Comments (6)
I am puzzled by the same problem, have you solved it by changing the version of CUDA? Thanks!
from deepbind.
Nope. I tried running it with cuda 8. It gave me an "ld" linking error on the smat cu file
from deepbind.
maybe the code isn't compatible for higher cuda versions.
from deepbind.
I tried running makefile with cuda7.0 on ubuntu16.04, then the new error came out:
/usr/include/string.h: In function ‘void* __mempcpy_inline(void*, const void*, size_t)’:
/usr/include/string.h:653:42: error: ‘memcpy’ was not declared in this scope
return (char *) memcpy (__dest, __src, __n) + __n;
^
makefile:230: recipe for target '../build/release/obj/SMAT_CUDA/reduce.o' failed
make: *** [../build/release/obj/SMAT_CUDA/reduce.o] Error 1
I think it's also due to the version of cuda.
from deepbind.
Doing something similar to this link solved the issue for me. I'm compiling with CUDA 9.2 as well. However, still haven't found a solution of the error from kangaroo_smat.
from deepbind.
Hello ljyang.
Could you explain what exactly you did to get it to work?
Best,
from deepbind.
Related Issues (8)
- demo_convnet.py run with error for the reason of libsmat_cudnn.so HOT 1
- deepbind_train_dream5.py fails on test step due to CUDA error in Memcpy2DAsync HOT 2
- Error in kangaroo_smat make HOT 2
- retraining using different model architecture
- AssertionError: CUDA error: no kernel image is available for execution on the device.
- Error message when installing DeepBind
- http://tools.genes.toronto.edu/deepbind/ offline? HOT 5
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