Technical glossary for the resource allocation competitions: Difference between revisions

'''VGPU:''' Stands for virtual graphics processing unit (VGPU). One or more VGPUs can be assigned to Virtual Machines (VM) within a cloud environment. Each VGPU is seen as a single physical GPU device by the VM's operating system.

'''Reference GPU Unit (RGU):''' RGU is a unit measuring the amount of GPU resources that are used. It represents the "cost" of utilizing a particular GPU model, whose RGU value varies based on performance. For example: 1 GPU A100-40GB = 4.0 RGU; 1 GPU V100-16GB = 2.2 RGU; 1 GPU P100-12GB = 1.0 RGU.

'''Core equivalent:''' A core equivalent is a bundle made up of a single core and some amount of associated memory. In other words, a core equivalent is a core plus the amount of memory considered to be associated with each core on a given system. See detailed explanation [[Allocations_and_compute_scheduling|here]].

'''GPU year:''' a GPU year is the equivalent of using 1 GPU continuously for a full year or 12 GPU for a month.

'''RGU year:''' RGU year is a calculated value that results from multiplying GPU years times the RGU of a given GPU model. For example, 10 GPU years of an A100-40GB (which ''costs'' 4 RGU) equals 40 RGU years.  

'''VCPU year:''' same as CPU year, but for cloud.

'''VGPU year:''' same as GPU year, but for cloud.

'''Compute instances:''' These are instances that have a limited life-time and typically have constant high-CPU requirements for the instances life-time. They have also been referred to as ‘batch’ instances. These will be granted higher vCPU/Memory quotas since they are time-limited instances.