Benchmarking Analytical Query Processing in Intel SGXv2
CoRR(2024)
摘要
The recently introduced second generation of Intel SGX (SGXv2) lifts memory
size limitations of the first generation. Theoretically, this promises to
enable secure and highly efficient analytical DBMSs in the cloud. To validate
this promise, in this paper, we conduct the first in-depth evaluation study of
running analytical query processing algorithms inside SGXv2. Our study reveals
that state-of-the-art query operators like radix joins and SIMD-based scans can
indeed achieve high performance inside SGXv2 enclaves. These operations are
orders of magnitude faster than joins optimized for the discontinued SGXv1
hardware. However, substantial performance overheads are still caused by subtle
hardware and software differences influencing code execution inside an SGX
enclave. We investigate these differences and propose new optimizations to
bring the performance inside the enclave on par with native code execution
outside an enclave.
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