| In-datacenter performance analysis of a tensor processing unit NP Jouppi, C Young, N Patil, D Patterson, G Agrawal, R Bajwa, S Bates, ... Proceedings of the 44th Annual International Symposium on Computer …, 2017 | 6154 | 2017 |
| Memory consistency and event ordering in scalable shared-memory multiprocessors K Gharachorloo, D Lenoski, J Laudon, P Gibbons, A Gupta, J Hennessy ACM SIGARCH Computer Architecture News 18 (2SI), 15-26, 1990 | 1840 | 1990 |
| The stanford dash multiprocessor D Lenoski, J Laudon, K Gharachorloo, WD Weber, A Gupta, J Hennessy, ... Computer 25 (3), 63-79, 1992 | 1506 | 1992 |
| The SGI Origin: a ccNUMA highly scalable server J Laudon, D Lenoski ACM SIGARCH Computer Architecture News 25 (2), 241-251, 1997 | 1244 | 1997 |
| The directory-based cache coherence protocol for the DASH multiprocessor D Lenoski, J Laudon, K Gharachorloo, A Gupta, J Hennessy ACM SIGARCH Computer Architecture News 18 (2SI), 148-159, 1990 | 1005 | 1990 |
| A graph placement methodology for fast chip design A Mirhoseini, A Goldie, M Yazgan, JW Jiang, E Songhori, S Wang, YJ Lee, ... Nature 594 (7862), 207-212, 2021 | 717 | 2021 |
| Fair queuing memory systems KJ Nesbit, N Aggarwal, J Laudon, JE Smith 2006 39th Annual IEEE/ACM International Symposium on Microarchitecture …, 2006 | 481 | 2006 |
| Ten Lessons From Three Generations Shaped Google’s TPUv4i: Industrial Product NP Jouppi, DH Yoon, M Ashcraft, M Gottscho, TB Jablin, G Kurian, ... 2021 ACM/IEEE 48th Annual International Symposium on Computer Architecture …, 2021 | 434 | 2021 |
| A domain-specific supercomputer for training deep neural networks NP Jouppi, DH Yoon, G Kurian, S Li, N Patil, J Laudon, C Young, ... Communications of the ACM 63 (7), 67-78, 2020 | 347 | 2020 |
| Mixture-of-experts with expert choice routing Y Zhou, T Lei, H Liu, N Du, Y Huang, V Zhao, AM Dai, QV Le, J Laudon Advances in Neural Information Processing Systems 35, 7103-7114, 2022 | 332 | 2022 |
| The DASH prototype: Implementation and performance D Lenoski, J Laudon, T Joe, D Nakahira, L Stevens, A Gupta, J Hennessy ACM SIGARCH Computer Architecture News 20 (2), 92-103, 1992 | 277 | 1992 |
| The DASH prototype: Logic overhead and performance D Lenoski, J Laudon, T Joe, D Nakahira, L Stevens, A Gupta, J Hennessy IEEE Transactions on Parallel and Distributed Systems 4 (1), 41-61, 1993 | 276 | 1993 |
| Chip Placement with Deep Reinforcement Learning A Mirhoseini, A Goldie, M Yazgan, J Jiang, E Songhori, S Wang, YJ Lee, ... arXiv preprint arXiv:2004.10746, 2020 | 268 | 2020 |
| Virtual private caches KJ Nesbit, J Laudon, JE Smith Proceedings of the 34th annual international symposium on Computer …, 2007 | 227 | 2007 |
| Apparatus and method for profiling system events in a fine grain multi-threaded multi-core processor N Kosche, JP Laudon, AR Talcott, S Patel, F Sajjadian US Patent 8,762,951, 2014 | 173 | 2014 |
| Interleaving: A multithreading technique targeting multiprocessors and workstations J Laudon, A Gupta, M Horowitz ACM SIGPLAN Notices 29 (11), 308-318, 1994 | 172 | 1994 |
| Maximizing CMP throughput with mediocre cores JD Davis, J Laudon, K Olukotun 14th International Conference on Parallel Architectures and Compilation …, 2005 | 165 | 2005 |
| Chip multiprocessor architecture: techniques to improve throughput and latency OA Olukotun, L Hammond, JP Laudon Morgan & Claypool Publishers, 2007 | 163 | 2007 |
| The ZS-1 central processor JE Smith, GE Dermer, BD Vanderwarn, SD Klinger, CM Rozewski, ... ACM SIGARCH Computer Architecture News 15 (5), 199-204, 1987 | 150 | 1987 |
| The design process for Google's training chips: TPUv2 and TPUv3 T Norrie, N Patil, DH Yoon, G Kurian, S Li, J Laudon, C Young, N Jouppi, ... IEEE Micro 41 (2), 56-63, 2021 | 149 | 2021 |
Dan LenoskiGoogle在 google.com 的电子邮件经过验证
