{"id":153157,"date":"2007-10-01T00:00:00","date_gmt":"2007-10-01T00:00:00","guid":{"rendered":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/msr-research-item\/parallel-white-noise-generation-on-a-gpu-via-cryptographic-hash\/"},"modified":"2018-10-16T21:00:18","modified_gmt":"2018-10-17T04:00:18","slug":"parallel-white-noise-generation-on-a-gpu-via-cryptographic-hash","status":"publish","type":"msr-research-item","link":"https:\/\/newed.any0.dpdns.org\/en-us\/research\/publication\/parallel-white-noise-generation-on-a-gpu-via-cryptographic-hash\/","title":{"rendered":"Parallel White Noise Generation on a GPU via Cryptographic Hash"},"content":{"rendered":"<div class=\"asset-content\">\n<p>A good random number generator is essential for many graphics applications. As more such applications move onto parallel processing, it is vital that a good parallel random number generator be used. Unfortunately, most random number generators today are still sequential, exposing performance bottlenecks and denying random accessibility for parallel computations. Furthermore, popular parallel random number generators are still based off sequential methods and can exhibit statistical bias. In this paper, we propose a random number generator that maps well onto a parallel processor while possessing white noise distribution. Our generator is based on cryptographic hash functions whose statistical robustness has been examined under heavy scrutiny by cryptologists. We implement our generator as a GPU pixel program, allowing us to compute random numbers in parallel just like ordinary texture fetches: given a texture coordinate per pixel, instead of returning a texel as in ordinary texture fetches, our pixel program computes a random noise value based on this given texture coordinate. We demonstrate that our approach features the best quality, speed, and random accessibility for graphics applications.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A good random number generator is essential for many graphics applications. As more such applications move onto parallel processing, it is vital that a good parallel random number generator be used. Unfortunately, most random number generators today are still sequential, exposing performance bottlenecks and denying random accessibility for parallel computations. Furthermore, popular parallel random number [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"Association for Computing Machinery, Inc.","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"I3D 2008","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"MSR-TR-2007-141","msr_organization":"","msr_pages_string":"9","msr_page_range_start":"9","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"Copyright \u00a9 2007 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and\/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or permissions@acm.org. The definitive version of this paper can be found at ACM's Digital Library -http:\/\/www.acm.org\/dl\/.","msr_conference_name":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"Microsoft Research","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2007-10-01","msr_highlight_text":"","msr_notes":"I3D 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