Resource connector enhancements

LSF resource connector now allows you to create Google Compute Cloud instances with GPU resources. This allows you to run GPU jobs on Google Compute Cloud host providers.

Use the new gpuextend attribute to define the GPU topology on the template host for the Google Compute Cloud host provider. To define the GPU topology, edit the googleprov_templates.json file and specify the gpuextend attribute. This attribute is a string in the following format:

"key1=value1;key2=value2;..."

LSB_GPU_NEW_SYNTAX=extend must be defined in the lsf.conf file for the gpuextend attribute to take effect.

You can also define the specific type and number of GPUs for the instance. Specify the new gpuType attribute to define the type of GPU, and the new gpuNumber attribute to define the number of GPUs on the instance. LSF resource connector currently supports the following types of GPUs:

• nvidia-tesla-k80
• nvidia-tesla-p100
• nvidia-tesla-p4
• nvidia-tesla-p100-vws
• nvidia-tesla-p4-vws

In previous versions of LSF, affinity jobs did not generate demand (which triggers the LSF resource connector to create the required cloud instances) because the templates did not define CPU topology. LSF resource connector can now generate demand for affinity jobs, and when LSF resource connector provisions the cloud instances, affinity information is collected and cached. This means that the LSF scheduler can dispatch jobs to the cloud instances with affinity information that satisfies the job affinity resource requirements.