This book constitutes the proceedings of the 19th International Symposium on Applied Reconfigurable Computing, ARC 2023, which was held in Cottbus, Germany, in September 2023.

Design Methods and Tools.- High-Level Synthesis of Memory Systems for Decoupled Data Orchestration.- Rapid Prototyping of Complex Micro-architectures through High-Level Synthesis.- NVMulator: A Con gurable Open-Source Non-Volatile Memory Emulator for FPGAs.- On the OpenCL Support for Streaming Fixed-Function Accelerators on Embedded SoC FPGAs.- Design Space Exploration of Application Specific Number Formats targeting an FPGA Implementation of SPICE.- Memory-Aware Scheduling for a Resource-Elastic FPGA Operating System.- ArcvaVX: OpenVX Framework for Adaptive Reconfigurable Computer Vision Architectures.- Applications.- FPGA-Integrated Bag of Little Bootstraps Accelerator for Approximate Database Query Processing.- Accelerating Graph Neural Networks in Pytorch With HLS and Deep Data flows.- DNN Model Theft through Trojan Side Channel on Edge FPGA Accelerator.- Towards Secure and Efficient Multi-generation Cellular Communications: Multi-mode SNOW-3G/V ASIC and FPGA Implementations.- A Convolution Neural Network based Displaced Vertex Trigger for the Belle II Experiment.- On-FPGA Spiking Neural Networks for Multi-Variable End-to-End Neural Decoding.- Implementation of a Perception System for Autonomous Vehicles using a Detection-Segmentation Network in SoC FPGA.- Architectures.- Increasing the Fault Tolerance of COTS FPGAs in Space: SEU Mitigation Techniques on MPSoC.- Scalable and Energy-Efficient NN Acceleration with GPU-ReRAM Architecture.- On Guaranteeing Schedulability of Periodic Real-time Hardware Tasks under ReconOS64.- Evolutionary FPGA-based Spiking Neural Networks for Continual Learning.- More Efficient CMMs on FPGAs: Instantiated Ternary Adders for Computation Coding.- Energy Efficient DNN Compaction for Edge Deployment.- Special Session: Near and In-Memory Computing.- TAPRE-HBM: Trace-Based Processor Rapid Emulation using HBM on FPGAs.- An Almost Fully RRAM-based LUT Design for Reconfigurable Circuits.- A Light-weight Vision Transformer toward Near-Memory Computation on an FPGA.- PhD Forum Papers