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ORCIDYaman Umuroglu
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2020 – today
- 2024
[j8]Lois Orosa
, Skanda Koppula, Yaman Umuroglu, Konstantinos Kanellopoulos, Juan Gómez-Luna, Michaela Blott, Kees A. Vissers, Onur Mutlu:
EcoFlow: Efficient Convolutional Dataflows on Low-Power Neural Network Accelerators. IEEE Trans. Computers 73(9): 2275-2289 (2024)- [c12]Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig, Yaman Umuroglu:
A2Q+: Improving Accumulator-Aware Weight Quantization. ICML 2024 - [i13]Ian Colbert, Alessandro Pappalardo, Jakoba Petri-Koenig, Yaman Umuroglu:
A2Q+: Improving Accumulator-Aware Weight Quantization. CoRR abs/2401.10432 (2024) - 2022
- [j7]Felix Jentzsch, Yaman Umuroglu, Alessandro Pappalardo, Michaela Blott, Marco Platzner:
RadioML Meets FINN: Enabling Future RF Applications With FPGA Streaming Architectures. IEEE Micro 42(6): 125-133 (2022) - [j6]Tobias Alonso, Lucian Petrica, Mario Ruiz, Jakoba Petri-Koenig, Yaman Umuroglu, Ioannis Stamelos, Elias Koromilas, Michaela Blott, Kees A. Vissers:
Elastic-DF: Scaling Performance of DNN Inference in FPGA Clouds through Automatic Partitioning. ACM Trans. Reconfigurable Technol. Syst. 15(2): 15:1-15:34 (2022) - [i12]Lois Orosa, Skanda Koppula, Yaman Umuroglu, Konstantinos Kanellopoulos, Juan Gómez-Luna, Michaela Blott, Kees A. Vissers, Onur Mutlu:
EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators. CoRR abs/2202.02310 (2022) - [i11]Alessandro Pappalardo, Yaman Umuroglu, Michaela Blott, Jovan Mitrevski, Benjamin Hawks, Nhan Tran, Vladimir Loncar, Sioni Summers, Hendrik Borras, Jules Muhizi, Matthew Trahms, Shih-Chieh Hsu, Scott Hauck, Javier M. Duarte:
QONNX: Representing Arbitrary-Precision Quantized Neural Networks. CoRR abs/2206.07527 (2022) - [i10]Hendrik Borras, Giuseppe Di Guglielmo, Javier M. Duarte, Nicolò Ghielmetti, Benjamin Hawks, Scott Hauck, Shih-Chieh Hsu, Ryan Kastner, Jason Liang, Andres Meza, Jules Muhizi, Tai Nguyen, Rushil Roy, Nhan Tran, Yaman Umuroglu, Olivia Weng, Aidan Yokuda, Michaela Blott:
Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark. CoRR abs/2206.11791 (2022) - 2021
- [j5]Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu:
Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference. Frontiers Artif. Intell. 4: 676564 (2021) - [j4]Michaela Blott, Nicholas J. Fraser, Giulio Gambardella, Lisa Halder, Johannes Kath, Zachary Neveu, Yaman Umuroglu, Alina Vasilciuc, Miriam Leeser, Linda Doyle:
Evaluation of Optimized CNNs on Heterogeneous Accelerators Using a Novel Benchmarking Approach. IEEE Trans. Computers 70(10): 1654-1669 (2021) - [i9]Benjamin Hawks, Javier M. Duarte, Nicholas J. Fraser, Alessandro Pappalardo, Nhan Tran, Yaman Umuroglu:
Ps and Qs: Quantization-aware pruning for efficient low latency neural network inference. CoRR abs/2102.11289 (2021) - 2020
- [c11]Yaman Umuroglu, Yash Akhauri, Nicholas J. Fraser, Michaela Blott:
High-Throughput DNN Inference with LogicNets. FCCM 2020: 238 - [c10]Michaela Blott, Johannes Kath, Lisa Halder, Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Miriam Leeser, Linda Doyle:
Evaluation of Optimized CNNs on FPGA and non-FPGA based Accelerators using a Novel Benchmarking Approach. FPGA 2020: 317 - [c9]Yaman Umuroglu, Yash Akhauri, Nicholas James Fraser, Michaela Blott:
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications. FPL 2020: 291-297 - [i8]Yaman Umuroglu, Yash Akhauri, Nicholas J. Fraser, Michaela Blott:
LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications. CoRR abs/2004.03021 (2020)
2010 – 2019
- 2019
- [j3]Yaman Umuroglu, Davide Conficconi, Lahiru Rasnayake, Thomas B. Preußer, Magnus Själander:
Optimizing Bit-Serial Matrix Multiplication for Reconfigurable Computing. ACM Trans. Reconfigurable Technol. Syst. 12(3): 15:1-15:24 (2019) - [i7]Yaman Umuroglu, Davide Conficconi, Lahiru Rasnayake, Thomas B. Preußer, Magnus Själander:
Optimizing Bit-Serial Matrix Multiplication for Reconfigurable Computing. CoRR abs/1901.00370 (2019) - 2018
- [b1]Yaman Umuroglu:
Accelerating Sparse Linear Algebra and Deep Neural Networks on Reconfigurable Platforms. Norwegian University of Science and Technology, Trondheim, Norway, 2018 - [j2]Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu, Miriam Leeser, Kees A. Vissers:
FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks. ACM Trans. Reconfigurable Technol. Syst. 11(3): 16:1-16:23 (2018) - [c8]Yaman Umuroglu, Lahiru Rasnayake, Magnus Själander:
BISMO: A Scalable Bit-Serial Matrix Multiplication Overlay for Reconfigurable Computing. FPL 2018: 307-314 - [i6]Yaman Umuroglu, Lahiru Rasnayake, Magnus Själander:
BISMO: A Scalable Bit-Serial Matrix Multiplication Overlay for Reconfigurable Computing. CoRR abs/1806.08862 (2018) - [i5]Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu, Miriam Leeser:
Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic. CoRR abs/1807.03123 (2018) - [i4]Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu:
FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks. CoRR abs/1809.04570 (2018) - 2017
- [c7]Yaman Umuroglu, Magnus Jahre:
Towards efficient quantized neural network inference on mobile devices: work-in-progress. CASES 2017: 18:1-18:2 - [c6]Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers:
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference. FPGA 2017: 65-74 - [c5]Nicholas J. Fraser, Yaman Umuroglu, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers:
Scaling Binarized Neural Networks on Reconfigurable Logic. PARMA-DITAM@HiPEAC 2017: 25-30 - [c4]Michaela Blott, Thomas B. Preußer, Nicholas J. Fraser, Giulio Gambardella, Kenneth O'Brien, Yaman Umuroglu, Miriam Leeser:
Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic. ICCD 2017: 419-422 - [i3]Nicholas J. Fraser, Yaman Umuroglu, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers:
Scaling Binarized Neural Networks on Reconfigurable Logic. CoRR abs/1701.03400 (2017) - [i2]Yaman Umuroglu, Magnus Jahre:
Streamlined Deployment for Quantized Neural Networks. CoRR abs/1709.04060 (2017) - 2016
- [j1]Yaman Umuroglu, Magnus Jahre:
Random access schemes for efficient FPGA SpMV acceleration. Microprocess. Microsystems 47: 321-332 (2016) - [i1]Yaman Umuroglu, Nicholas J. Fraser, Giulio Gambardella, Michaela Blott, Philip Heng Wai Leong, Magnus Jahre, Kees A. Vissers:
FINN: A Framework for Fast, Scalable Binarized Neural Network Inference. CoRR abs/1612.07119 (2016) - 2015
- [c3]Yaman Umuroglu, Magnus Jahre:
A Vector Caching Scheme for Streaming FPGA SpMV Accelerators. ARC 2015: 15-26 - [c2]Yaman Umuroglu, Donn Morrison, Magnus Jahre:
Hybrid breadth-first search on a single-chip FPGA-CPU heterogeneous platform. FPL 2015: 1-8 - 2014
- [c1]Yaman Umuroglu, Magnus Jahre:
An energy efficient column-major backend for FPGA SpMV accelerators. ICCD 2014: 432-439
Coauthor Index
aka: Nicholas James Fraser
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