local:A local installer is self-contained and includes every component. It is a large file that only needs to be downloaded from the internet once and can be installed on multiple systems. Local installers are the recommended type of installer with low- bandwidth internet connections, or where ...
Describe the bug This issue occurs on a SLURM cluster where worker nodes equipped with multiple GPU's are shared amongst users. GPU's are given slot number assignments (for example, on a node with 8 GPU's:0-7), and users may be assigned ...
Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device PCI Bus ID / PCI location ID: 1 / 0 Compute Mode: < Default (multiple host threads...
There is a specific case whereCUDA_VISIBLE_DEVICESis useful in our upcoming CUDA 6 release with Unified Memory (see mypost on Unified Memory). Unified Memory enables multiple GPUs and CPUs to share a single, managed memory space. Unified Memory between GPUs requires that the GPUs all supportpe...
(multiple host threads canuse::cudaSetDevice()with device simultaneously)>>Peer access from TeslaK20c(GPU0)->TeslaK20c(GPU1):Yes>Peer access from TeslaK20c(GPU1)->TeslaK20c(GPU0):Yes deviceQuery,CUDA Driver=CUDART,CUDA Driver Version=9.0,CUDA Runtime Version=8.0,NumDevs=2,Device0=Tesla K20c...
but it runs on GPU 0 ignoringCUDA_VISIBLE_DEVICES=1 Then I tried to use deepspeed launcher flags as explained here:https://www.deepspeed.ai/getting-started/#resource-configuration-multi-nodeand encountered multiple issues there: I think the--hostfilecl arg in the example are in the wrong plac...
There is a specific case whereCUDA_VISIBLE_DEVICESis useful in our upcoming CUDA 6 release with Unified Memory (see mypost on Unified Memory). Unified Memory enables multiple GPUs and CPUs to share a single, managed memory space. Unified Memory between GPUs requires that the GPUs all supportpe...
While adding GPU tests for SGD, it was noticed that this behavior leads to the following error messages when running a TensorFlow job with multiple GPUs on a single node: (pid=661) 2021-09-28 15:53:29.767329: I tensorflow/stream_executor/cuda/cuda_driver.cc:789] failed to allocate 734.56...