GS-TG: 3D Gaussian Splatting Accelerator with Tile Grouping for Reducing Redundant Sorting while Preserving Rasterization Efficiency
3D Gaussian Splatting (3D-GS) has emerged as a promising alternative to neural radiance fields (NeRF) as it offers high speed as well as high image quality in novel view synthesis. Despite these advancements, 3D-GS still struggles to meet the frames per second (FPS) demands of real-time applications...
Uloženo v:
| Vydáno v: | 2025 62nd ACM/IEEE Design Automation Conference (DAC) s. 1 - 7 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
22.06.2025
|
| Témata: | |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | 3D Gaussian Splatting (3D-GS) has emerged as a promising alternative to neural radiance fields (NeRF) as it offers high speed as well as high image quality in novel view synthesis. Despite these advancements, 3D-GS still struggles to meet the frames per second (FPS) demands of real-time applications. In this paper, we introduce GS-TG, a tile-grouping-based accelerator that enhances 3D-GS rendering speed by reducing redundant sorting operations and preserving rasterization efficiency. GS-TG addresses a critical trade-off issue in 3D-GS rendering: increasing the tile size effectively reduces redundant sorting operations, but it concurrently increases unnecessary rasterization computations. So, during sorting of the proposed approach, GS-TG groups small tiles (for making large tiles) to share sorting operations across tiles within each group, significantly reducing redundant computations. During rasterization, a bitmask assigned to each Gaussian identifies relevant small tiles, to enable efficient sharing of sorting results. Consequently, GS-TG enables sorting to be performed as if a large tile size is used by grouping tiles during the sorting stage, while allowing rasterization to proceed with the original small tiles by using bitmasks in the rasterization stage. GS-TG is a lossless method requiring no retraining or fine-tuning and it can be seamlessly integrated with previous 3D-GS optimization techniques. Experimental results show that GS-TG achieves an average speed-up of 1.54 times over state-of-the-art 3D-GS accelerators. |
|---|---|
| AbstractList | 3D Gaussian Splatting (3D-GS) has emerged as a promising alternative to neural radiance fields (NeRF) as it offers high speed as well as high image quality in novel view synthesis. Despite these advancements, 3D-GS still struggles to meet the frames per second (FPS) demands of real-time applications. In this paper, we introduce GS-TG, a tile-grouping-based accelerator that enhances 3D-GS rendering speed by reducing redundant sorting operations and preserving rasterization efficiency. GS-TG addresses a critical trade-off issue in 3D-GS rendering: increasing the tile size effectively reduces redundant sorting operations, but it concurrently increases unnecessary rasterization computations. So, during sorting of the proposed approach, GS-TG groups small tiles (for making large tiles) to share sorting operations across tiles within each group, significantly reducing redundant computations. During rasterization, a bitmask assigned to each Gaussian identifies relevant small tiles, to enable efficient sharing of sorting results. Consequently, GS-TG enables sorting to be performed as if a large tile size is used by grouping tiles during the sorting stage, while allowing rasterization to proceed with the original small tiles by using bitmasks in the rasterization stage. GS-TG is a lossless method requiring no retraining or fine-tuning and it can be seamlessly integrated with previous 3D-GS optimization techniques. Experimental results show that GS-TG achieves an average speed-up of 1.54 times over state-of-the-art 3D-GS accelerators. |
| Author | Park, Jongsun Jo, Joongho |
| Author_xml | – sequence: 1 givenname: Joongho surname: Jo fullname: Jo, Joongho email: jojoss1004@korea.ac.kr organization: Korea University,Seoul,Republic of Korea – sequence: 2 givenname: Jongsun surname: Park fullname: Park, Jongsun email: jongsun@korea.ac.kr organization: Korea University,Seoul,Republic of Korea |
| BookMark | eNo1UM1OAjEQrokeFHkDY_oCi21n_-qNAK4mJBrBM5ktU2mydkm3SPDsg8uinma-v0m-uWLnvvXE2K0UIymFvpuOJzmUqR4pobIjJQFUCWdsqAtdAshMgEjLS_ZdLZJldc9hyivcdZ1DzxfbBmN0_p2PjaGGAsY28L2LG750DfEqtLttL9sj_UrrnelBv_g1-sgXbTil95ve_RKoo_B5smAXKbgvjK71fGatM468OVyzC4tNR8O_OWBvD7Pl5DGZP1dPk_E8QVnomECOGiUWoOvcFEJqQqo1gjk2sSZPlc2UwnVmMytKmddpKnMUUioq69pkFgbs5veuI6LVNrgPDIfV_3PgB1IuYHE |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IH CBEJK RIE RIO |
| DOI | 10.1109/DAC63849.2025.11133283 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan (POP) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP) 1998-present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798331503048 |
| EndPage | 7 |
| ExternalDocumentID | 11133283 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IH CBEJK RIE RIO |
| ID | FETCH-LOGICAL-a179t-36a9a1a739b6c7019eaeb9a3c048fc642f522ad5f5f0816b4416a0112e8bbc5f3 |
| IEDL.DBID | RIE |
| IngestDate | Wed Oct 01 07:05:15 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | true |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-a179t-36a9a1a739b6c7019eaeb9a3c048fc642f522ad5f5f0816b4416a0112e8bbc5f3 |
| PageCount | 7 |
| ParticipantIDs | ieee_primary_11133283 |
| PublicationCentury | 2000 |
| PublicationDate | 2025-June-22 |
| PublicationDateYYYYMMDD | 2025-06-22 |
| PublicationDate_xml | – month: 06 year: 2025 text: 2025-June-22 day: 22 |
| PublicationDecade | 2020 |
| PublicationTitle | 2025 62nd ACM/IEEE Design Automation Conference (DAC) |
| PublicationTitleAbbrev | DAC |
| PublicationYear | 2025 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 2.295401 |
| Snippet | 3D Gaussian Splatting (3D-GS) has emerged as a promising alternative to neural radiance fields (NeRF) as it offers high speed as well as high image quality in... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1 |
| SubjectTerms | Accelerator Energy efficiency Gaussian Splatting Hardware Image quality Neural radiance field Optimization Pipelines Real-time systems Rendering Rendering (computer graphics) Sorting Three-dimensional displays |
| Title | GS-TG: 3D Gaussian Splatting Accelerator with Tile Grouping for Reducing Redundant Sorting while Preserving Rasterization Efficiency |
| URI | https://ieeexplore.ieee.org/document/11133283 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG6EePCkRoyKmh68Lkifu94ILw-GEEHDjUxLG03MQmDRP-APt1MWjQcP3rrb2WzS2dmZTuebj5AbmXomvFSJgLA3ERxUkiovEuW0yYDzTEU6oOcHPRym02k2KsHqEQvjnIvFZ66Bw3iWP1_YDabKmkiLzoM_rJCK1moL1ipRv63brNltd8LXJBB-wmRjJ_yLNiV6jf7hP993RGo_-Ds6-vYsx2TP5SfkczBOJoM7yrt0AJs1gh_pePkGsXCZtq0NDiSemVPMrdJJMHcaM0s4HUJT-ohdWvECB2Ennhd0vFjFpz9eUBrLMfDXgSKADRRKjCbtxT4TCNKskad-b9K5T0oOhQSCqRUJV5BBCzTPjLLYet2BQyXYYLnehs2HDwEYzKWXHik4TIiOFASbZy41xkrPT0k1X-TujFDQmdMOmJaSCa1N6lLh5-ANIAs7s-ekhks4W27bZMx2q3fxx_06OUBFYd0VY5ekWqw27ors2_fidb26jsr9AvzkqHU |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LT8MwDI5gIMEJEEO8yYFrt5Hm0XKb9kSMaWIF7Ta5WSKQUDdtHfwBfjhx1oE4cOCWNq4qxXXtOP78EXItIsu4FTLg4PYmPAQZRNLyQBqVxhCGsfR0QM891e9Ho1E8KMDqHgtjjPHFZ6aCQ3-WP5nqJabKqkiLHjp_uEm2BOestoJrFbjfm1pcbdYb7nviCEBhorIW_0Wc4v1Ge--fb9wn5R8EHh18-5YDsmGyQ_LZGQZJ55aGTdqB5QLhj3Q4ewNfukzrWjsX4k_NKWZXaeIMnvrcEk674JQ-Yp9WvMCB24tnOR1O5_7pjxeUxoIM_HmgCGALhQKlSVu-0wTCNMvkqd1KGt2gYFEIwBlbHoQSYrgBFcap1Nh83YBBNWhnu1a77Yd1IRhMhBUWSThSFx9JcFbPTJSmWtjwiJSyaWaOCQUVG2WAKSEYVyqNTMTtBGwKyMPO9Akp4xKOZ6tGGeP16p3-cf-K7HSTh964d9e_PyO7qDSswmLsnJTy-dJckG39nr8u5pde0V_pIqu8 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2025+62nd+ACM%2FIEEE+Design+Automation+Conference+%28DAC%29&rft.atitle=GS-TG%3A+3D+Gaussian+Splatting+Accelerator+with+Tile+Grouping+for+Reducing+Redundant+Sorting+while+Preserving+Rasterization+Efficiency&rft.au=Jo%2C+Joongho&rft.au=Park%2C+Jongsun&rft.date=2025-06-22&rft.pub=IEEE&rft.spage=1&rft.epage=7&rft_id=info:doi/10.1109%2FDAC63849.2025.11133283&rft.externalDocID=11133283 |