| Masr: A modular accelerator for sparse rnns U Gupta, B Reagen, L Pentecost, M Donato, T Tambe, AM Rush, GY Wei, ... 2019 28th International Conference on Parallel Architectures and Compilation …, 2019 | 51 | 2019 |
| Edgebert: Sentence-level energy optimizations for latency-aware multi-task nlp inference T Tambe, C Hooper, L Pentecost, T Jia, EY Yang, M Donato, V Sanh, ... MICRO-54: 54th Annual IEEE/ACM International Symposium on Microarchitecture …, 2021 | 38 | 2021 |
| Algorithm-hardware co-design of adaptive floating-point encodings for resilient deep learning inference T Tambe, EY Yang, Z Wan, Y Deng, VJ Reddi, A Rush, D Brooks, GY Wei 2020 57th ACM/IEEE Design Automation Conference (DAC), 1-6, 2020 | 32 | 2020 |
| 9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence … T Tambe, EY Yang, GG Ko, Y Chai, C Hooper, M Donato, PN Whatmough, ... 2021 IEEE International Solid-State Circuits Conference (ISSCC) 64, 158-160, 2021 | 25 | 2021 |
| Adaptivfloat: A floating-point based data type for resilient deep learning inference T Tambe, EY Yang, Z Wan, Y Deng, VJ Reddi, A Rush, D Brooks, GY Wei arXiv preprint arXiv:1909.13271, 2019 | 22 | 2019 |
| Robomorphic computing: a design methodology for domain-specific accelerators parameterized by robot morphology SM Neuman, B Plancher, T Bourgeat, T Tambe, S Devadas, VJ Reddi Proceedings of the 26th ACM International Conference on Architectural …, 2021 | 14 | 2021 |
| A 3mm2 Programmable Bayesian Inference Accelerator for Unsupervised Machine Perception using Parallel Gibbs Sampling in 16nm GG Ko, Y Chai, M Donato, PN Whatmough, T Tambe, RA Rutenbar, ... 2020 IEEE Symposium on VLSI Circuits, 1-2, 2020 | 9 | 2020 |
| EdgeBERT: Optimizing On-chip inference for multi-task NLP T Tambe, C Hooper, L Pentecost, EY Yang, M Donato, V Sanh, AM Rush, ... arXiv preprint arXiv:2011.14203, 2020 | 7 | 2020 |
| Autosoc: Automating algorithm-soc co-design for aerial robots S Krishnan, T Tambe, Z Wan, VJ Reddi arXiv preprint arXiv:2109.05683, 2021 | 5 | 2021 |
| A scalable bayesian inference accelerator for unsupervised learning G Ko, Y Chai, M Donato, PN Whatmough, T Tambe, RA Rutenbar, GY Wei, ... 2020 IEEE Hot Chips 32 Symposium (HCS), 1-27, 2020 | 3 | 2020 |
| SM6: A 16nm System-on-Chip for Accurate and Noise-Robust Attention-Based NLP Applications : The 33rd Hot Chips Symposium – August 22-24, 2021 T Tambe, EY Yang, GG Ko, Y Chai, C Hooper, M Donato, PN Whatmough, ... 2021 IEEE Hot Chips 33 Symposium (HCS), 1-13, 2021 | 2 | 2021 |
| Study of posit numeric in speech recognition neural inference Z Wan, E Mibuari, EY Yang, T Tambe Harvard Univ., Cambridge, MA, USA, Tech. Rep. CS247r, 2018 | 2 | 2018 |
| ASAP: automatic synthesis of area-efficient and precision-aware CGRAs C Tan, T Tambe, J Zhang, B Fang, T Geng, GY Wei, D Brooks, A Tumeo, ... Proceedings of the 36th ACM International Conference on Supercomputing, 1-13, 2022 | 1 | 2022 |
| GoldenEye: A Platform for Evaluating Emerging Numerical Data Formats in DNN Accelerators A Mahmoud, T Tambe, T Aloui, D Brooks, GY Wei 2022 52nd Annual IEEE/IFIP International Conference on Dependable Systems …, 2022 | 1 | 2022 |
| Specialized Accelerators and Compiler Flows: Replacing Accelerator APIs with a Formal Software/Hardware Interface BY Huang, S Lyubomirsky, Y Li, M He, T Tambe, GH Smith, A Gaonkar, ... arXiv preprint arXiv:2203.00218, 2022 | 1 | 2022 |
| A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs T Tambe, EY Yang, GG Ko, Y Chai, C Hooper, M Donato, PN Whatmough, ... IEEE Journal of Solid-State Circuits, 2022 | | 2022 |
| Quantifying and Maximizing the Benefits of Back-End Noise Adaption on Attention-Based Speech Recognition Models C Hooper, T Tambe, GY Wei arXiv preprint arXiv:2105.01134, 2021 | | 2021 |
| Learnings from a HLS-based High-Productivity Digital VLSI Flow T Tambe, D Brooks, GY Wei | | 2021 |
| From DSLs to Accelerator-Rich Platform Implementations: Addressing the Mapping Gap BY Huang, S Lyubomirsky, T Tambe, Y Li, M He, G Smith, GY Wei, ... | | 2021 |
