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{ "category": "SciPy 2012", "language": "English", "slug": "numba-python-bytecode-to-llvm-translator", "speakers": [ "Jon Riehl", "Travis Oliphant" ], "tags": [ "hpc" ], "id": 1194, "state": 1, "title": "Numba Python bytecode to LLVM translator", "summary": "", "description": "Numba is a Python bytecode to LLVM translator that allows creation of fast,\nmachine code from Python functions. The Low Level Virtual Machine (LLVM)\nproject is rapidly becoming a hardware-industry standard for the intermediate\nrepresentation (IR) of compiled codes. Numba's high-level translator to the\nLLVM IR provides Python the ability to take advantage of the machine code\ngenerated by the hardware manufacturers contributions to LLVM. Numba\ntranslates a Python function comprised of a subset of Python syntax to machine\ncode using simple type inference and the creation of multiple machine-code\nversions. In this talk, I will describe the design of Numba, illustrate its\napplications to multiple domains and discuss the enhancements to NumPy and\nSciPy that can benefit from this tool.\n\n", "quality_notes": "", "copyright_text": "CC BY-SA", "embed": "<object width=\"640\" height=\"390\"><param name=\"movie\" value=\";hl=en_US\"></param><param name=\"allowFullScreen\" value=\"true\"></param><param name=\"allowscriptaccess\" value=\"always\"></param><embed src=\";hl=en_US\" type=\"application/x-shockwave-flash\" width=\"640\" height=\"390\" allowscriptaccess=\"always\" allowfullscreen=\"true\"></embed></object>", "thumbnail_url": "", "duration": null, "video_ogv_length": null, "video_ogv_url": null, "video_ogv_download_only": false, "video_mp4_length": null, "video_mp4_url": "", "video_mp4_download_only": false, "video_webm_length": null, "video_webm_url": "", "video_webm_download_only": false, "video_flv_length": null, "video_flv_url": "", "video_flv_download_only": false, "source_url": "", "whiteboard": "", "recorded": "2012-07-18", "added": "2012-08-31T16:34:29", "updated": "2014-04-08T20:28:27.148" }