3 papers
cs.DC2026
The Serialized Bridge: Understanding and Recovering LLM Serving Performance under Blackwell GPU Confidential Computing
Hang Yin, Kevin Wang
GPU Confidential Computing (GPU-CC) now preserves GPU-local performance: on NVIDIA B300, BF16 matmul runs at 0.998x of non-confidential performance. Yet LLM serving under Intel TDX…
cs.CR2026
Implement Kubernetes Pod-Level Remote Attestation for Confidential Workloads on dstack
Yang Yang, Kevin Wang, Yuanhai Luo +4
The rise of LLM-as-a-Service and other confidential cloud workloads demands cryptographic proof that user data is processed in a trusted, untampered environment. Existing solutions…
cs.CR2025
Dstack: A Zero Trust Framework for Confidential Containers
Shunfan Zhou, Kevin Wang, Hang Yin
Web3 applications require execution platforms that maintain confidentiality and integrity without relying on centralized trust authorities. While Trusted Execution Environments (TE…