| From high-level deep neural models to FPGAs H Sharma, J Park, D Mahajan, E Amaro, JK Kim, C Shao, A Mishra, ... 2016 49th Annual IEEE/ACM International Symposium on Microarchitecture …, 2016 | 464 | 2016 |
| Tabla: A unified template-based framework for accelerating statistical machine learning D Mahajan, J Park, E Amaro, H Sharma, A Yazdanbakhsh, JK Kim, ... 2016 IEEE International Symposium on High Performance Computer Architecture …, 2016 | 157 | 2016 |
| FireSim: FPGA-accelerated cycle-exact scale-out system simulation in the public cloud S Karandikar, H Mao, D Kim, D Biancolin, A Amid, D Lee, N Pemberton, ... 2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture …, 2018 | 139 | 2018 |
| DNNWEAVER: From High-Level Deep Network Models to FPGA Acceleration H Sharma, J Park, E Amaro, B Thwaites, P Kotha, A Gupta, JK Kim, ... | 50 | 2016 |
| Can far memory improve job throughput? E Amaro, C Branner-Augmon, Z Luo, A Ousterhout, MK Aguilera, A Panda, ... Proceedings of the Fifteenth European Conference on Computer Systems, 1-16, 2020 | 46 | 2020 |
| AxGames: Towards Crowdsourcing Quality Target Determination in Approximate Computing J Park, E Amaro, D Mahajan, B Thwaites, H Esmaeilzadeh Proceedings of the Twenty-First International Conference on Architectural …, 2016 | 34 | 2016 |
| Remote Memory Calls E Amaro, Z Luo, A Ousterhout, A Krishnamurthy, A Panda, S Ratnasamy, ... Proceedings of the 19th ACM Workshop on Hot Topics in Networks, 38-44, 2020 | 7 | 2020 |
Hadi EsmaeilzadehAssociate Professor; Computer Science and Engineering; University of California, San DiegoVerified email at eng.ucsd.edu
