{'fraction_non_alphanumeric': 0.016786570743405275, 'fraction_numerical': 0.0, 'mean_word_length': 5.68, '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}}
Dynamic task mapping of graphics processing applications on many-core architectures through stream rewriting

Although modern graphics processing units (GPU) contain a large number of programmable shader cores, the focus on data parallelism and also the lack of efficient on-chip communication hinder the creation of custom graphics pipelines with arbitrary topologies. Based on the concept of stream rewriting, we propose a novel many-core architecture for graphics processing, which supports dynamic scheduling of recursively expandable task graphs and graphics pipelines. In particular, the tasks and their dependencies are encoded as a token stream, which is iteratively rewritten via pattern matching on multiple cores in parallel. The scalability of the proposed hardware architecture has been evaluated using an FPGA prototype.