HEPCloud: An FPGA-Based Multicore Processor for FV Somewhat Homomorphic Function Evaluation

74 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

HEAX: An Architecture for Computing on Encrypted Data (2019, methodology): “that focus on non-CKKS schemes. In what follows, we briefly review the research effort related to FPGA, ASIC, and GPU-based acceleration for non-CKKS schemes. HardwareAccelerationfornon-CKKSSchemes.In[53], a system based on FPGA is proposed for BFV scheme to process ciphertext polynomial sizes of 21”
HEAX: High-Performance Architecture for Computation on Homomorphically Encrypted Data in the Cloud (2019, methodology): “As has been shown by prior art [66, 67], leveraging off-chip memory to store intermediate results significantly reduces the overall performance due to high delays between subsequent reads and writes.”
FPGA-Based High-Performance Parallel Architecture for Homomorphic Computing on Encrypted Data (2019, methodology): “In [20] a single core memory-efﬁcient NTT algorithm was constructed that overcomes the second bottleneck by keeping the two required coefﬁcients ( A [ k + j ] and A [ k + j + m/ 2] ) together in a same word of the memory.”
Implementation and Performance Evaluation of RNS Variants of the BFV Homomorphic Encryption Scheme (2019, methodology): “For instance, the FPGA-based implementation HEPCloud in [18] of the textbook BFV scheme computed a homomorphic multiplication for n ¼ 215 and log 2q ¼ 1; 228 in 26.67 seconds (with 3.36 seconds spent on the computation and the rest on the off-chip memory access).”