EXECUTION OF TRAINED NEURAL NETWORKS USING A DATABASE SYSTEM
In an embodiment, a computer-implemented method for efficient execution of a trained neural network using a database system, the trained neural network comprising a plurality of layers each comprising weight values and bias values and programmed at each of the layers to execute an affine transformat...
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creator | MILLER, KENTON SHAH, SAMIR ZHANG, BEI |
description | In an embodiment, a computer-implemented method for efficient execution of a trained neural network using a database system, the trained neural network comprising a plurality of layers each comprising weight values and bias values and programmed at each of the layers to execute an affine transformation of an activation function and an input value, comprises: for a particular layer of the trained neural network, dividing the affine transformation input a plurality of transformation pieces; executing each of the transformation pieces to result in computed pieces and writing the computed pieces to a first database table; using one or more database queries, combining the computed pieces and applying the activation function to generate a set of output data; writing the output data to one of a plurality of different second database tables that respectively correspond to the layers; repeating the dividing, executing, combining, applying and writing for all layers of the trained neural network. |
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executing each of the transformation pieces to result in computed pieces and writing the computed pieces to a first database table; using one or more database queries, combining the computed pieces and applying the activation function to generate a set of output data; writing the output data to one of a plurality of different second database tables that respectively correspond to the layers; repeating the dividing, executing, combining, applying and writing for all layers of the trained neural network.</description><language>eng</language><subject>CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; ELECTRIC DIGITAL DATA PROCESSING ; PHYSICS</subject><creationdate>2020</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20200611&DB=EPODOC&CC=US&NR=2020184311A1$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,776,881,25542,76516</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20200611&DB=EPODOC&CC=US&NR=2020184311A1$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>MILLER, KENTON</creatorcontrib><creatorcontrib>SHAH, SAMIR</creatorcontrib><creatorcontrib>ZHANG, BEI</creatorcontrib><title>EXECUTION OF TRAINED NEURAL NETWORKS USING A DATABASE SYSTEM</title><description>In an embodiment, a computer-implemented method for efficient execution of a trained neural network using a database system, the trained neural network comprising a plurality of layers each comprising weight values and bias values and programmed at each of the layers to execute an affine transformation of an activation function and an input value, comprises: for a particular layer of the trained neural network, dividing the affine transformation input a plurality of transformation pieces; executing each of the transformation pieces to result in computed pieces and writing the computed pieces to a first database table; using one or more database queries, combining the computed pieces and applying the activation function to generate a set of output data; writing the output data to one of a plurality of different second database tables that respectively correspond to the layers; repeating the dividing, executing, combining, applying and writing for all layers of the trained neural network.</description><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2020</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZLBxjXB1Dg3x9PdT8HdTCAly9PRzdVHwcw0NcvQBUiHh_kHewQqhwZ5-7gqOCi6OIY5OjsGuCsGRwSGuvjwMrGmJOcWpvFCam0HZzTXE2UM3tSA_PrW4IDE5NS-1JD402MjAyMDQwsTY0NDR0Jg4VQCxySp4</recordid><startdate>20200611</startdate><enddate>20200611</enddate><creator>MILLER, KENTON</creator><creator>SHAH, SAMIR</creator><creator>ZHANG, BEI</creator><scope>EVB</scope></search><sort><creationdate>20200611</creationdate><title>EXECUTION OF TRAINED NEURAL NETWORKS USING A DATABASE SYSTEM</title><author>MILLER, KENTON ; 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executing each of the transformation pieces to result in computed pieces and writing the computed pieces to a first database table; using one or more database queries, combining the computed pieces and applying the activation function to generate a set of output data; writing the output data to one of a plurality of different second database tables that respectively correspond to the layers; repeating the dividing, executing, combining, applying and writing for all layers of the trained neural network.</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | EXECUTION OF TRAINED NEURAL NETWORKS USING A DATABASE SYSTEM |
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