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Michaela Blott

EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators



Lois Orosa , Skanda Koppula , Yaman Umuroglu , Konstantinos Kanellopoulos , Juan Gomez-Luna , Michaela Blott , Kees Vissers , Onur Mutlu


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Applications and Techniques for Fast Machine Learning in Science



Allison McCarn Deiana , Nhan Tran , Joshua Agar , Michaela Blott , Giuseppe Di Guglielmo , Javier Duarte , Philip Harris , Scott Hauck , Mia Liu , Mark S. Neubauer , Jennifer Ngadiuba , Seda Ogrenci-Memik , Maurizio Pierini , Thea Aarrestad , Steffen Bahr , Jurgen Becker , Anne-Sophie Berthold , Richard J. Bonventre , Tomas E. Muller Bravo , Markus Diefenthaler , Zhen Dong , Nick Fritzsche , Amir Gholami , Ekaterina Govorkova , Kyle J Hazelwood , Christian Herwig , Babar Khan , Sehoon Kim , Thomas Klijnsma , Yaling Liu , Kin Ho Lo , Tri Nguyen , Gianantonio Pezzullo , Seyedramin Rasoulinezhad , Ryan A. Rivera , Kate Scholberg , Justin Selig , Sougata Sen , Dmitri Strukov , William Tang , Savannah Thais , Kai Lukas Unger , Ricardo Vilalta , Belinavon Krosigk , Thomas K. Warburton , Maria Acosta Flechas , Anthony Aportela , Thomas Calvet , Leonardo Cristella , Daniel Diaz , Caterina Doglioni , Maria Domenica Galati , Elham E Khoda , Farah Fahim , Davide Giri , Benjamin Hawks , Duc Hoang , Burt Holzman , Shih-Chieh Hsu , Sergo Jindariani , Iris Johnson , Raghav Kansal , Ryan Kastner , Erik Katsavounidis , Jeffrey Krupa , Pan Li , Sandeep Madireddy , Ethan Marx , Patrick McCormack , Andres Meza , Jovan Mitrevski , Mohammed Attia Mohammed , Farouk Mokhtar , Eric Moreno , Srishti Nagu , Rohin Narayan , Noah Palladino , Zhiqiang Que , Sang Eon Park , Subramanian Ramamoorthy , Dylan Rankin , Simon Rothman , Ashish Sharma , Sioni Summers , Pietro Vischia , Jean-Roch Vlimant , Olivia Weng

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* 66 pages, 13 figures, 5 tables 
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FAT: Training Neural Networks for Reliable Inference Under Hardware Faults



Ussama Zahid , Giulio Gambardella , Nicholas J. Fraser , Michaela Blott , Kees Vissers

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LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications



Yaman Umuroglu , Yash Akhauri , Nicholas J. Fraser , Michaela Blott

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Evolutionary Bin Packing for Memory-Efficient Dataflow Inference Acceleration on FPGA



Mairin Kroes , Lucian Petrica , Sorin Cotofana , Michaela Blott

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* To appear in GECCO 2020 Proceedings 
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Efficient Error-Tolerant Quantized Neural Network Accelerators



Giulio Gambardella , Johannes Kappauf , Michaela Blott , Christoph Doehring , Martin Kumm , Peter Zipf , Kees Vissers

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* 2019 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFT) 
 * 6 pages, 5 figures 
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Synetgy: Algorithm-hardware Co-design for ConvNet Accelerators on Embedded FPGAs



Yifan Yang , Qijing Huang , Bichen Wu , Tianjun Zhang , Liang Ma , Giulio Gambardella , Michaela Blott , Luciano Lavagno , Kees Vissers , John Wawrzynek , Kurt Keutzer

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* To appear in the 27th International Symposium on Field-Programmable Gate Arrays, February 2019 
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Accuracy to Throughput Trade-offs for Reduced Precision Neural Networks on Reconfigurable Logic



Jiang Su , Nicholas J. Fraser , Giulio Gambardella , Michaela Blott , Gianluca Durelli , David B. Thomas , Philip Leong , Peter Y. K. Cheung

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* Accepted by ARC 2018 
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FINN-L: Library Extensions and Design Trade-off Analysis for Variable Precision LSTM Networks on FPGAs



Vladimir Rybalkin , Alessandro Pappalardo , Muhammad Mohsin Ghaffar , Giulio Gambardella , Norbert Wehn , Michaela Blott

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* Accepted for publication, 28th International Conference on Field Programmable Logic and Applications (FPL), August, 2018, Dublin, Ireland 
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SYQ: Learning Symmetric Quantization For Efficient Deep Neural Networks



Julian Faraone , Nicholas Fraser , Michaela Blott , Philip H. W. Leong

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* Published as a conference paper at the 2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 
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