Communication quantization for data-parallel training of deep neural networks N Dryden, SA Jacobs, T Moon, B Van Essen Proceedings of the Workshop on Machine Learning in High Performance …, 2016 | 249 | 2016 |
Accelerating a random forest classifier: Multi-core, GP-GPU, or FPGA? B Van Essen, C Macaraeg, M Gokhale, R Prenger Field-Programmable Custom Computing Machines (FCCM), 2012 IEEE 20th Annual …, 2012 | 227 | 2012 |
SPR: an architecture-adaptive CGRA mapping tool S Friedman, A Carroll, B Van Essen, B Ylvisaker, C Ebeling, S Hauck Proceedings of the ACM/SIGDA international symposium on Field programmable …, 2009 | 160 | 2009 |
Truenorth ecosystem for brain-inspired computing: scalable systems, software, and applications J Sawada, F Akopyan, AS Cassidy, B Taba, MV Debole, P Datta, ... High Performance Computing, Networking, Storage and Analysis, SC16 …, 2016 | 109 | 2016 |
TrueNorth Ecosystem for Brain-Inspired Computing: Scalable Systems, Software, and Applications BC Van Essen, EX Wang, DP Widemann, Q Wu, WE Murphy, ... | 109* | 2016 |
LBANN: Livermore big artificial neural network HPC toolkit B Van Essen, H Kim, R Pearce, K Boakye, B Chen Proceedings of the Workshop on Machine Learning in High-Performance …, 2015 | 101 | 2015 |
DI-MMAP—a scalable memory-map runtime for out-of-core data-intensive applications B Van Essen, H Hsieh, S Ames, R Pearce, M Gokhale Cluster Computing 18 (1), 15-28, 2015 | 73 | 2015 |
On the role of NVRAM in data-intensive architectures: an evaluation B Van Essen, R Pearce, S Ames, M Gokhale Parallel & Distributed Processing Symposium (IPDPS), 2012 IEEE 26th …, 2012 | 64 | 2012 |
Quadratic Unconstrained Binary Optimization (QUBO) on neuromorphic computing system MZ Alom, B Van Essen, AT Moody, DP Widemann, TM Taha Neural Networks (IJCNN), 2017 International Joint Conference on, 3922-3929, 2017 | 47 | 2017 |
Large-scale deep learning on the YFCC100M dataset K Ni, R Pearce, K Boakye, B Van Essen, D Borth, B Chen, E Wang arXiv preprint arXiv:1502.03409, 2015 | 40 | 2015 |
Method of securing programmable logic configuration data BC Van Essen, JW Kidd, CM Petersen, HH Schmit US Patent 7,197,647, 2007 | 40 | 2007 |
DI-MMAP: A high performance memory-map runtime for data-intensive applications B Van Essen, H Hsieh, S Ames, M Gokhale High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC …, 2012 | 37 | 2012 |
Method of securing programmable logic configuration data BC Van Essen, JW Kidd, CM Petersen, HH Schmit US Patent 7,711,964, 2010 | 33 | 2010 |
Designing a coarse-grained reconfigurable architecture for power efficiency A Carroll, S Friedman, B Van Essen, A Wood, B Ylvisaker, C Ebeling, ... Department of Energy NA-22 University Information Technical Interchange …, 2007 | 33 | 2007 |
Towards a distributed large-scale dynamic graph data store K Iwabuchi, S Sallinen, R Pearce, B Van Essen, M Gokhale, S Matsuoka Parallel and Distributed Processing Symposium Workshops, 2016 IEEE …, 2016 | 32 | 2016 |
Static versus scheduled interconnect in coarse-grained reconfigurable arrays B Van Essen, A Wood, A Carroll, S Friedman, R Panda, B Ylvisaker, ... Field Programmable Logic and Applications, 2009. FPL 2009. International …, 2009 | 32 | 2009 |
Integrated in-system storage architecture for high performance computing D Kimpe, K Mohror, A Moody, B Van Essen, M Gokhale, R Ross, ... Proceedings of the 2nd International Workshop on Runtime and Operating …, 2012 | 31 | 2012 |
A container-based approach to OS specialization for exascale computing JA Zounmevo, S Perarnau, K Iskra, K Yoshii, R Gioiosa, BC Van Essen, ... Cloud Engineering (IC2E), 2015 IEEE International Conference on, 359-364, 2015 | 25 | 2015 |
A Spike-Based Long Short-Term Memory on a Neurosynaptic Processor A Shrestha, K Ahmed, Y Wang, DP Widemann, AT Moody, BC Van Essen, ... | 24* | |
Towards Scalable Parallel Training of Deep Neural Networks SA Jacobs, N Dryden, R Pearce, B Van Essen Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2017 | 20 | 2017 |