Matthew Mattina

Most-cited papers

Federated Learning Based on Dynamic Regularization
D. A. E. Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina +2 more
2021International Conference on Learning Representations1,297 citations
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Processor: A 64-Core SoC with Mesh Interconnect
S. Bell, B. Edwards, J. Amann, R. Conlin +17 more
2010503 citations
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A Systematic Methodology for Characterizing Scalability of DNN Accelerators using SCALE-Sim
A. Samajdar, J. Joseph, Yuhao Zhu, P. Whatmough +2 more
2020IEEE International Symposium on Performance Analysis of Systems and Software265 citations
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SpArSe: Sparse Architecture Search for CNNs on Resource-Constrained Microcontrollers
Igor Fedorov, Ryan P. Adams, Matthew Mattina, P. Whatmough
2019Neural Information Processing Systems181 citations
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TinyLSTMs: Efficient Neural Speech Enhancement for Hearing Aids
Igor Fedorov, Marko Stamenovic, Carl R. Jensen, Li-Chia Yang +4 more
2020Interspeech139 citations Open access
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SCALE-Sim: Systolic CNN Accelerator
A. Samajdar, Yuhao Zhu, P. Whatmough, Matthew Mattina +1 more
2018arXiv.org138 citations
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Last level cache (LLC) performance of data mining workloads on a CMP - a case study of parallel bioinformatics workloads
A. Jaleel, Matthew Mattina, Bruce Jacob
2006The Twelfth International Symposium on High-Performance Computer Architecture, 2006.137 citations Open access
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S2TA: Exploiting Structured Sparsity for Energy-Efficient Mobile CNN Acceleration
Zhi-gang Liu, P. Whatmough, Yu-Hao Zhu, Matthew Mattina
2021International Symposium on High-Performance Computer Architecture122 citations Open access
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Tarantula: a vector extension to the alpha architecture
R. Espasa, Federico Ardanaz, J. Emer, S. Felix +7 more
2002Proceedings 29th Annual International Symposium on Computer Architecture104 citations
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Systolic Tensor Array: An Efficient Structured-Sparse GEMM Accelerator for Mobile CNN Inference
Zhi-gang Liu, P. Whatmough, Matthew Mattina
2020IEEE computer architecture letters102 citations Open access
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Euphrates: Algorithm-SoC Co-Design for Low-Power Mobile Continuous Vision
Yuhao Zhu, A. Samajdar, Matthew Mattina, P. Whatmough
2018International Symposium on Computer Architecture101 citations Open access
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Debiasing Model Updates for Improving Personalized Federated Training
D. A. E. Acar, Yue Zhao, Ruizhao Zhu, Ramon Matas Navarro +3 more
2021International Conference on Machine Learning81 citations
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FixyNN: Efficient Hardware for Mobile Computer Vision via Transfer Learning
P. Whatmough, Chuteng Zhou, Patrick Hansen, S. K. Venkataramanaiah +2 more
2019arXiv.org67 citations
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Searching for Winograd-aware Quantized Networks
Javier Fernandez-marques, P. Whatmough, Andrew Mundy, Matthew Mattina
2020Conference on Machine Learning and Systems43 citations
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Learning low-precision neural networks without Straight-Through Estimator(STE)
Z. G. Liu, Matthew Mattina
2019International Joint Conference on Artificial Intelligence43 citations Open access
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Noisy Machines: Understanding Noisy Neural Networks and Enhancing Robustness to Analog Hardware Errors Using Distillation
Chuteng Zhou, Prad Kadambi, Matthew Mattina, P. Whatmough
2020arXiv.org40 citations
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Compressing RNNs for IoT devices by 15-38x using Kronecker Products
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Chu Zhou +3 more
2019arXiv.org36 citations
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Efficient Winograd or Cook-Toom Convolution Kernel Implementation on Widely Used Mobile CPUs
Partha P. Maji, Andrew Mundy, Ganesh S. Dasika, Jesse G. Beu +2 more
20192019 2nd Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2)28 citations Open access
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Ternary Hybrid Neural-Tree Networks for Highly Constrained IoT Applications
Dibakar Gope, Ganesh S. Dasika, Matthew Mattina
2019USENIX workshop on Tackling computer systems problems with machine learning techniques28 citations
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Mobile Machine Learning Hardware at ARM: A Systems-on-Chip (SoC) Perspective
Yuhao Zhu, Matthew Mattina, P. Whatmough
2018arXiv.org24 citations
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ISP4ML: The Role of Image Signal Processing in Efficient Deep Learning Vision Systems
Patrick Hansen, Alexey Vilkin, Yury Krustalev, J. Imber +4 more
2021International Conference on Pattern Recognition21 citations
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Run-Time Efficient RNN Compression for Inference on Edge Devices
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh S. Dasika +1 more
20192019 2nd Workshop on Energy Efficient Machine Learning and Cognitive Computing for Embedded Applications (EMC2)21 citations Open access
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UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units
Igor Fedorov, Ramon Matas, Hokchhay Tann, Chu Zhou +2 more
2022Neural Information Processing Systems19 citations
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Towards Efficient Point Cloud Graph Neural Networks Through Architectural Simplification
Shyam A. Tailor, Re-Ne Jong, Tiago Azevedo, Matthew Mattina +1 more
20212021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)17 citations Open access
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Ternary MobileNets via Per-Layer Hybrid Filter Banks
Dibakar Gope, Jesse G. Beu, Urmish Thakker, Matthew Mattina
20192020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)16 citations Open access
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Sparse Systolic Tensor Array for Efficient CNN Hardware Acceleration
Zhi-gang Liu, P. Whatmough, Matthew Mattina
2020arXiv.org15 citations
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On the Effects of Quantisation on Model Uncertainty in Bayesian Neural Networks
Martin Ferianc, Partha P. Maji, Matthew Mattina, Miguel L. Rodrigues
2021Conference on Uncertainty in Artificial Intelligence14 citations
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Efficient Residue Number System Based Winograd Convolution
Zhi-gang Liu, Matthew Mattina
2020European Conference on Computer Vision14 citations Open access
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Measuring scheduling efficiency of RNNs for NLP applications
Urmish Thakker, Ganesh S. Dasika, Jesse G. Beu, Matthew Mattina
2019arXiv.org14 citations
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Rank and run-time aware compression of NLP Applications
Urmish Thakker, Jesse G. Beu, Dibakar Gope, Ganesh S. Dasika +1 more
2020SUSTAINLP13 citations Open access
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Pushing the limits of RNN Compression
Urmish Thakker, Igor Fedorov, Jesse G. Beu, Dibakar Gope +3 more
20192019 Fifth Workshop on Energy Efficient Machine Learning and Cognitive Computing - NeurIPS Edition (EMC2-NIPS)13 citations Open access
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Compressing Language Models using Doped Kronecker Products
Urmish Thakker, Paul N. Whatmough, Matthew Mattina, Jesse G. Beu
2020arXiv.org10 citations
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ISP4ML: Understanding the Role of Image Signal Processing in Efficient Deep Learning Vision Systems
Patrick Hansen, Alexey Vilkin, Yu. V. Khrustalev, J. Imber +3 more
2019arXiv.org10 citations
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Compressing RNNs to Kilobyte Budget for IoT Devices Using Kronecker Products
Urmish Thakker, Igor Fedorov, Chu Zhou, Dibakar Gope +3 more
2021ACM Journal on Emerging Technologies in Computing Systems9 citations
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FixyNN: Energy-Efficient Real-Time Mobile Computer Vision Hardware Acceleration via Transfer Learning
P. Whatmough, Chuteng Zhou, Patrick Hansen, S. K. Venkataramanaiah +2 more
2019USENIX workshop on Tackling computer systems problems with machine learning techniques9 citations
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Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices
Urmish Thakker, P. Whatmough, Zhi-gang Liu, Matthew Mattina +1 more
2021Conference on Machine Learning and Systems8 citations
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High Throughput Matrix-Matrix Multiplication between Asymmetric Bit-Width Operands
Dibakar Gope, Jesse G. Beu, Matthew Mattina
2020arXiv.org8 citations
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Information contraction in noisy binary neural networks and its implications
Chuteng Zhou, Quntao Zhuang, Matthew Mattina, P. Whatmough
2021arXiv.org4 citations
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Strong data processing inequality in neural networks with noisy neurons and its implications
Chuteng Zhou, Quntao Zhuang, Matthew Mattina, P. Whatmough
2021International Symposium on Information Theory4 citations
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Networks of the Tilera Multicore Processor
David Wentzlaff, Patrick Griffin, Henry Hoffman, Lie-Wei Bao +6 more
20102 citations
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Co-Designing Hardware and Models for Efficient On-Device ML Inference
Matthew Mattina
2021International Symposium on Low Power Electronics and Design1 citations
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Energy Efficient Hardware for On-Device CNN Inference via Transfer Learning
P. Whatmough, Chuteng Zhou, Patrick Hansen, Matthew Mattina
2018arXiv.org1 citations
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Efficient and Robust Machine Learning for Real-World Systems
Franz Pernkopf, Wolfgang Roth, M. Zöhrer, Lukas Pfeifenberger +6 more
2018arXiv.org1 citations
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Maia 200: A Software Defined Dataflow System for Large-scale AI Acceleration
Sherry Xu, M. Heddes, Jackson Peng, Tom Savell +13 more
20260 citations
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Algorithm-SoC Co-Design for Energy-Efficient Continuous Vision ∗
Yuhao Zhu, A. Samajdar, Matthew Mattina, P. Whatmough
20190 citations
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Vorrichtung und Verfahren zur Partitionierung eines gemeinsamen Cachespeichers eines Chip-Multiprozessors
Matthew Mattina, Antonio Juan-Hormigo, Joel Emer, Ramón Matas-Navarro
20050 citations
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Dispositif et procédé de partitionnement d'une antémémoire partagée d'un multiprocesseur à puce
Matthew Mattina, Antonio Juan-Hormigo, J. Emer, Ramón Matas-Navarro
20050 citations
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Neural Networks For Embedded Control Designs Applied To The “Smarter Car”
M. Embrechts, M. Luetzelschwab, F. DiCesare, Matthew Mattina
19960 citations
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