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Two-level configuration for FPGA: A new design methodology based on a computing fabric.

, , , and . ISCAS, page 265-268. IEEE, (2012)

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Bit-Slicing FPGA Accelerator for Quantized Neural Networks., , , and . ISCAS, page 1-5. IEEE, (2019)Hardware description and synthesis of control-intensive reconfigurable dataflow architectures (abstract only)., and . FPGA, page 274-275. ACM, (2013)Temporal Logic Explanations for Dynamic Decision Systems Using Anchors and Monte Carlo Tree Search (Abstract Reprint)., , and . AAAI, page 22694. AAAI Press, (2024)ASIP Accelerator for LUT-based Neural Networks Inference., , and . NEWCAS, page 524-528. IEEE, (2022)RISC-V Barrel Processor for Deep Neural Network Acceleration., , , , and . ISCAS, page 1-5. IEEE, (2021)Quark: An Integer RISC-V Vector Processor for Sub-Byte Quantized DNN Inference., , , , , , , , , and 1 other author(s). ISCAS, page 1-5. IEEE, (2023)BinaryConnect: Training Deep Neural Networks with binary weights during propagations., , and . NIPS, page 3123-3131. (2015)Two-level configuration for FPGA: A new design methodology based on a computing fabric., , , and . ISCAS, page 265-268. IEEE, (2012)Max-hashing fragments for large data sets detection.. ReConFig, page 1-6. IEEE, (2013)Synchronized-transfer-level design methodology applied to hardware matrix multiplication., and . ReConFig, page 1-7. IEEE, (2012)