Comments (2)
The CUDA backend does not support mixed precision (it needs things like mixed precision matrix-vector product, and CuSparse did not have those when the backend was implemented, not sure about now).
You can use the VexCL backend for amgcl with CUDA as backend for VexCL.
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constructing the preconditioner is done on CPU, but why do we need to specify backend type for amg precondtioner?
The preconditioner is constructed on the CPU and then moved into the specified backend for application.
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Related Issues (20)
- input GPU data directly into CUDA solver HOT 2
- cuda compute error HOT 2
- Compilation AMGCL problem on AMD architectur with scotch library HOT 2
- ...\boost\preprocessor\control\iif.hpp|25|error: 'BOOST_PP_IIF_0' was not declared in this scope| HOT 11
- Convergence issue with gmres + Eigen backend HOT 1
- blocksystems with different sized blocks HOT 2
- how to use amgcl with gpu HOT 3
- First run slow with CUDA HOT 3
- Performance with AMGCL HOT 1
- No Instance of Constructor for cusparse_ilu0 under Single Precision (float32) HOT 5
- MPI rebuild example HOT 5
- profiler tic toc in parallel code HOT 1
- scoped_ticker HOT 1
- How does the AMGCL library run on windows10 HOT 1
- Can amgcl support for a Schur solver which's matrix are mix block size? HOT 2
- Could Not find Boost: missing: program_options HOT 4
- I do not know how to tune the amgcl to make solver converged HOT 3
- Julia and C Wrapper HOT 2
- Get NaN on floating point precision solver HOT 2
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