| Parallel multi channel convolution using general matrix multiplication A Vasudevan, A Anderson, D Gregg 2017 IEEE 28th International Conference on Application-specific Systems …, 2017 | 201 | 2017 |
| Low-memory gemm-based convolution algorithms for deep neural networks A Anderson, A Vasudevan, C Keane, D Gregg arXiv preprint arXiv:1709.03395, 2017 | 77 | 2017 |
| Optimal DNN primitive selection with partitioned boolean quadratic programming A Anderson, D Gregg Proceedings of the 2018 International Symposium on Code Generation and …, 2018 | 39 | 2018 |
| High-Performance Low-Memory Lowering: GEMM-based Algorithms for DNN Convolution A Anderson, A Vasudevan, C Keane, D Gregg 2020 IEEE 32nd International Symposium on Computer Architecture and High …, 2020 | 34 | 2020 |
| Error analysis and improving the accuracy of Winograd convolution for deep neural networks B Barabasz, A Anderson, KM Soodhalter, D Gregg ACM Transactions on Mathematical Software (TOMS) 46 (4), 1-33, 2020 | 31 | 2020 |
| Winograd convolution for deep neural networks: Efficient point selection SA Alam, A Anderson, B Barabasz, D Gregg ACM Transactions on Embedded Computing Systems 21 (6), 1-28, 2022 | 30 | 2022 |
| Automatic vectorization of interleaved data revisited A Anderson, A Malik, D Gregg ACM Transactions on Architecture and Code Optimization (TACO) 12 (4), 1-25, 2015 | 24 | 2015 |
| Bonseyes AI Pipeline—Bringing AI to You: End-to-end integration of data, algorithms, and deployment tools MD Prado, J Su, R Saeed, L Keller, N Vallez, A Anderson, D Gregg, ... ACM Transactions on Internet of Things 1 (4), 1-25, 2020 | 20 | 2020 |
| Performance-oriented neural architecture search A Anderson, J Su, R Dahyot, D Gregg 2019 International Conference on High Performance Computing & Simulation …, 2019 | 20 | 2019 |
| Vectorization of multibyte floating point data formats A Anderson, D Gregg Proceedings of the 2016 International Conference on Parallel Architectures …, 2016 | 18 | 2016 |
| Efficient Multibyte Floating Point Data Formats Using Vectorization A Anderson, S Muralidharan, D Gregg IEEE Transactions on Computers 66 (12), 2081-2096, 2017 | 14 | 2017 |
| TASO: Time and Space Optimization for Memory-Constrained DNN Inference Y Wen, A Anderson, V Radu, MFP O'Boyle, D Gregg 2020 IEEE 32nd International Symposium on Computer Architecture and High …, 2020 | 13 | 2020 |
| Taxonomy of Saliency Metrics for Channel Pruning K Persand, A Anderson, D Gregg IEEE Access 9, 120110-120126, 2021 | 9 | 2021 |
| Composition of Saliency Metrics for Pruning with a Myopic Oracle K Persand, A Anderson, D Gregg 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 753-759, 2020 | 9 | 2020 |
| POSTER: Space and Time Optimal DNN Primitive Selection with Integer Linear Programming Y Wen, A Anderson, V Radu, MFP O’Boyle, D Gregg 2019 28th International Conference on Parallel Architectures and Compilation …, 2019 | 3 | 2019 |
| Hardware and software performance in deep learning A Anderson, J Garland, J Yuan Wen, B Barabasz, K Persand, ... | 3 | 2019 |
| Scalar Arithmetic Multiple Data: Customizable Precision for Deep Neural Networks A Anderson, M Doyle, D Gregg 2019 IEEE 26th Symposium on Computer Arithmetic (ARITH), 61-68, 2019 | 2 | 2019 |
| Bonseyes AI Pipeline—Bringing AI to you M DE PRADO, J SU, R SAEED, K LORENZO, N VALLEZ, A ANDERSON, ... End-to-end integration of data, algorithms and deployment tools, arxiv. org …, 2019 | 1 | 2019 |
| Improving the Accuracy of Winograd Convolution for Deep Neural Networks B BARABASZ, A ANDERSON, D GREGG arXiv preprint arXiv:1803.10986, 2018 | 1 | 2018 |
| Vectorization for Accelerated Gather/Scatter and Multibyte Data Formats A Anderson Trinity College Dublin, 2016 | 1 | 2016 |
David GreggProfessor in Computer Science, Lero, Trinity College DublinDirección de correo verificada de cs.tcd.ie
