Performance of ML-Based Bandwidth Compression on FPGAs
This thesis investigates the integration of machine learning (ML)-based compression on Field-Programmable Gate Arrays (FPGAs) to enhance bandwidth compression of data, a crucial aspect in scientific research where large amounts of data are produced in real-time. The compression tool Baler, utilizing autoencoders for ML-based compression, is designed to handle scientific data efficiently. By combin
