arXiv (All)
open access
Cerium: A Multi-GPU Framework for Terabyte-Scale Encrypted Inference
Encrypted AI using fully homomorphic encryption (FHE) enables inference directly over encrypted queries, providing strong privacy guarantees. However, its computational and memory overheads have limited practical deployment. Custom FHE accelerators improve performance, but rely on advanced manufactu
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- WarpGuard: Towards Control-Flow Attestation for Heterogeneous CPU-GPU Execution#370276
- FP8 is All You Need (Part 1): Debunking Hardware FP64 as the HPC Holy Grail (Sep 3rd version)#986869
- Physically Partitioned KVCache Format for CPU--GPU Load Balancing in MoE Inference#1084454
- Physically Partitioned KVCache Format for CPU--GPU Load Balancing in MoE Inference#919360
- Compiler and Hardware Co-Design for Accelerator Architectures#1078170
Record · ID 1399771
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive