{section: Advertise the GPU}
 
-The availability of GPU resources must be advertised in the machine's ClassAd, in order for jobs that need GPUs to be matched with machines that have GPUs. The HTCondor =condor_gpu_discovery= tool is designed to assist in detecting GPUs and in providing configuration details that help to set up the advertisement of GPU information.
+The availability of GPU resources must be advertised in the machine's ClassAd, in order for jobs that need GPUs to be matched with machines that have GPUs. The HTCondor _condor_gpu_discovery_ tool is designed to assist in detecting GPUs and in providing configuration details that help to set up the advertisement of GPU information.
 This tool detects CUDA and OpenCL devices, and it outputs a list of GPU identifiers for all detected devices.
 
-HTCondor has a general mechanism for declaring user-defined slot resources. GPUs are a user-defined slot resource, so use this mechanism to define a resource called 'GPUs'. This resource type name, 'GPUs,' is case insensitive, but you must be consistent about the plural. HTCondor considers 'GPU' to be a different resource type than 'GPUs'.  We recommend the use of 'GPUs' for GPU custom resources.
+HTCondor has a general mechanism for declaring user-defined slot resources. GPUs are a user-defined slot resource, so this mechanism is used to define a resource. These examples use the resource type name =GPUs=. These resource type names are case insensitive, but all characters within the name are significant,
+so be consistent.
 
-To define 'GPUs' as a custom resource simply add the following statements to the configuration on your execute node.
+Define =GPUs= as a custom resource by adding the following definitions to the configuration of the execute node.
 
     MACHINE_RESOURCE_GPUs = $(LIBEXEC)/condor_gpu_discovery -properties
     ENVIRONMENT_FOR_AssignedGPUs = CUDA_VISIBLE_DEVICES, GPU_DEVICE_ORDINAL
 
 
-The first line tells HTCondor to run the condor_gpu_discovery tool, and use its output to define a custom resource called 'GPUs'.
+=MACHINE_RESOURCE_GPUs= tells HTCondor to run the _condor_gpu_discovery_ tool, and use its output to define a custom resource called =GPUs=.
 
-The second line tells HTCondor to publish the AssignedGPUs for a slot in the job's environment using the environment variables =CUDA_VISIBLE_DEVICES= and =GPU_DEVICE_ORDINAL=. If you know for certain that your devices will be CUDA then you can omit =GPU_DEVICE_ORDINAL= in the configuration above.  If you know for certain that your devices are OpenCL only, then you can omit =CUDA_VISIBLE_DEVICES=. In addition =AssignedGPUs= will always be published into the job's environment as =_CONDOR_AssignedGPUs=, so the second line above is not strictly necessary, but it is recommended.
+=ENVIRONMENT_FOR_AssignedGPUs= tells HTCondor to publish the value of machine ClassAd attribute =AssignedGPUs= for a slot in the job's environment using the environment variables =CUDA_VISIBLE_DEVICES= and =GPU_DEVICE_ORDINAL=. If you know for certain that your devices will be CUDA, then you can omit =GPU_DEVICE_ORDINAL= in the configuration above.  If you know for certain that your devices are OpenCL only, then you can omit =CUDA_VISIBLE_DEVICES=. In addition, =AssignedGPUs= will always be published into the job's environment as =_CONDOR_AssignedGPUs=, so the second line above is not strictly necessary, but it is recommended.
 
-The output of the condor_gpu_discovery tool will report =DetectedGPUs= and list the GPU id of each one.  GPU ids will be CUDA<n> or OCL<n> where <n> is an integer, and CUDA or OCL indicates whether the CUDA library or the OpenCL library is used to communicate with the device.
+The output of the _condor_gpu_discovery_ tool will report =DetectedGPUs= and list the GPU id of each one.  GPU ids will be CUDA<n> or OCL<n>, where <n> is an integer, and CUDA or OCL indicates whether the CUDA library or the OpenCL library is used to communicate with the device.
 
-The -properties argument in the command above tells condor_gpu_discovery to also list significant attributes of the device(s). These attributes will then be published in the slot ads.
+The =-properties= argument in the command above tells _condor_gpu_discovery_ to also list significant attributes of the device(s). These attributes will then be published in the slot ClassAds.
 
-This is typical output of condor_gpu_discovery
+Here is typical output of _condor_gpu_discovery_
 {code}
 > condor_gpu_discovery -properties
 DetectedGPUs="CUDA0, CUDA1, CUDA2, CUDA3"