Debbie Marr

According to our database, Debbie Marr authored at least 22 papers between 2015 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

SE1: What Technologies Will Shape the Future of Computing?

Hugh Mair, Shinichiro Shiratake, Eric Karl, Thomas Burd, Jonathan Chang, Debbie Marr, Samuel Naffziger, Henk Corporaal, Ken Takeuchi, Naresh R. Shanbhag

Proceedings of the IEEE International Solid-State Circuits Conference, 2021

2019

Evaluating and Enhancing Intel® Stratix® 10 FPGAs for Persistent Real-Time AI.

Eriko Nurvitadhi, Dongup Kwon, Ali Jafari, Andrew Boutros, Jaewoong Sim, Phillip Tomson, Huseyin Sumbul, Gregory K. Chen, Phil C. Knag, Raghavan Kumar, Ram Krishnamurthy, Debbie Marr, Sergey Gribok, Bogdan Pasca, Martin Langhammer, Aravind Dasu

Proceedings of the 2019 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2019

Why Compete When You Can Work Together: FPGA-ASIC Integration for Persistent RNNs.

Eriko Nurvitadhi, Dongup Kwon, Ali Jafari, Andrew Boutros, Jaewoong Sim, Phillip Tomson, Huseyin Sumbul, Gregory K. Chen, Phil C. Knag, Raghavan Kumar, Ram Krishnamurthy, Sergey Gribok, Bogdan Pasca, Martin Langhammer, Debbie Marr, Aravind Dasu

Proceedings of the 27th IEEE Annual International Symposium on Field-Programmable Custom Computing Machines, 2019

2018

Guest Editors' Introduction: Hardware Accelerators for Data Centers.

Mustafa Ozdal, Gi-Joon Nam, Debbie Marr

IEEE Des. Test, 2018

WRPN & Apprentice: Methods for Training and Inference using Low-Precision Numerics.

Asit K. Mishra, Debbie Marr

CoRR, 2018

WRPN: Wide Reduced-Precision Networks.

Asit K. Mishra, Eriko Nurvitadhi, Jeffrey J. Cook, Debbie Marr

Proceedings of the 6th International Conference on Learning Representations, 2018

Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy.

Asit K. Mishra, Debbie Marr

Proceedings of the 6th International Conference on Learning Representations, 2018

In-Package Domain-Specific ASICs for Intel® Stratix® 10 FPGAs: A Case Study of Accelerating Deep Learning Using TensorTile ASIC.

Eriko Nurvitadhi, Jeffrey J. Cook, Asit K. Mishra, Debbie Marr, Kevin Nealis, Philip Colangelo, Andrew C. Ling, Davor Capalija, Utku Aydonat, Aravind Dasu, Sergey Y. Shumarayev

Proceedings of the 28th International Conference on Field Programmable Logic and Applications, 2018

In-Package Domain-Specific ASICs for Intel® Stratix® 10 FPGAs: A Case Study of Accelerating Deep Learning Using TensorTile ASIC(Abstract Only).

Eriko Nurvitadhi, Jeffrey J. Cook, Asit K. Mishra, Debbie Marr, Kevin Nealis, Philip Colangelo, Andrew C. Ling, Davor Capalija, Utku Aydonat, Sergey Y. Shumarayev, Aravind Dasu

Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018

A Customizable Matrix Multiplication Framework for the Intel HARPv2 Xeon+FPGA Platform: A Deep Learning Case Study.

Duncan J. M. Moss, Krishnan Srivatsan, Eriko Nurvitadhi, Piotr Ratuszniak, Chris Johnson, Jaewoong Sim, Asit K. Mishra, Debbie Marr, Suchit Subhaschandra, Philip Heng Wai Leong

Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2018

2017

Low Precision RNNs: Quantizing RNNs Without Losing Accuracy.

Supriya Kapur, Asit K. Mishra, Debbie Marr

CoRR, 2017

WRPN: Training and Inference using Wide Reduced-Precision Networks.

Asit K. Mishra, Jeffrey J. Cook, Eriko Nurvitadhi, Debbie Marr

CoRR, 2017

Accelerating Deep Convolutional Networks using low-precision and sparsity.

Ganesh Venkatesh, Eriko Nurvitadhi, Debbie Marr

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Customizable FPGA OpenCL matrix multiply design template for deep neural networks.

Jack Yinger, Eriko Nurvitadhi, Davor Capalija, Andrew C. Ling, Debbie Marr, Krishnan Srivatsan, Duncan J. M. Moss, Suchit Subhaschandra

Proceedings of the International Conference on Field Programmable Technology, 2017

High performance binary neural networks on the Xeon+FPGA™ platform.

Duncan J. M. Moss, Eriko Nurvitadhi, Jaewoong Sim, Asit K. Mishra, Debbie Marr, Suchit Subhaschandra, Philip Heng Wai Leong

Proceedings of the 27th International Conference on Field Programmable Logic and Applications, 2017

Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?

Eriko Nurvitadhi, Ganesh Venkatesh, Jaewoong Sim, Debbie Marr, Randy Huang, Jason Ong Gee Hock, Yeong Tat Liew, Krishnan Srivatsan, Duncan J. M. Moss, Suchit Subhaschandra, Guy Boudoukh

Proceedings of the 2017 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, 2017

Fine-grained accelerators for sparse machine learning workloads.

Asit K. Mishra, Eriko Nurvitadhi, Ganesh Venkatesh, Jonathan Pearce, Debbie Marr

Proceedings of the 22nd Asia and South Pacific Design Automation Conference, 2017

2016

Efficient Execution of Bursty Applications.

Milad Hashemi, Debbie Marr, Doug Carmean, Yale N. Patt

IEEE Comput. Archit. Lett., 2016

Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC.

Eriko Nurvitadhi, David Sheffield, Jaewoong Sim, Asit K. Mishra, Ganesh Venkatesh, Debbie Marr

Proceedings of the 2016 International Conference on Field-Programmable Technology, 2016

Accelerating recurrent neural networks in analytics servers: Comparison of FPGA, CPU, GPU, and ASIC.

Eriko Nurvitadhi, Jaewoong Sim, David Sheffield, Asit K. Mishra, Krishnan Srivatsan, Debbie Marr

Proceedings of the 26th International Conference on Field Programmable Logic and Applications, 2016

Hardware accelerator for analytics of sparse data.

Eriko Nurvitadhi, Asit K. Mishra, Yu Wang, Ganesh Venkatesh, Debbie Marr

Proceedings of the 2016 Design, Automation & Test in Europe Conference & Exhibition, 2016

2015

A sparse matrix vector multiply accelerator for support vector machine.

Eriko Nurvitadhi, Asit K. Mishra, Debbie Marr

Proceedings of the 2015 International Conference on Compilers, 2015