THCudaCheck FAIL file=/home/dhhorka/libs/pytorch/aten/src/THC/THCTensorMathCompareT.cuh line=69 error=48 : no kernel image is available for execution on the device.
I compiled from source pytorch 1.1 (using the code tagged as v1.1.0). The thing is, I am running this code in a remote server where there are two different nodes with different gpus architectures. I compiled the code in the node that contains old gpus . WhenI execute the pytorch script on these GPU’s the code code is working properly but… when I execute this code on the new gpus (2080ti) I get the previous error.
I tried to compile pytorch in the new gpus and then the code It is working on the new gpus but it does not work in the old gpus… I am using cuda 10. Is there anyway to make it work in both GPUs?
P.S: I do not put a category to this topic because I am not pretty sure witch one fits better in this case.
Thanks for pointing out the error. This is what happened to me indeed.
More specifically, I was running a script on a remote cluster using GPUs and retrieving some GPU tensors. While trying to read this tensors in my local computer (which only supports CPU tensors) I encountered this error.
I’m now converting these tensors while on the cluster.