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Monarch now supports running distributed training workloads on Kubernetes clusters. The new KubernetesJob API connects to pre-provisioned GPU pods managed by the https://github.com/meta-pytorch/monarch-kubernetes/ repository, enabling seamless multi-node DDP training on Kubernetes.
Key Capabilities:...
This release focuses on correctness, robustness, and operational maturity. Major improvements span supervision and shutdown semantics, logging and observability, Kubernetes readiness, SPMD workflows, test hygiene, and build compatibility. Monarch is now more predictable under failure, easier to debug, and better suited for long-running and large-scale...
🦋 Monarch v0.1.0 — Initial Release We’re excited to announce the first public release of Monarch, a distributed programming framework for PyTorchbuilt around scalable actor messaging and direct memory access. Monarch brings together ideas from actor-based concurrency, fault-tolerant supervision, and high-performance tensor communication to make distributed training simpler, more explicit, and f...
First Monarch Release! https://pypi.org/project/torchmonarch/0.0.0/