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Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel
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| Published in: | ArXiv cs.DC Recent Papers |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
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| _version_ | 1864130790303989760 |
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| collection | WordPress RSS FRELIP Feed Integration |
| container_title | ArXiv cs.DC Recent Papers |
| description | |
| discipline_display | Engineering & Technology |
| discipline_facet | Engineering & Technology |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:48786 |
| institution | FRELIP |
| journal_source_facet | ArXiv cs.DC Recent Papers |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel ArXiv cs.DC Recent Papers Computer Science & IT Engineering & Technology |
| sub_discipline_display | Computer Science & IT |
| sub_discipline_facet | Computer Science & IT |
| subject_display | ArXiv cs.DC Recent Papers Computer Science & IT Engineering & Technology ArXiv cs.DC Recent Papers Computer Science & IT Engineering & Technology |
| subject_facet | ArXiv cs.DC Recent Papers Computer Science & IT Engineering & Technology |
| title | Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel |
| title_auth | Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel |
| title_full | Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel |
| title_fullStr | Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel |
| title_full_unstemmed | Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel |
| title_short | Exploring the Efficiency of 3D-Stacked AI Chip Architecture for LLM Inference with Voxel |
| title_sort | exploring the efficiency of 3d-stacked ai chip architecture for llm inference with voxel |
| topic | ArXiv cs.DC Recent Papers Computer Science & IT Engineering & Technology |
| url | https://arxiv.org/abs/2604.26821v1 |