An energy efficient column-major backend for FPGA SpMV accelerators. - Yaman Umuroglu; Magnus Jahre (ICCD, 2014)

A Vector Caching Scheme for Streaming FPGA SpMV Accelerators. - Yaman Umuroglu; Magnus Jahre (ARC, 2015)

Hybrid breadth-first search on a single-chip FPGA-CPU heterogeneous platform. - Yaman Umuroglu; Donn Morrison; Magnus Jahre (FPL, 2015)

Random access schemes for efficient FPGA SpMV acceleration. - Yaman Umuroglu; Magnus Jahre (Microprocess. Microsystems, 2016)

Towards efficient quantized neural network inference on mobile devices: work-in-progress. - Yaman Umuroglu; Magnus Jahre (CASES, 2017)

FINN: A Framework for Fast, Scalable Binarized Neural Network Inference. - Yaman Umuroglu; Nicholas J. Fraser; Giulio Gambardella; Michaela Blott; Philip Heng Wai Leong; Magnus Jahre; Kees A. Vissers (FPGA, 2017)

Scaling Binarized Neural Networks on Reconfigurable Logic. - Nicholas J. Fraser; Yaman Umuroglu; Giulio Gambardella; Michaela Blott; Philip Heng Wai Leong; Magnus Jahre; Kees A. Vissers (PARMA-DITAM@HiPEAC, 2017)

Scaling Neural Network Performance through Customized Hardware Architectures on Reconfigurable Logic. - Michaela Blott; Thomas B. Preußer; Nicholas J. Fraser; Giulio Gambardella; Kenneth O'Brien; Yaman Umuroglu; Miriam Leeser (ICCD, 2017)

Streamlined Deployment for Quantized Neural Networks. - Yaman Umuroglu; Magnus Jahre (CoRR, 2017)

BISMO: A Scalable Bit-Serial Matrix Multiplication Overlay for Reconfigurable Computing. - Yaman Umuroglu; Lahiru Rasnayake; Magnus Själander (FPL, 2018)

FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks. - Michaela Blott; Thomas B. Preußer; Nicholas J. Fraser; Giulio Gambardella; Kenneth O'Brien; Yaman Umuroglu (CoRR, 2018)

FINN-R: An End-to-End Deep-Learning Framework for Fast Exploration of Quantized Neural Networks. - Michaela Blott; Thomas B. Preußer; Nicholas J. Fraser; Giulio Gambardella; Kenneth O'Brien; Yaman Umuroglu; Miriam Leeser; Kees A. Vissers (ACM Trans. Reconfigurable Technol. Syst., 2018)

Accelerating Sparse Linear Algebra and Deep Neural Networks on Reconfigurable Platforms. - Yaman Umuroglu (2018)

Optimizing Bit-Serial Matrix Multiplication for Reconfigurable Computing. - Yaman Umuroglu; Davide Conficconi; Lahiru Rasnayake; Thomas B. Preußer; Magnus Själander (ACM Trans. Reconfigurable Technol. Syst., 2019)

High-Throughput DNN Inference with LogicNets. - Yaman Umuroglu; Yash Akhauri; Nicholas J. Fraser; Michaela Blott (FCCM, 2020)

Evaluation of Optimized CNNs on FPGA and non-FPGA based Accelerators using a Novel Benchmarking Approach. - Michaela Blott; Johannes Kath; Lisa Halder; Yaman Umuroglu; Nicholas J. Fraser; Giulio Gambardella; Miriam Leeser; Linda Doyle (FPGA, 2020)

LogicNets: Co-Designed Neural Networks and Circuits for Extreme-Throughput Applications. - Yaman Umuroglu; Yash Akhauri; Nicholas James Fraser; Michaela Blott (FPL, 2020)

Ps and Qs: Quantization-Aware Pruning for Efficient Low Latency Neural Network Inference. - Benjamin Hawks; Javier M. Duarte; Nicholas J. Fraser; Alessandro Pappalardo; Nhan Tran; Yaman Umuroglu (Frontiers Artif. Intell., 2021)

Evaluation of Optimized CNNs on Heterogeneous Accelerators Using a Novel Benchmarking Approach. - Michaela Blott; Nicholas J. Fraser; Giulio Gambardella; Lisa Halder; Johannes Kath; Zachary Neveu; Yaman Umuroglu; Alina Vasilciuc; Miriam Leeser; Linda Doyle (IEEE Trans. Computers, 2021)

QONNX: Representing Arbitrary-Precision Quantized Neural Networks. - 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; et al. (CoRR, 2022)

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark. - Hendrik Borras; Giuseppe Di Guglielmo; Javier M. Duarte; Nicolò Ghielmetti; Benjamin Hawks; Scott Hauck; Shih-Chieh Hsu; Ryan Kastner; Jason Liang; Andres Meza 001; Jules Muhizi; Tai Nguyen 003; et al. (CoRR, 2022)

RadioML Meets FINN: Enabling Future RF Applications With FPGA Streaming Architectures. - Felix Jentzsch; Yaman Umuroglu; Alessandro Pappalardo; Michaela Blott; Marco Platzner (IEEE Micro, 2022)

Elastic-DF: Scaling Performance of DNN Inference in FPGA Clouds through Automatic Partitioning. - Tobias Alonso; Lucian Petrica; Mario Ruiz; Jakoba Petri-Koenig; Yaman Umuroglu; Ioannis Stamelos; Elias Koromilas; Michaela Blott; Kees A. Vissers (ACM Trans. Reconfigurable Technol. Syst., 2022)

A2Q+: Improving Accumulator-Aware Weight Quantization. - Ian Colbert; Alessandro Pappalardo; Jakoba Petri-Koenig; Yaman Umuroglu (ICML, 2024)

EcoFlow: Efficient Convolutional Dataflows on Low-Power Neural Network Accelerators. - Lois Orosa 001; Skanda Koppula; Yaman Umuroglu; Konstantinos Kanellopoulos; Juan Gómez-Luna; Michaela Blott; Kees A. Vissers; Onur Mutlu (IEEE Trans. Computers, 2024)