Invited: Accelerating Fully Homomorphic Encryption with Processing in Memory
Fully homomorphic encryption (FHE) provides a promising solution for future computing needs by allowing privacy-preserving computation. However, its practical use has been limited by the huge latency overhead it incurs while computing. This is primarily due to the huge size of encrypted data and int...
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| Veröffentlicht in: | 2021 58th ACM/IEEE Design Automation Conference (DAC) S. 1335 - 1338 |
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IEEE
05.12.2021
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| Abstract | Fully homomorphic encryption (FHE) provides a promising solution for future computing needs by allowing privacy-preserving computation. However, its practical use has been limited by the huge latency overhead it incurs while computing. This is primarily due to the huge size of encrypted data and intermediate processing required to compute on it. In this paper, we present insights into the benefits of accelerating FHE with processing in-memory (PIM). PIM is an excellent match for the FHE since it provides extensive parallelism, in-situ operations, and bit-level granularity. We present FHE-PIM, which implements basic polynomial primitives with PIM and uses them to accelerate key FHE operations in memory. This can significantly make the time-consuming procedure of FHE bootstrapping faster in memory. We compare the speedup of FHE-PIM for various FHE operations with their CPU implementations. FHE-PIM can achieve an estimated average throughput improvement of 88,397 \times as compared to CPU for FHE arithmetic operations. |
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| AbstractList | Fully homomorphic encryption (FHE) provides a promising solution for future computing needs by allowing privacy-preserving computation. However, its practical use has been limited by the huge latency overhead it incurs while computing. This is primarily due to the huge size of encrypted data and intermediate processing required to compute on it. In this paper, we present insights into the benefits of accelerating FHE with processing in-memory (PIM). PIM is an excellent match for the FHE since it provides extensive parallelism, in-situ operations, and bit-level granularity. We present FHE-PIM, which implements basic polynomial primitives with PIM and uses them to accelerate key FHE operations in memory. This can significantly make the time-consuming procedure of FHE bootstrapping faster in memory. We compare the speedup of FHE-PIM for various FHE operations with their CPU implementations. FHE-PIM can achieve an estimated average throughput improvement of 88,397 \times as compared to CPU for FHE arithmetic operations. |
| Author | Rosing, Tajana Simunic Gupta, Saransh |
| Author_xml | – sequence: 1 givenname: Saransh surname: Gupta fullname: Gupta, Saransh email: sgupta@ucsd.edu organization: University of California,Computer Science and Engineering,San Diego La Jolla,USA – sequence: 2 givenname: Tajana Simunic surname: Rosing fullname: Rosing, Tajana Simunic email: tajana@ucsd.edu organization: University of California,Computer Science and Engineering,San Diego La Jolla,USA |
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| Snippet | Fully homomorphic encryption (FHE) provides a promising solution for future computing needs by allowing privacy-preserving computation. However, its practical... |
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| SubjectTerms | Arithmetic Cryptography Design automation fully homomorphic encryption Logic gates Parallel processing processing in-memory secure computation secure learning Throughput |
| Title | Invited: Accelerating Fully Homomorphic Encryption with Processing in Memory |
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