| Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks C Mendis, A Renda, S Amarasinghe, M Carbin International Conference on Machine Learning, 4505-4515, 2019 | 166 | 2019 |
| Making caches work for graph analytics Y Zhang, V Kiriansky, C Mendis, S Amarasinghe, M Zaharia 2017 IEEE International Conference on Big Data (Big Data), 293-302, 2017 | 141 | 2017 |
| 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 | 68 | 2021 |
| Helium: Lifting high-performance stencil kernels from stripped x86 binaries to Halide DSL code C Mendis, J Bosboom, K Wu, S Kamil, J Ragan-Kelley, S Paris, Q Zhao, ... Proceedings of the 36th ACM SIGPLAN Conference on Programming Language …, 2015 | 47 | 2015 |
| Compiler auto-vectorization with imitation learning C Mendis, C Yang, Y Pu, DS Amarasinghe, M Carbin Advances in Neural Information Processing Systems 32, 2019 | 41 | 2019 |
| goSLP: globally optimized superword level parallelism framework C Mendis, S Amarasinghe Proceedings of the ACM on Programming Languages 2 (OOPSLA), 110, 2018 | 41 | 2018 |
| VeGen: a vectorizer generator for SIMD and beyond Y Chen, C Mendis, M Carbin, S Amarasinghe Proceedings of the 26th ACM International Conference on Architectural …, 2021 | 38 | 2021 |
| Difftune: Optimizing cpu simulator parameters with learned differentiable surrogates A Renda, Y Chen, C Mendis, M Carbin 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture …, 2020 | 37 | 2020 |
| BHive: A benchmark suite and measurement framework for validating x86-64 basic block performance models Y Chen, A Brahmakshatriya, C Mendis, A Renda, E Atkinson, O Sýkora, ... 2019 IEEE International Symposium on Workload Characterization (IISWC), 167-177, 2019 | 36 | 2019 |
| Optimizing cache performance for graph analytics Y Zhang, V Kiriansky, C Mendis, M Zaharia, S Amarasinghe arXiv preprint arXiv:1608.01362, 8, 2016 | 19 | 2016 |
| Parallelizing wfst speech decoders C Mendis, J Droppo, S Maleki, M Musuvathi, T Mytkowicz, G Zweig 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 18 | 2016 |
| Revec: Program Rejuvenation through Revectorization C Mendis, A Jain, P Jain, S Amarasinghe 28th International Conference on Compiler Construction, 29-41, 2019 | 17 | 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 | 12 | 2022 |
| All you need is superword-level parallelism: systematic control-flow vectorization with SLP Y Chen, C Mendis, S Amarasinghe Proceedings of the 43rd ACM SIGPLAN International Conference on Programming …, 2022 | 10 | 2022 |
| TGOpt: Redundancy-aware optimizations for temporal graph attention networks Y Wang, C Mendis Proceedings of the 28th ACM SIGPLAN Annual Symposium on Principles and …, 2023 | 9 | 2023 |
| WACO: learning workload-aware co-optimization of the format and schedule of a sparse tensor program J Won, C Mendis, JS Emer, S Amarasinghe Proceedings of the 28th ACM International Conference on Architectural …, 2023 | 8 | 2023 |
| Spade: A flexible and scalable accelerator for spmm and sddmm G Gerogiannis, S Yesil, D Lenadora, D Cao, C Mendis, J Torrellas Proceedings of the 50th Annual International Symposium on Computer …, 2023 | 6 | 2023 |
| Unified Convolution Framework: A compiler-based approach to support sparse convolutions J Won, C Hong, C Mendis, J Emer, S Amarasinghe Proceedings of Machine Learning and Systems 5, 2023 | 5 | 2023 |
| 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 | 4 | 2024 |
| Towards automated construction of compiler optimizations TCY Mendis Massachusetts Institute of Technology, 2020 | 4 | 2020 |
Saman AmarasingheMIT在 mit.edu 的电子邮件经过验证
