| E3:{Energy-Efficient} microservices on {SmartNIC-Accelerated} servers M Liu, S Peter, A Krishnamurthy, PM Phothilimthana 2019 USENIX Annual Technical Conference (USENIX ATC 19), 363-378, 2019 | 143 | 2019 |
| Floem: A programming system for {NIC-Accelerated} network applications PM Phothilimthana, M Liu, A Kaufmann, S Peter, R Bodik, T Anderson 13th USENIX Symposium on Operating Systems Design and Implementation (OSDI …, 2018 | 131 | 2018 |
| Scaling up superoptimization PM Phothilimthana, A Thakur, R Bodik, D Dhurjati Proceedings of the Twenty-First International Conference on Architectural …, 2016 | 127 | 2016 |
| Portable performance on heterogeneous architectures PM Phothilimthana, J Ansel, J Ragan-Kelley, S Amarasinghe ACM SIGARCH Computer Architecture News 41 (1), 431-444, 2013 | 118 | 2013 |
| Chlorophyll: Synthesis-aided compiler for low-power spatial architectures PM Phothilimthana, T Jelvis, R Shah, N Totla, S Chasins, R Bodik ACM SIGPLAN Notices 49 (6), 396-407, 2014 | 87 | 2014 |
| A learned performance model for tensor processing units S Kaufman, P Phothilimthana, Y Zhou, C Mendis, S Roy, A Sabne, ... Proceedings of Machine Learning and Systems 3, 387-400, 2021 | 69 | 2021 |
| Equality saturation for tensor graph superoptimization Y Yang, P Phothilimthana, Y Wang, M Willsey, S Roy, J Pienaar Proceedings of Machine Learning and Systems 3, 255-268, 2021 | 67 | 2021 |
| Swizzle inventor: data movement synthesis for GPU kernels PM Phothilimthana, AS Elliott, A Wang, A Jangda, B Hagedorn, H Barthels, ... Proceedings of the Twenty-Fourth International Conference on Architectural …, 2019 | 54 | 2019 |
| Transferable graph optimizers for ml compilers Y Zhou, S Roy, A Abdolrashidi, D Wong, P Ma, Q Xu, H Liu, ... Advances in Neural Information Processing Systems 33, 13844-13855, 2020 | 52 | 2020 |
| Communication-minimizing 2D convolution in GPU registers FN Iandola, D Sheffield, MJ Anderson, PM Phothilimthana, K Keutzer 2013 IEEE International Conference on Image Processing, 2116-2120, 2013 | 42 | 2013 |
| High-coverage hint generation for massive courses: Do automated hints help CS1 students? PM Phothilimthana, S Sridhara Proceedings of the 2017 ACM Conference on Innovation and Technology in …, 2017 | 28 | 2017 |
| A flexible approach to autotuning multi-pass machine learning compilers PM Phothilimthana, A Sabne, N Sarda, KS Murthy, Y Zhou, ... 2021 30th International Conference on Parallel Architectures and Compilation …, 2021 | 25 | 2021 |
| A comparison of error metrics for learning model parameters in bayesian knowledge tracing A Dhanani, SY Lee, PM Phothilimthana, Z Pardos Workshop Approaching Twenty Years of Knowledge Tracing (BKT20y). Citeseer, 8-9, 2014 | 21 | 2014 |
| Data-driven synthesis of full probabilistic programs S Chasins, PM Phothilimthana Computer Aided Verification: 29th International Conference, CAV 2017 …, 2017 | 20 | 2017 |
| Greenthumb: Superoptimizer construction framework PM Phothilimthana, A Thakur, R Bodik, D Dhurjati Proceedings of the 25th International Conference on Compiler Construction …, 2016 | 18 | 2016 |
| Short and simple cycle separators in planar graphs E Fox-Epstein, S Mozes, PM Phothilimthana, C Sommer Journal of Experimental Algorithmics (JEA) 21, 1-24, 2016 | 16 | 2016 |
| Learned TPU cost model for XLA tensor programs S Kaufman, PM Phothilimthana, M Burrows Proc. Workshop ML Syst. NeurIPS, 1-6, 2019 | 15 | 2019 |
| Granite: A graph neural network model for basic block throughput estimation O Sýkora, PM Phothilimthana, C Mendis, A Yazdanbakhsh 2022 IEEE International Symposium on Workload Characterization (IISWC), 14-26, 2022 | 14 | 2022 |
| Learning large graph property prediction via graph segment training K Cao, M Phothilimthana, S Abu-El-Haija, D Zelle, Y Zhou, C Mendis, ... Advances in Neural Information Processing Systems 36, 2024 | 7 | 2024 |
| Neural architecture search using property guided synthesis C Jin, PM Phothilimthana, S Roy Proceedings of the ACM on Programming Languages 6 (OOPSLA2), 1150-1179, 2022 | 7 | 2022 |
sudip royGoogle在 google.com 的电子邮件经过验证
