Allan Menezes amenezes007 at
Thu Apr 25 20:45:39 CEST 2013

Dear Tobjorn, Todd,

    I had brought this question up long before of using specifcally CUDA and NVIDIA  GPUs

to accelerate some GMP functions. To compromise one can create a hybrid gmp library where some

gmp functions are executed on the host machines CPU and some on the GPU and some perhaps a 

combination of both. For example there exists a GMP port of some mpf fumctions in CUMP (google

cump and cuda) . But my much earlier suggestion was using par4all software (google par4all)

to change carefully the generic subdirectory of C routines in the gmp library by the pat4all software

into CUDA routines which can be compiled with nvcc. Par4all takes as input a C program and outputs 

a paralellized .cu  file. On the other hand for AMD Graphic Cards  or NVIDIA with OpenCl one could use

SnuCl( google snucl opencl).

Par4all would only compile source C files into .cu which would could still be under the Creative Commons

Licensing paradigm and the end user with a suitable configure could compile the the hybrid GMP library

on his/her/other machine using ones on install CUDA software. Hence the branch Hybrid GMP library source as distributed

would be suitably open source.

Notably a good high end GPU would be the Geforce TITAN for about $1000CDN which boasts a double precision

peak of 1.3 Teraflops and $.5 Teraflops single precision to test it on.


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