CODEWITHSUNDEEP
machine-learningnvidiaamazon-sagemakermxnet
Iyyappan Amirthalingam
Iyyappan Amirthalingam

Reputation: 324

AWS SageMaker MXNet USE_CUDA=1

I am using the AWS ml.p2.xlarge sagemaker instance and conda_amazonei_mxnet_p36 kernel after install MXnet CUDA

!pip install mxnet-cu101

when I try to run the following code

mx_tfidf = mx.nd.sparse.array(tfidf_matrix, ctx=mx.gpu())

I am getting the following error

MXNetError: [19:54:53] src/storage/storage.cc:119: 
Compile with USE_CUDA=1 to enable GPU usage

Please help me to resolve the issue

nvidia-smi

nvidia configuration as follows

Upvotes: 0

Views: 1148

Answers (1)

Olivier Cruchant
Olivier Cruchant

Reputation: 4037

please consider using the other Jupyter kernels conda_mxnet_p27 or conda_mxnet_p36. The kernel you use - conda_amazonei_mxnet_p36 - is primarily designed for local testing of the Amazon Elastic Inference hardware accelerator, (exposed as mx.eia() hardware context in mxnet), and presumably doesn't come with the mx.gpu() context enabled.

Upvotes: 1

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