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You Cannot Improve What You Do not Measure: FPGA vs. ASIC Efficiency Gaps for Convolutional Neural Network Inference., , and . ACM Trans. Reconfigurable Technol. Syst., 11 (3): 20:1-20:23 (2018)FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems., , , , and . CoRR, (2022)Koios: A Deep Learning Benchmark Suite for FPGA Architecture and CAD Research., , , , , , , , , and 2 other author(s). FPL, page 355-362. IEEE, (2021)Specializing for Efficiency: Customizing AI Inference Processors on FPGAs., , and . ICM, page 62-65. IEEE, (2021)Beyond Peak Performance: Comparing the Real Performance of AI-Optimized FPGAs and GPUs., , , , , , , and . FPT, page 10-19. IEEE, (2020)High Throughput FPGA-Based Object Detection via Algorithm-Hardware Co-Design., , , , , , , , , and . ACM Trans. Reconfigurable Technol. Syst., 17 (1): 1:1-1:20 (March 2024)Architecture and Application Co-Design for Beyond-FPGA Reconfigurable Acceleration Devices., , and . IEEE Access, (2022)Hardware acceleration of novel chaos-based image encryption for IoT applications., , , and . ICM, page 1-4. IEEE, (2017)A Whole New World: How to Architect Beyond-FPGA Reconfigurable Acceleration Devices?, , and . FPL, page 265-270. IEEE, (2023)RAD-Sim: Rapid Architecture Exploration for Novel Reconfigurable Acceleration Devices., , and . FPL, page 438-444. IEEE, (2022)