Open flaviobeck opened 5 years ago
Looks like nvcc crashed. Have you tried CUDA 10.0 instead of 10.1?
I have darknet working with CUDA 10.1. Had some other issues. But to give you hope it should work.
I am on the master branch. I have not freshened the project in a while. Hash is 80d9bec20f0a44ab07616215c6eadb2d633492fe so perhaps try that specific version.
Like you ... since I see this in your output ... we both have edited the Makefile and updated paths to cuda near line 50
COMMON+= -DGPU -I/usr/local/cuda-10.1/include/
LDFLAGS+= -L/usr/local/cuda-10.1/lib64 -lcuda -lcudart -lcublas -lcurand
Then I got errors about could not find cuda near the end of the build.
-L/usr/local/cuda-10.1/lib64 -lcuda -lcudart -lcublas -lcurand -lstdc++
/usr/bin/ld: cannot find -lcuda
collect2: error: ld returned 1 exit status
Makefile:85: recipe for target 'libdarknet.so' failed
make: *** [libdarknet.so] Error 1
Fixed the above by adding a symlink to the cuda library I found in linux-gnu folder.
cd /usr/local/cuda-10.1/lib64
sudo ln -s /usr/lib/x86_64-linux-gnu/libcuda.so.418.39 libcuda.so
The build worked fine and I was able to run the example below at about 75 times faster than on the system CPU:
./darknet detect cfg/yolo.cfg yolo.weights data/dog.jpg
I am on Ubuntu 18.04 I got most of my tools (compilers, and libraries)l from following the instructions for OpenCV 4.0.1 build. Those are found below. Perhaps it is a compiler version or make issue?
https://github.com/spmallick/learnopencv/blob/master/InstallScripts/installOpenCV-4-on-Ubuntu-18-04.sh
omg!! It works!!! thanks aerobiotic
I tried the above command. Still not working!!. Please help
my version cudnn-10.1-linux-x64-v7.6.5.32.tgz Just replace at /src/gemm.c:232: cudaThreadSynchronize() with cudaDeviceSynchronize()
Hello, I have installed darknet and compile for CPU. it works fine!
After, I have installed cuda:
When I try to compile again (Changed Makefile GPU=1), I have the following error:
Still running with CPU: ./darknet detect cfg/yolov3.cfg yolov3.weights data/dog.jpg
how to fix this error to compile for CUDA ?