runbin Shi, Yuhao Ding, Xuechao Wei, He Li, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding |
| 2020 | FPGA | FTDL: An FPGA-tailored Architecture for Deep Learning Systems. | Runbin Shi, Yuhao Ding, Xuechao Wei, Hang Liu, Hayden Kwok-Hay So, Caiwen Ding |
| 2020 | ICLR | Dynamic Sparse Training: Find Efficient Sparse Network From Scratch With Trainable Masked Layers. | Junjie Liu, Zhe Xu, Runbin Shi, Ray C. C. Cheung, Hayden Kwok-Hay So |
| 2020 | ICS | CSB-RNN: a faster-than-realtime RNN acceleration framework with compressed structured blocks. | Runbin Shi, Peiyan Dong, Tong Geng, Yuhao Ding, Xiaolong Ma, Hayden Kwok-Hay So, Martin C. Herbordt, Ang Li, Yanzhi Wang |
| 2020 | MICRO | AWB-GCN: A Graph Convolutional Network Accelerator with Runtime Workload Rebalancing. | Tong Geng, Ang Li, Runbin Shi, Chunshu Wu, Tianqi Wang, Yanfei Li, Pouya Haghi, Antonino Tumeo, Shuai Che, Steven K. Reinhardt, Martin C. Herbordt |
| 2019 | DAC | E-LSTM: Efficient Inference of Sparse LSTM on Embedded Heterogeneous System. | Runbin Shi, Junjie Liu, Hayden Kwok-Hay So, Shuo Wang, Yun Liang |
| 2016 | DATE | The neuro vector engine: Flexibility to improve convolutional net efficiency for wearable vision. | Maurice Peemen, Runbin Shi, Sohan Lal, Ben H. H. Juurlink, Bart Mesman, Henk Corporaal |
| 2016 | HPCC | A Heterogeneous System for Real-Time Detection with AdaBoost. | Zheng Xu, Runbin Shi, Zhihao Sun, Yaqi Li, Yuanjia Zhao, Chenjian Wu |
| 2015 | DSD | A Locality Aware Convolutional Neural Networks Accelerator. | Runbin Shi, Zheng Xu, Zhihao Sun, Maurice Peemen, Ang Li, Henk Corporaal, Di Wu |