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I first wrote a code for dense state matrix multiplication based on the seal library. After transplanting it to the pyfhel library, I found that the speed was much faster. So I tested the ciphertext multiplication of ckks locally.
Without performing re-linearization, the time consumption of 1000 multiplications was:
seal 48s c++
pyfhel 1s python
This makes me feel unbelievable. My cpu is i3-10100f. Does pyfhel use gpu acceleration?
The text was updated successfully, but these errors were encountered:
Based on previous questions and answers regarding the GPU support in Pyfhel, you can refer to these issues: #205, #171. All in all, Pyfhel depends on the underlying backend FHE libs, which have not yet been ported to GPU.
The multiplication in Pyfhel might be using parallelisation across several CPUs.
The multiplication happens in-place in Pyfhel, if you are running many multiplications in SEAL creating new objects every time you might be paying some extra computational cost.
I first wrote a code for dense state matrix multiplication based on the seal library. After transplanting it to the pyfhel library, I found that the speed was much faster. So I tested the ciphertext multiplication of ckks locally.
Without performing re-linearization, the time consumption of 1000 multiplications was:
seal 48s c++
pyfhel 1s python
This makes me feel unbelievable. My cpu is i3-10100f. Does pyfhel use gpu acceleration?
The text was updated successfully, but these errors were encountered: