Comments (1)
At this point, it is not possible and not reasonable to change the polynomial degree.
- Degree 1024 is chosen in the TFHE paper. Decreasing it compromises security, while increasing it is less efficient.
- Code in this library is optimized for degree 1024 only.
If you are only interested in accelerating polynomial arithmetic operations, the cuHE library supports larger polynomial degrees.
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Related Issues (16)
- Ctxt destructor fails when using cpu HOT 2
- error: use of deleted function HOT 2
- how to run this library and run code HOT 1
- user@HP-Z8-G4-Workstation:~/cuFHE-master/cufhe/python$ python test_circuits_gpu.py Traceback (most recent call last): File "test_circuits_gpu.py", line 23, in <module> import lib.fhe_gpu as fhe File "/home/user/cuFHE-master/cufhe/python/lib/fhe_gpu.py", line 59 fhe.Encrypt(ctxt.ctxt_, ptxt, prikey) ^ TabError: inconsistent use of tabs and spaces in indentation
- Typo in definition of TLWE key HOT 1
- Does cuFHE support multi-GPU computation?
- test_api_gpu fails every time with CUDA_EXCEPTION_15 HOT 4
- make cpu fails if nvcc is not installed
- CUDA Compilation error
- WriteCtxtToFile
- i/o problem
- Polynomial Multiplication time
- test_api_gpu FAIL every time. Build seems alright (compiles and runs) HOT 14
- SIGSEGV for test_api_cpu HOT 1
- Use of private key to encrypt HOT 2
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