| Dark silicon and the end of multicore scaling H Esmaeilzadeh, E Blem, R St. Amant, K Sankaralingam, D Burger Proceedings of the 38th annual international symposium on Computer …, 2011 | 2572 | 2011 |
| A reconfigurable fabric for accelerating large-scale datacenter services A Putnam, AM Caulfield, ES Chung, D Chiou, K Constantinides, J Demme, ... ACM SIGARCH Computer Architecture News 42 (3), 13-24, 2014 | 1554 | 2014 |
| Neural acceleration for general-purpose approximate programs H Esmaeilzadeh, A Sampson, L Ceze, D Burger 2012 45th annual IEEE/ACM international symposium on microarchitecture, 449-460, 2012 | 871 | 2012 |
| From high-level deep neural models to FPGAs H Sharma, J Park, D Mahajan, E Amaro, JK Kim, C Shao, A Mishra, ... 2016 49th Annual IEEE/ACM International Symposium on Microarchitecture …, 2016 | 640 | 2016 |
| Bit fusion: Bit-level dynamically composable architecture for accelerating deep neural network H Sharma, J Park, N Suda, L Lai, B Chau, JK Kim, V Chandra, ... 2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture …, 2018 | 612 | 2018 |
| Architecture support for disciplined approximate programming H Esmaeilzadeh, A Sampson, L Ceze, D Burger Proceedings of the seventeenth international conference on Architectural …, 2012 | 597 | 2012 |
| Dark silicon and the end of multicore scaling H Esmaeilzadeh, E Blem, RS Amant, K Sankaralingam, D Burger IEEE micro 32 (3), 122-134, 2012 | 388 | 2012 |
| AxBench: A multiplatform benchmark suite for approximate computing A Yazdanbakhsh, D Mahajan, H Esmaeilzadeh, P Lotfi-Kamran IEEE Design & Test 34 (2), 60-68, 2016 | 274 | 2016 |
| General-purpose code acceleration with limited-precision analog computation R St. Amant, A Yazdanbakhsh, J Park, B Thwaites, H Esmaeilzadeh, ... ACM SIGARCH Computer Architecture News 42 (3), 505-516, 2014 | 239 | 2014 |
| Power challenges may end the multicore era H Esmaeilzadeh, E Blem, RS Amant, K Sankaralingam, D Burger Communications of the ACM 56 (2), 93-102, 2013 | 228 | 2013 |
| Tabla: A unified template-based framework for accelerating statistical machine learning D Mahajan, J Park, E Amaro, H Sharma, A Yazdanbakhsh, JK Kim, ... 2016 IEEE International Symposium on High Performance Computer Architecture …, 2016 | 214 | 2016 |
| Snapea: Predictive early activation for reducing computation in deep convolutional neural networks V Akhlaghi, A Yazdanbakhsh, K Samadi, RK Gupta, H Esmaeilzadeh 2018 ACM/IEEE 45th Annual International Symposium on Computer Architecture …, 2018 | 196 | 2018 |
| SNNAP: Approximate computing on programmable SoCs via neural acceleration T Moreau, M Wyse, J Nelson, A Sampson, H Esmaeilzadeh, L Ceze, ... 2015 IEEE 21st International Symposium on High Performance Computer …, 2015 | 186 | 2015 |
| A reconfigurable fabric for accelerating large-scale datacenter services A Putnam, AM Caulfield, ES Chung, D Chiou, K Constantinides, J Demme, ... IEEE Micro 35 (3), 10-22, 2015 | 171 | 2015 |
| Privacy in deep learning: A survey F Mireshghallah, M Taram, P Vepakomma, A Singh, R Raskar, ... arXiv preprint arXiv:2004.12254, 2020 | 168 | 2020 |
| Neural acceleration for GPU throughput processors A Yazdanbakhsh, J Park, H Sharma, P Lotfi-Kamran, H Esmaeilzadeh Proceedings of the 48th international symposium on microarchitecture, 482-493, 2015 | 136 | 2015 |
| Planaria: Dynamic architecture fission for spatial multi-tenant acceleration of deep neural networks S Ghodrati, BH Ahn, JK Kim, S Kinzer, BR Yatham, N Alla, H Sharma, ... 2020 53rd Annual IEEE/ACM International Symposium on Microarchitecture …, 2020 | 120 | 2020 |
| Ganax: A unified mimd-simd acceleration for generative adversarial networks A Yazdanbakhsh, H Falahati, PJ Wolfe, H Esmaeilzadeh, K Samadi 2018 ACM/IEEE 45th annual international symposium on computer architecture …, 2018 | 115 | 2018 |
| Looking back on the language and hardware revolutions: measured power, performance, and scaling H Esmaeilzadeh, T Cao, Y Xi, SM Blackburn, KS McKinley ACM SIGARCH Computer Architecture News 39 (1), 319-332, 2011 | 114 | 2011 |
| Shredder: Learning noise distributions to protect inference privacy F Mireshghallah, M Taram, P Ramrakhyani, A Jalali, D Tullsen, ... Proceedings of the Twenty-Fifth International Conference on Architectural …, 2020 | 102 | 2020 |
Doug BurgerCorporate VP, Managing Director, Microsoft Research CoreVerified email at microsoft.com
