NVIDIA/k8s-device-plugin

Features

• Device Plugin Integration - Implements the Kubernetes device plugin interface to enable the cluster to recognize and partition hardware accelerators.
• Multi-Tenant Hardware Sharing - Enables multiple concurrent containers to share a single physical graphics device using virtualization and partitioning strategies.
• Hardware Resource Exposure - Provides standardized interfaces for accessing host hardware accelerators within container environments.
• Node Metadata Labeling - Automatically applies metadata tags to cluster nodes based on detected hardware capabilities to facilitate intelligent workload placement.
• GPU Resource Orchestrators - Identifies available accelerators on cluster nodes and reports them to the scheduler for request fulfillment.
• GPU Workload Orchestration - Allocates specific hardware accelerators to containers based on resource requests defined in the workload specification.
• Hardware Discovery - Scans and identifies physical hardware to prepare accelerators for automated cluster-wide advertisement.
• Hardware Segment Partitioning - Logically divides monolithic hardware units into isolated segments to allow multiple independent containers to share a single device.
• Hardware Capability Labeling - Generates and applies metadata labels to nodes to describe specific hardware capabilities and sharing strategies.
• Hardware Availability Detection - Scans local host paths and system files to identify and verify the presence of physical accelerators.
• Hardware Accelerator Time-Slicing - Interleaves execution cycles of hardware accelerators across multiple workloads to maximize GPU utilization.
• Hardware Resource Partitioning - Divides physical graphics hardware into isolated segments to allow multiple concurrent workloads to share a single device.
• Hardware Accelerator Discovery - Scans local host filesystems and system paths to enumerate available accelerators for registration with the cluster scheduler.
• Hardware Device Exposure - Selectively maps host device nodes into isolated container namespaces to provide direct compute access.
• Host-to-Container Path Mappings - Mounts physical hardware character devices from the host filesystem directly into container namespaces for low-latency access.
• gRPC Plugin Implementations - Implements the gRPC remote procedure call interface to register hardware resources with the cluster orchestrator.
• Memory Exchange Mappings - Maps device nodes directly into container namespaces to enable specific memory exchange channels for workloads.
• Hardware Acceleration - Supports exposing host hardware resources to containerized workloads for compute-intensive task scheduling.
• Communication Channels - Configures low-level logical paths for reliable data exchange between hardware accelerators.
• Multi-Instance GPU Passthroughs - Exposes multi-instance GPU (MIG) compute instances into containers to provide isolated hardware environments.
• High-Performance Computing - Configures container environments to access specialized hardware and memory channels for demanding scientific tasks.
• MPS Resource Partitioning - Partitions memory and compute capacity using a control daemon to enforce explicit limits for multiple concurrent workloads.
• Container Resource Injections - Maps memory exchange channels and device nodes into container environments based on hardware discovery.
• GPU Health Monitors - Monitors GPU health and availability on cluster nodes to facilitate accurate container resource requests.

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