šŸ¤– AI runs on GPUs, NOT CPUs. Modern AI workloads—think LLMs, real-time inference—need massive parallelism. GPUs like NVIDIA’s H100 do that beautifully. But here's the harsh truth: once your data hits GPU memory, it's COMPLETELY exposed. GPU TEEs change the game. 🧵
1/🧵 Think of GPU TEEs as bulletproof vaults inside your graphics card. They keep your AI execution private, verifiable, and tamper-proof—even if the host OS is compromised. The best part? Near-zero performance overhead (<2% on large models). 😱
2/🧵 How does GPU TEE work? šŸ”’ Hardware Root of Trust burned into each chip šŸ”’ Secure boot with signed firmware šŸ”’ Encrypted CPU-GPU communication šŸ”’ Remote attestation to prove integrity šŸ”’ Zero visibility to host OS or hypervisor Full trust chain from silicon to software.
3/🧵 Phala dropped the world's first GPU TEE benchmarks last September. The results: šŸ‘Š <9% average performance loss šŸ‘Š Larger models = near-zero overhead šŸ‘Š 20-25% longer startup (worth it for security) šŸ‘Š PCIe transfer is the only real bottleneck
4/🧵 Real talk: this solves MASSIVE problems in AI: šŸ„ Healthcare AI on shared clusters (patient data stays encrypted) šŸ¦ Financial models that can't leak trading strategies šŸ”¬ Federated learning without exposing raw datasets āš–ļø Regulatory compliance by design
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