{'fraction_non_alphanumeric': 0.02412280701754386, 'fraction_numerical': 0.0, 'mean_word_length': 5.568345323741007, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A fast, scalable, and energy-efficient edge acceleration architecture based on FPGA cluster

FPGA-based acceleration has been emerged to avoid the cloud computing overload problem by accelerating the compute-intensive workload on edge networks. Though existing studies for FPGA-based edge acceleration have focused on optimizing the computing time, they did not address the burden of the FPGA-aided server under an enormous computing requests circumstance. The massive computing requests can cause delays in transmission and processing at the FPGA-aided server, leading to long response times and high system energy consumption. Therefore, we propose an emerging edge acceleration architecture based on FPGA cluster over the low-latency RDMA-based network. Preliminary simulation results demonstrate that our architecture is fast, scalable, and energy-efficient in comparison with the FPGA-aided servers cluster.