RELEASE · CODING · #2929
NVIDIA launches Workload Map to standardize Kubernetes AI workload descriptions
NVIDIA Workload Map (formerly Karta) provides a Kubernetes CRD and Go library that defines a common structural view of distributed workloads, plus a catalog of prebuilt definitions for frameworks such as JobSet, PyTorchJob, Ray, KServe, MPIJob, and others. Consumers including KAI Scheduler, NVIDIA Run:ai, and Elotl’s Nova can use these shared definitions to inspect, gang-schedule, and manage multi-pod AI workloads without framework-specific parsing code.
KEY POINTS
- NVIDIA Workload Map (formerly Karta) provides a Kubernetes CRD and Go library that defines a common structural view of distributed workloads, plus a catalog of prebuilt definitions for frameworks such as JobSet, PyTorchJob, Ray, KServe, MPIJob, and others.
- Consumers including KAI Scheduler, NVIDIA Run:ai, and Elotl’s Nova can use these shared definitions to inspect, gang-schedule, and manage multi-pod AI workloads without framework-specific parsing code.
- A shared, reusable workload description can speed integration of new AI frameworks across schedulers and platforms and reduce per-framework adapter work.
WHY IT MATTERS
A shared, reusable workload description can speed integration of new AI frameworks across schedulers and platforms and reduce per-framework adapter work.