Title:
Neural Methods for Resolving Hard-to-Predict Branches
Neural Methods for Resolving Hard-to-Predict Branches
| dc.contributor.advisor | Conte, Thomas M. | |
| dc.contributor.author | Gupta, Pulkit | |
| dc.contributor.department | Computer Science | |
| dc.date.accessioned | 2022-01-14T16:13:46Z | |
| dc.date.available | 2022-01-14T16:13:46Z | |
| dc.date.created | 2021-12 | |
| dc.date.issued | 2021-12-17 | |
| dc.date.submitted | December 2021 | |
| dc.date.updated | 2022-01-14T16:13:46Z | |
| dc.description.abstract | This work presents a new category of branch predictors designed to be addendums to existing state of the art prediction mechanisms. We call these neural network inspired predictors Shallow Online Neural (SON) Predictors as they utilize easily quantizable shallow networks and exhibit online training as opposed to other related works. This predictor is apt as both a branch prediction scheme and as a TAGE confidence predictor. | |
| dc.description.degree | M.S. | |
| dc.format.mimetype | application/pdf | |
| dc.identifier.uri | http://hdl.handle.net/1853/66176 | |
| dc.language.iso | en_US | |
| dc.publisher | Georgia Institute of Technology | |
| dc.subject | Branch Prediction | |
| dc.subject | Neural Networks | |
| dc.subject | Fixed-Point | |
| dc.subject | Choice Prediction | |
| dc.title | Neural Methods for Resolving Hard-to-Predict Branches | |
| dc.type | Text | |
| dc.type.genre | Thesis | |
| dspace.entity.type | Publication | |
| local.contributor.advisor | Conte, Thomas M. | |
| local.contributor.corporatename | College of Computing | |
| relation.isAdvisorOfPublication | 4d68ec01-18d9-48c9-ab69-55832ecf2dbf | |
| relation.isOrgUnitOfPublication | c8892b3c-8db6-4b7b-a33a-1b67f7db2021 | |
| thesis.degree.level | Masters |