{'fraction_non_alphanumeric': 0.019736842105263157, 'fraction_numerical': 0.0, 'mean_word_length': 5.720588235294118, '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}}
Effective Profiling for Data-Intensive GPU Programs: Work-in-Progress

GPU profilers have been successfully used to analyze bottlenecks and slowdowns of GPU programs. Several instrumentation tools for profiling GPU binaries are introduced, but these tools take little consideration into GPU architectures. In this paper, we investigate common factors of performance degradation on existing GPU profilers and provide design guide to improve the performance.