| Memristive logic: A framework for evaluation and comparison J Reuben, R Ben-Hur, N Wald, N Talati, AH Ali, PE Gaillardon, ... 2017 27th International Symposium on Power and Timing Modeling, Optimization …, 2017 | 51 | 2017 |
| Efficient algorithms for in-memory fixed point multiplication using magic A Haj-Ali, R Ben-Hur, N Wald, S Kvatinsky 2018 IEEE International Symposium on Circuits and Systems (ISCAS), 1-5, 2018 | 40 | 2018 |
| IMAGING: In-Memory AlGorithms for Image processiNG A Haj-Ali, R Ben-Hur, N Wald, R Ronen, S Kvatinsky IEEE Transactions on Circuits and Systems I: Regular Papers, 2018 | 34 | 2018 |
| Ansor: Generating high-performance tensor programs for deep learning L Zheng, C Jia, M Sun, Z Wu, CH Yu, A Haj-Ali, Y Wang, J Yang, D Zhuo, ... 14th {USENIX} Symposium on Operating Systems Design and Implementation …, 2020 | 30 | 2020 |
| NeuroVectorizer: End-to-end vectorization with deep reinforcement learning A Haj-Ali, NK Ahmed, T Willke, YS Shao, K Asanovic, I Stoica Proceedings of the 18th ACM/IEEE International Symposium on Code Generation …, 2020 | 29 | 2020 |
| SIMPLER MAGIC: Synthesis and Mapping of In-Memory Logic Executed in a Single Row to Improve Throughput R Ben-Hur, R Ronen, A Haj-Ali, D Bhattacharjee, A Eliahu, N Peled, ... IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2019 | 23 | 2019 |
| Gemmini: An agile systolic array generator enabling systematic evaluations of deep-learning architectures H Genc, A Haj-Ali, V Iyer, A Amid, H Mao, J Wright, C Schmidt, J Zhao, ... arXiv preprint arXiv:1911.09925, 2019 | 20 | 2019 |
| A View on Deep Reinforcement Learning in System Optimization A Haj-Ali, N K. Ahmed, T Willke, J Gonzalez, K Asanovic, I Stoica https://arxiv.org/abs/1908.01275, 2019 | 19* | 2019 |
| AutoCkt: deep reinforcement learning of analog circuit designs K Settaluri, A Haj-Ali, Q Huang, K Hakhamaneshi, B Nikolic 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE), 490-495, 2020 | 17 | 2020 |
| Not in name alone: A memristive memory processing unit for real in-memory processing A Haj-Ali, R Ben-Hur, N Wald, R Ronen, S Kvatinsky IEEE Micro 38 (5), 13-21, 2018 | 16 | 2018 |
| Practical challenges in delivering the promises of real processing-in-memory machines N Talati, AH Ali, RB Hur, N Wald, R Ronen, PE Gaillardon, S Kvatinsky 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2018 | 16 | 2018 |
| Autophase: Compiler phase-ordering for hls with deep reinforcement learning Q Huang, A Haj-Ali, W Moses, J Xiang, I Stoica, K Asanovic, J Wawrzynek 2019 IEEE 27th Annual International Symposium on Field-Programmable Custom …, 2019 | 14 | 2019 |
| mmpu—a real processing-in-memory architecture to combat the von neumann bottleneck N Talati, R Ben-Hur, N Wald, A Haj-Ali, J Reuben, S Kvatinsky Applications of Emerging Memory Technology, 191-213, 2020 | 12 | 2020 |
| Supporting the momentum training algorithm using a memristor-based synapse T Greenberg-Toledo, R Mazor, A Haj-Ali, S Kvatinsky IEEE Transactions on Circuits and Systems I: Regular Papers 66 (4), 1571-1583, 2019 | 8 | 2019 |
| A taxonomy and evaluation framework for memristive logic J Reuben, N Talati, N Wald, R Ben-Hur, AH Ali, PE Gaillardon, ... Handbook of Memristor Networks, 1065-1099, 2019 | 8 | 2019 |
| AutoPhase: Juggling HLS Phase Orderings in Random Forests with Deep Reinforcement Learning. A Haj-Ali, Qijing (Jenny) Huang, WS Moses, J Xiang, K Asanovic, ... MLSys, 2020 | 7 | 2020 |
| RLDRM: closed loop dynamic cache allocation with deep reinforcement learning for network function virtualization B Li, Y Wang, R Wang, C Tai, R Iyer, Z Zhou, A Herdrich, T Zhang, ... 2020 6th IEEE Conference on Network Softwarization (NetSoft), 335-343, 2020 | 4 | 2020 |
| ProTuner: tuning programs with Monte Carlo tree search A Haj-Ali, H Genc, Q Huang, W Moses, J Wawrzynek, K Asanović, I Stoica arXiv preprint arXiv:2005.13685, 2020 | 4 | 2020 |
| Learning to vectorize using deep reinforcement learning A Haj-Ali, NK Ahmed, T Willke, S Shao, K Asanovic, I Stoica Workshop on ML for Systems at NeurIPS, 2019 | 4 | 2019 |
| AutoPhase: Compiler Phase-Ordering for High Level Synthesis with Deep Reinforcement Learning A Haj-Ali, Q Huang, W Moses, J Xiang, I Stoica, K Asanovic, J Wawrzynek arXiv preprint arXiv:1901.04615, 2019 | 2 | 2019 |
Shahar KvatinskyTechnion - Israel Institute of TechnologyVerified email at ee.technion.ac.il
