GPGPU-WG KnowledgeBase - Batch Schedulers - SchedulerScenarios - GPUOnlyQueue

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Single GPGPU per node

A simple batch setup that assumes a physical node and its componenent GPGPU card expose a single Job Slot would simplify Resource Centre setup. Each GPGPU node could be partitioned from the non-GPGPU nodes using an access-control-list. However, most modern physical nodes contain and expose multiple CPU-cores to the batch system. If the physical system supports Virtualisation, a CPU-core could be allocated to the GPU on the phsical node, and a single virtual machine could expose the remainder of the job slots. For example: Assume the physical host (wn1) has 8-cores, we can configure the node to declare (in torque) "np=1" to the batch system. If we create a VM with "np=7", then all cores can be allocated to the batch system.


The major drawback of taking the gpgpu queue approach is that:

  • There is a direct relationship between the number of available CPU cores to the number of GPGPUs.
    • This hinders jobs that require more CPUs than there are GPGPUs
    • It cannot deal with jobs requiring a mixture of just CPU and CPU/GPU pairs "-lnodes=1+nodes=2:ppn=2:gpus=2" without the risk or wasting/blocking resources.


Options for RC

  • Define a queue with name tagged gpgpu
  • Apply the usual VO restrictions on the queue
  • Define an ACL that partitions these nodes from non-GPGPU nodes
  • Publish basic SoftwareEnvironment (eg. CUDA, CUDA-5, CUDA-5.5)
  • Ensure the WN environment is configured with all relevant GPGPU Software development kit installed.

JDL Example 1

This example simply requests 1 job slots from any queue matching "*gpgpu$". This is equivalent to the PBS -l nodes=1

[
Type="Job";

JobType="Normal";
Executable = "myScript.sh";
StdOutput = "std.out";
StdError = "std.err";
InputSandbox =  {"myScript.sh"};
Requirements =  ( RegExp("*gpgpu$", other.GlueCEUniqueID) && Member("CUDA", other.GlueHostApplicationSoftwareRunTimeEnvironment);
]

JDL Example 2

This example simply requests 2 job slots from any queue matching "*gpgpu$". The allocated cores may be on distinct hosts, so we cannot assume that the the GPGPU application will see or can enumerate both GPGPU cards. This is equivalent to the PBS -l nodes=2

[
Type="Job";
JobType="Normal";
CPUnumber=2;
# myScript.sh must take responsibility for executing the GPGPU application on both the allocated core/GPGPU pairs!
Executable = "myScript.sh";  
StdOutput = "std.out";
StdError = "std.err";
InputSandbox =  {"myScript.sh"};
Requirements =  ( RegExp(".*gpgpu$", other.GlueCEUniqueID) && Member("CUDA", other.GlueHostApplicationSoftwareRunTimeEnvironment);
]

Multiple GPGPUs per Physical Node

Similar to the Virtualisation example above, a physical node with N-gpgpu cards could be configured with:

np=#NUM_OF_GPGPUS

A virtual machine could the remaining number of cores:

np=#NUM_OF_CORES-#NUM_OF_GPGPUS job slots


The drawback of this scheme is that we need to develop a scheme to ensure that jobs from distinct users cannot interfere with each other. User code could try to enumerate and use all the GPGPUs on the node. This will have (potentially job-catastrophic) unintended side-effects, so we need some mechanism to ensure that a user-job does not consume more than its allocation.

The VT must investigate ways of mitigating cross-job contamination, such as linux cgroups and cpusets.


JDL Example 3 JDL - multiple GPGPU per node

This example should ensure 2 GPGPUs on the same host. Again, if there are more than 2 GPGPUs on the node, we need to ensure that other user processes do no interfere with each other. This is equivalent to the PBS -l nodes=1:ppn=2. In reality 2 cores are actually allocated to the job, so there is a potential waste of resources.

[
Type="Job";
JobType="Normal";
CPUnumber=2;
SMPgranularity=2;
# We assume that the GPGPU application will take responsibilty for enumerating both GPGPU devices
Executable = "myScript.sh";  
StdOutput = "std.out";
StdError = "std.err";
InputSandbox =  {"myScript.sh"};
Requirements =  ( RegExp(".*gpgpu$", other.GlueCEUniqueID) && Member("CUDA", other.GlueHostApplicationSoftwareRunTimeEnvironment);
]