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Scheduling Policies#

NVIDIA vGPU for Compute offers a range of scheduling policies that allow administrators to customize resource allocation based on workload intensity and organizational priorities, ensuring optimal resource utilization and alignment with business needs. These policies determine how GPU resources are shared across multiple VMs and directly impact factors like latency, throughput, and performance stability in multi-tenant environments.

For workloads with varying demands, time slicing plays a critical role in determining scheduling efficiency. The vGPU scheduler time slice represents the duration a VM’s work is allowed to run on the GPU before preemption. A longer time slice maximizes throughput for compute-heavy workloads, such as CUDA applications, by minimizing context switching. In contrast, a shorter time slice reduces latency, making it ideal for latency-sensitive tasks like graphics applications.

NVIDIA provides three scheduling modes, each designed for different workload requirements and environments. For more information, refer to the vGPU Schedulers documentation.

Table 148 vGPU Scheduling Modes#
Mode	Behavior	Workload fit
Best Effort	Default scheduler. VMs share GPU time without strict fairness guarantees.	Mixed workloads where latency is secondary to throughput
Equal Share	Each VM receives an equal share of GPU time in round-robin fashion.	Homogeneous multi-tenant environments
Fixed Share	Each VM receives a fixed percentage of GPU time configured by the administrator.	Workloads with known, predictable resource requirements

Refer to the Changing Scheduling Behavior for Time-Sliced vGPUs documentation for how to configure and adjust scheduling policies to meet specific resource distribution needs.