IBM Data and AI Ideas Portal for Customers


This portal is to open public enhancement requests against products and services offered by the IBM Data & AI organization. To view all of your ideas submitted to IBM, create and manage groups of Ideas, or create an idea explicitly set to be either visible by all (public) or visible only to you and IBM (private), use the IBM Unified Ideas Portal (https://ideas.ibm.com).


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Specific links you will want to bookmark for future use

Welcome to the IBM Ideas Portal (https://www.ibm.com/ideas) - Use this site to find out additional information and details about the IBM Ideas process and statuses.

IBM Unified Ideas Portal (https://ideas.ibm.com) - Use this site to view all of your ideas, create new ideas for any IBM product, or search for ideas across all of IBM.

ideasibm@us.ibm.com - Use this email to suggest enhancements to the Ideas process or request help from IBM for submitting your Ideas.

IBM Employees should enter Ideas at https://ideas.ibm.com


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Status Delivered
Workspace Spectrum Conductor
Components Version 2.4.1
Created by Guest
Created on Jul 1, 2020

RELATED IDEAS

Running only CPU based model via WMLA

We are using WMLA to run GPU based jobs fine and also able to scale across the cluster. However, we are trying to run a model only on CPU (not on GPU) using the WMLA framework. We have prepared a model which runs only on CPU and not at all sending it to GPU.

Also, while submitting a job, we did not define “gpuPerWorker” parameter. However, what we see is that the model is getting GPU slots allocated first, based on availability, and then CPU slot allocation starts once the GPU slots are over.

For Example:
Our current configuration:
Total CPU slots: 12*96
Total GPU slots: 48

Resource available before submitting the WMLA job:
Total CPU slots: 10*96
Total GPU slots: 35

We submitted a job with below params:
'maxParalleJobNum': 120

Did not define --gpuPerWorker param while submitting the job.

Our observation:
The job gets allocated to 35 GPU slots first and then starts occupying CPU slots for remaining 85 parallel tasks, the job stays in WAITING state for some time here for CPU slot allocation.

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