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Together AI boosts GPU cluster reliability with auto-repair and Slinky 1.0

Together AI has enhanced its GPU Clusters with new features focused on reliability and operational control for large-scale AI workloads. These updates include passive health checks to detect hardware and software degradations during active use, and an automated node repair system that suggests and executes actions like rebooting or reprovisioning faulty nodes, with human oversight for critical tasks. Additionally, Together AI has rebuilt its Slurm-on-Kubernetes stack using Slinky 1.0 to improve the stability and resilience of job scheduling. AI

IMPACT Enhances the operational stability of AI training and inference infrastructure.

RANK_REASON This is a product update for an existing service, not a new frontier release or significant industry event.

Read on Together AI blog →

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Together AI boosts GPU cluster reliability with auto-repair and Slinky 1.0

COVERAGE [1]

  1. Together AI blog TIER_1 English(EN) ·

    New in Together GPU Clusters: Reliability and control for production GPU clusters

    See how Together AI is improving production GPU clusters with passive health checks, node repair, stronger Slurm reliability, OIDC, and startup scripts.