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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2403.11874 |
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| _version_ | 1866915116716392448 |
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| author | Lutsch, Adrian El-Hindi, Muhammad Heinrich, Matthias Ritter, Daniel István, Zsolt Binnig, Carsten |
| author_facet | Lutsch, Adrian El-Hindi, Muhammad Heinrich, Matthias Ritter, Daniel István, Zsolt Binnig, Carsten |
| contents | Trusted Execution Environments (TEEs), such as Intel's Software Guard Extensions (SGX), are increasingly being adopted to address trust and compliance issues in the public cloud. Intel SGX's second generation (SGXv2) addresses many limitations of its predecessor (SGXv1), offering the potential for secure and efficient analytical cloud DBMSs. We assess this potential and conduct the first in-depth evaluation study of analytical query processing algorithms inside SGXv2. Our study reveals that, unlike SGXv1, state-of-the-art algorithms like radix joins and SIMD-based scans are a good starting point for achieving high-performance query processing inside SGXv2. However, subtle hardware and software differences still influence code execution inside SGX enclaves and cause substantial overheads. We investigate these differences and propose new optimizations to bring the performance inside enclaves on par with native code execution outside enclaves. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_11874 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Benchmarking Analytical Query Processing in Intel SGXv2 Lutsch, Adrian El-Hindi, Muhammad Heinrich, Matthias Ritter, Daniel István, Zsolt Binnig, Carsten Databases H.2; B.8 Trusted Execution Environments (TEEs), such as Intel's Software Guard Extensions (SGX), are increasingly being adopted to address trust and compliance issues in the public cloud. Intel SGX's second generation (SGXv2) addresses many limitations of its predecessor (SGXv1), offering the potential for secure and efficient analytical cloud DBMSs. We assess this potential and conduct the first in-depth evaluation study of analytical query processing algorithms inside SGXv2. Our study reveals that, unlike SGXv1, state-of-the-art algorithms like radix joins and SIMD-based scans are a good starting point for achieving high-performance query processing inside SGXv2. However, subtle hardware and software differences still influence code execution inside SGX enclaves and cause substantial overheads. We investigate these differences and propose new optimizations to bring the performance inside enclaves on par with native code execution outside enclaves. |
| title | Benchmarking Analytical Query Processing in Intel SGXv2 |
| topic | Databases H.2; B.8 |
| url | https://arxiv.org/abs/2403.11874 |