<jupyter_start><jupyter_text>`openacc_interop` is an example program to demonstrate OpenACC interoperabilityfeatures. The application reads a grayscale image in pgm format, applies anedge detector (combination of gaussian blur and sharpening filter) and writesthe output as grayscale image in pgm format. The filters are applied infrequencies space and the necessary DFTs are carried out with using either aFFT library with a FFTW compatible interface, e.g. Intel MKL, in case a CPU isused for the compute or cuFFT in case a NVIDIA GPU is used.<jupyter_code>!make<jupyter_output>make: Nothing to be done for `all'.<jupyter_text>Usage```./openacc_interop input.pgm output.pgm ```E.g. using the example image from the subfolder images:<jupyter_code>!./openacc_interop images/617019_NVIDIA_HQ_bldg.pgm images/output.pgm<jupyter_output>Wrote output image images/output.pgm of size 2400 x 1600
{'fraction_non_alphanumeric': 0.059684684684684686, 'fraction_numerical': 0.015765765765765764, 'mean_word_length': 6.0, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 7, '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}}
{'chain_length': '2', 'dir': 'jupyter-structured-clean-dedup', 'id': '489275', 'license': 'CC-BY-4.0', 'n_tokens_mistral': 288, 'n_tokens_neox': 269, 'n_words': 107, 'path': 'Code_Examples/Chapter_09/python-notebook/Chapter 9.ipynb', 'repo_name': 'OpenACCUserGroup/openacc_concept_strategies_book', 'size': '888'}