Privacy Preserving In-memory Computing Engine Article Swipe
Haoran Geng
,
Jianqiao Mo
,
Dayane Reis
,
Jonathan Takeshita
,
Taeho Jung
,
Brandon Reagen
,
Michael Niemier
,
Xiaobo Sharon Hu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2308.02648
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2308.02648
Privacy has rapidly become a major concern/design consideration. Homomorphic Encryption (HE) and Garbled Circuits (GC) are privacy-preserving techniques that support computations on encrypted data. HE and GC can complement each other, as HE is more efficient for linear operations, while GC is more effective for non-linear operations. Together, they enable complex computing tasks, such as machine learning, to be performed exactly on ciphertexts. However, HE and GC introduce two major bottlenecks: an elevated computational overhead and high data transfer costs. This paper presents PPIMCE, an in-memory computing (IMC) fabric designed to mitigate both computational overhead and data transfer issues. Through the use of multiple IMC cores for high parallelism, and by leveraging in-SRAM IMC for data management, PPIMCE offers a compact, energy-efficient solution for accelerating HE and GC. PPIMCE achieves a 107X speedup against a CPU implementation of GC. Additionally, PPIMCE achieves a 1,500X and 800X speedup compared to CPU and GPU implementations of CKKS-based HE multiplications. For privacy-preserving machine learning inference, PPIMCE attains a 1,000X speedup compared to CPU and a 12X speedup against CraterLake, the state-of-art privacy preserving computation accelerator.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2308.02648
- https://arxiv.org/pdf/2308.02648
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385681031
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4385681031Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2308.02648Digital Object Identifier
- Title
-
Privacy Preserving In-memory Computing EngineWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-04Full publication date if available
- Authors
-
Haoran Geng, Jianqiao Mo, Dayane Reis, Jonathan Takeshita, Taeho Jung, Brandon Reagen, Michael Niemier, Xiaobo Sharon HuList of authors in order
- Landing page
-
https://arxiv.org/abs/2308.02648Publisher landing page
- PDF URL
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https://arxiv.org/pdf/2308.02648Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2308.02648Direct OA link when available
- Concepts
-
Speedup, Computer science, Homomorphic encryption, Parallel computing, Overhead (engineering), Encryption, Cloud computing, Computation, Algorithm, Computer network, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1Per-year citation counts (last 5 years)
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.CraterLake, | 175 |
| abstract_inverted_index.Homomorphic | 8 |
| abstract_inverted_index.computation | 180 |
| abstract_inverted_index.management, | 116 |
| abstract_inverted_index.operations, | 38 |
| abstract_inverted_index.operations. | 46 |
| abstract_inverted_index.accelerating | 124 |
| abstract_inverted_index.accelerator. | 181 |
| abstract_inverted_index.bottlenecks: | 70 |
| abstract_inverted_index.ciphertexts. | 62 |
| abstract_inverted_index.computations | 20 |
| abstract_inverted_index.parallelism, | 108 |
| abstract_inverted_index.state-of-art | 177 |
| abstract_inverted_index.Additionally, | 139 |
| abstract_inverted_index.computational | 73, 93 |
| abstract_inverted_index.concern/design | 6 |
| abstract_inverted_index.consideration. | 7 |
| abstract_inverted_index.implementation | 136 |
| abstract_inverted_index.implementations | 152 |
| abstract_inverted_index.energy-efficient | 121 |
| abstract_inverted_index.multiplications. | 156 |
| abstract_inverted_index.privacy-preserving | 16, 158 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 8 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8500000238418579 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile |