Multi-Instance GPU Support for ML Workloads with cnvrg.io on NVIDIA A100

Provision, allocate, monitor & manage MIG instances with cnvrg.io meta-scheduler

Deliver Accelerated ML Workloads of All Sizes with Multi-Instance GPU (MIG)

cnvrg.io is the first ML platform to integrate the NVIDIA multi-instance GPU (MIG) functionality of the NVIDIA A100 Tensor Core GPU. The cnvrg.io MIG support is certified for NVIDIA DGX A100 systems as part of the NVIDIA DGX-Ready Software program and delivers on-demand access to MIG instances of one or more NVIDIA A100 GPUs for ML/DL workloads in one click. cnvrg.io delivers MLOps, utilization, assignment and scheduling of MIG resources for ML workloads.

Maximize GPU Utilization

Achieve up to 7X more GPU instances on a single NVIDIA A100 GPU and up to 56X more on the 8 A100 GPUs in NVIDIA DGX A100
Allocate right-sized GPU with guaranteed quality of service (QoS) for every job
Enable inference, training, and HPC workloads to run at the same time on a single GPU
Automate MIG pool management and make instances available immediately after job is completed

Accelerate ML Workflow

Deliver data scientists one click self-service access to MIG instances
Partition instances on-demand with pre-configured resource templates
Run simultaneous mixed workloads on independent instances
Automatically schedule containerized workloads within any MIG instance

Maintain Flexibility and Control

Track utilization and constantly monitor the pool of MIG resources
Set a library of pre-configured MIG instance templates of different sizes
Standardize UI for all compute resources for simplified use
Leverage meta-scheduling of MIG resources for optimized availability
Simplify utilization of NVIDIA A100 and resource management for IT and DevOps teams