Deep speech 2: End-to-end speech recognition in english and mandarin D Amodei, S Ananthanarayanan, R Anubhai, J Bai, E Battenberg, C Case, ... International conference on machine learning, 173-182, 2016 | 1878 | 2016 |
Deep speech: Scaling up end-to-end speech recognition A Hannun, C Case, J Casper, B Catanzaro, G Diamos, E Elsen, ... arXiv preprint arXiv:1412.5567, 2014 | 1325 | 2014 |
Parallel prefix sum (scan) with CUDA M Harris, S Sengupta, JD Owens GPU gems 3 (39), 851-876, 2007 | 926 | 2007 |
Scan primitives for GPU computing S Sengupta, M Harris, Y Zhang, JD Owens | 775 | 2007 |
Fast BVH construction on GPUs C Lauterbach, M Garland, S Sengupta, D Luebke, D Manocha Computer Graphics Forum 28 (2), 375-384, 2009 | 497 | 2009 |
Deep voice: Real-time neural text-to-speech SÖ Arık, M Chrzanowski, A Coates, G Diamos, A Gibiansky, Y Kang, X Li, ... International Conference on Machine Learning, 195-204, 2017 | 363 | 2017 |
Glift: Generic, efficient, random-access GPU data structures AE Lefohn, S Sengupta, J Kniss, R Strzodka, JD Owens ACM Transactions on Graphics (TOG) 25 (1), 60-99, 2006 | 221 | 2006 |
Real-time parallel hashing on the GPU DA Alcantara, A Sharf, F Abbasinejad, S Sengupta, M Mitzenmacher, ... ACM SIGGRAPH Asia 2009 papers, 1-9, 2009 | 219 | 2009 |
Navigating the maze of graph analytics frameworks using massive graph datasets N Satish, N Sundaram, MMA Patwary, J Seo, J Park, MA Hassaan, ... Proceedings of the 2014 ACM SIGMOD international conference on Management of …, 2014 | 205* | 2014 |
Efficient parallel scan algorithms for GPUs S Sengupta, M Harris, M Garland NVIDIA, Santa Clara, CA, Tech. Rep. NVR-2008-003 1 (1), 1-17, 2008 | 180 | 2008 |
Exploring sparsity in recurrent neural networks S Narang, E Elsen, G Diamos, S Sengupta arXiv preprint arXiv:1704.05119, 2017 | 167 | 2017 |
A work-efficient step-efficient prefix sum algorithm S Sengupta, A Lefohn, JD Owens | 110 | 2006 |
Resolution-matched shadow maps AE Lefohn, S Sengupta, JD Owens ACM Transactions on Graphics (TOG) 26 (4), 20-es, 2007 | 91 | 2007 |
Scientific computing with multicore and accelerators J Kurzak, DA Bader, J Dongarra CRC Press, 2010 | 78 | 2010 |
Persistent rnns: Stashing recurrent weights on-chip G Diamos, S Sengupta, B Catanzaro, M Chrzanowski, A Coates, E Elsen, ... International Conference on Machine Learning, 2024-2033, 2016 | 68 | 2016 |
Out‐of‐core data management for path tracing on hybrid resources B Budge, T Bernardin, JA Stuart, S Sengupta, KI Joy, JD Owens Computer Graphics Forum 28 (2), 385-396, 2009 | 63 | 2009 |
CUDPP: CUDA data parallel primitives library M Harris, J Owens, S Sengupta, Y Zhang, A Davidson 2011 08 06)[2012 07 20]. http:∥ gpgpu. org/developer/cudpp, 2007 | 60 | 2007 |
Building an efficient hash table on the GPU DA Alcantara, V Volkov, S Sengupta, M Mitzenmacher, JD Owens, ... GPU Computing Gems Jade Edition, 39-53, 2012 | 48 | 2012 |
Efficient Parallel Scan Algorithms for Manycore GPUs. S Sengupta, MJ Harris, M Garland, JD Owens Scientific Computing with Multicore and Accelerators, 413-442, 2010 | 47 | 2010 |
GPU Gems3 M Harris Parallel Prefix sum (scan) with CUDA, 2007 | 39 | 2007 |