{"id":"https://openalex.org/W4416004096","doi":"https://doi.org/10.1145/3731599.3767544","title":"A High Performance GPU CountSketch Implementation and Its Application to Multisketching and Least Squares Problems","display_name":"A High Performance GPU CountSketch Implementation and Its Application to Multisketching and Least Squares Problems","publication_year":2025,"publication_date":"2025-11-07","ids":{"openalex":"https://openalex.org/W4416004096","doi":"https://doi.org/10.1145/3731599.3767544"},"language":null,"primary_location":{"id":"doi:10.1145/3731599.3767544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3731599.3767544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SC '25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3731599.3767544","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101461538","display_name":"Andrew J. Higgins","orcid":"https://orcid.org/0009-0007-5527-9263"},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Andrew James Higgins","raw_affiliation_strings":["Sandia National Laboratories, Albuquerque, New Mexico, USA"],"raw_orcid":"https://orcid.org/0009-0007-5527-9263","affiliations":[{"raw_affiliation_string":"Sandia National Laboratories, Albuquerque, New Mexico, USA","institution_ids":["https://openalex.org/I4210104735"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042681205","display_name":"Erik G. Boman","orcid":"https://orcid.org/0000-0003-2216-5546"},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Erik Boman","raw_affiliation_strings":["Sandia National Laboratories, Albuquerque, New Mexico, USA"],"raw_orcid":"https://orcid.org/0000-0003-2216-5546","affiliations":[{"raw_affiliation_string":"Sandia National Laboratories, Albuquerque, New Mexico, USA","institution_ids":["https://openalex.org/I4210104735"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052397462","display_name":"Ichitaro Yamazaki","orcid":"https://orcid.org/0000-0002-6196-2508"},"institutions":[{"id":"https://openalex.org/I4210104735","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12","country_code":"US","type":"facility","lineage":["https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210104735"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ichitaro Yamazaki","raw_affiliation_strings":["Sandia National Laboratories, Albuquerque, New Mexico, USA"],"raw_orcid":"https://orcid.org/0000-0002-6196-2508","affiliations":[{"raw_affiliation_string":"Sandia National Laboratories, Albuquerque, New Mexico, USA","institution_ids":["https://openalex.org/I4210104735"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5101461538"],"corresponding_institution_ids":["https://openalex.org/I4210104735"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.16702554,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1808","last_page":"1815"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.6948000192642212,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.6948000192642212,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.050599999725818634,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.02590000070631504,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sketch","display_name":"Sketch","score":0.7257000207901001},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.6194999814033508},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.5910999774932861},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.5231999754905701},{"id":"https://openalex.org/keywords/random-projection","display_name":"Random projection","score":0.5115000009536743},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4205999970436096},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4169999957084656},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.41609999537467957},{"id":"https://openalex.org/keywords/factor","display_name":"Factor (programming language)","score":0.4025999903678894}],"concepts":[{"id":"https://openalex.org/C2779231336","wikidata":"https://www.wikidata.org/wiki/Q7534724","display_name":"Sketch","level":2,"score":0.7257000207901001},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.6194999814033508},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.5910999774932861},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5231999754905701},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5194000005722046},{"id":"https://openalex.org/C2777036070","wikidata":"https://www.wikidata.org/wiki/Q18393452","display_name":"Random projection","level":2,"score":0.5115000009536743},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5095000267028809},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4603999853134155},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4205999970436096},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4169999957084656},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.41609999537467957},{"id":"https://openalex.org/C2781039887","wikidata":"https://www.wikidata.org/wiki/Q1391724","display_name":"Factor (programming language)","level":2,"score":0.4025999903678894},{"id":"https://openalex.org/C64812099","wikidata":"https://www.wikidata.org/wiki/Q176604","display_name":"Random matrix","level":3,"score":0.3659999966621399},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33959999680519104},{"id":"https://openalex.org/C128669082","wikidata":"https://www.wikidata.org/wiki/Q583461","display_name":"Randomized algorithm","level":2,"score":0.33230000734329224},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.3301999866962433},{"id":"https://openalex.org/C109282560","wikidata":"https://www.wikidata.org/wiki/Q4166054","display_name":"Singular value","level":3,"score":0.3025999963283539},{"id":"https://openalex.org/C22789450","wikidata":"https://www.wikidata.org/wiki/Q420904","display_name":"Singular value decomposition","level":2,"score":0.27720001339912415},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2752000093460083},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27309998869895935},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2685000002384186},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.2662999927997589},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.26440000534057617},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.2551000118255615},{"id":"https://openalex.org/C30463267","wikidata":"https://www.wikidata.org/wiki/Q1422682","display_name":"Hadamard matrix","level":3,"score":0.25450000166893005}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3731599.3767544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3731599.3767544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SC '25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3731599.3767544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3731599.3767544","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the SC '25 Workshops of the International Conference for High Performance Computing, Networking, Storage and Analysis","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G805931733","display_name":null,"funder_award_id":"DE-NA-0003525","funder_id":"https://openalex.org/F4320338291","funder_display_name":"Sandia National Laboratories"}],"funders":[{"id":"https://openalex.org/F4320338291","display_name":"Sandia National Laboratories","ror":"https://ror.org/01apwpt12"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1779006005","https://openalex.org/W2007500622","https://openalex.org/W2008776938","https://openalex.org/W2020804487","https://openalex.org/W2045390367","https://openalex.org/W2124659530","https://openalex.org/W2134342155","https://openalex.org/W2792702316","https://openalex.org/W2963455674","https://openalex.org/W3108353645","https://openalex.org/W3112410551","https://openalex.org/W3139361274","https://openalex.org/W4249843299","https://openalex.org/W4320800818","https://openalex.org/W4409053225"],"related_works":[],"abstract_inverted_index":{"Random":[0],"sketching":[1],"is":[2],"a":[3,61,65],"dimensionality":[4],"reduction":[5],"technique":[6],"that":[7],"approximately":[8],"preserves":[9],"norms":[10],"and":[11,33,67],"singular":[12],"values":[13],"up":[14],"to":[15],"some":[16],"O(1)":[17],"distortion":[18],"factor":[19],"with":[20],"high":[21],"probability.":[22],"The":[23],"most":[24],"popular":[25],"sketches":[26],"in":[27],"literature":[28],"are":[29],"the":[30,34,40,58],"Gaussian":[31,68],"sketch":[32],"subsampled":[35],"randomized":[36],"Hadamard":[37],"transform,":[38],"while":[39],"CountSketch":[41,66],"has":[42],"lower":[43],"complexity.":[44],"Combining":[45],"two":[46],"sketches,":[47],"known":[48],"as":[49],"multisketching,":[50],"offers":[51],"an":[52],"inexpensive":[53],"means":[54],"of":[55,60],"quickly":[56],"reducing":[57],"dimension":[59],"matrix":[62],"by":[63],"combining":[64],"sketch.":[69]},"counts_by_year":[],"updated_date":"2025-11-08T23:21:52.890332","created_date":"2025-11-07T00:00:00"}