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Tag: distributed training

  • Cloud Blog: Google is a Leader in the 2025 Gartner® Magic Quadrant™ for Container Management

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/containers-kubernetes/2025-gartner-magic-quadrant-for-container-management-leader/ Source: Cloud Blog Title: Google is a Leader in the 2025 Gartner® Magic Quadrant™ for Container Management Feedly Summary: We’re excited to share that Gartner has recognized Google as a Leader for the third year in a row in the 2025 Gartner® Magic Quadrant™ for Container Management, based on its Completeness of…

  • Cloud Blog: Taming the stragglers: Maximize AI training performance with automated straggler detection

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    Kurt Seifried
    in

    Source URL: https://cloud.google.com/blog/products/compute/stragglers-in-ai-a-guide-to-automated-straggler-detection/ Source: Cloud Blog Title: Taming the stragglers: Maximize AI training performance with automated straggler detection Feedly Summary: Stragglers are an industry-wide issue for developers working with large-scale machine learning workloads. The larger and more powerful these systems become, the more their performance is hostage to the subtle misbehavior of a single component.…

  • Cloud Blog: Introducing Ironwood TPUs and new innovations in AI Hypercomputer

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/compute/whats-new-with-ai-hypercomputer/ Source: Cloud Blog Title: Introducing Ironwood TPUs and new innovations in AI Hypercomputer Feedly Summary: Today’s innovation isn’t born in a lab or at a drafting board; it’s built on the bedrock of AI infrastructure. AI workloads have new and unique demands — addressing these requires a finely crafted combination of hardware…

  • Cloud Blog: Accelerate AI/ML workloads using Cloud Storage hierarchical namespace

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/storage-data-transfer/cloud-storage-hierarchical-namespace-improves-aiml-checkpointing/ Source: Cloud Blog Title: Accelerate AI/ML workloads using Cloud Storage hierarchical namespace Feedly Summary: As AI and machine learning (ML) workloads continue to grow, the infrastructure supporting them must evolve to meet their unique demands. Here on the Google Cloud Storage team, we’re committed to providing AI/ML practitioners with tools to optimize…

  • The Register: DeepMind working on distributed training of large AI models

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    by

    Kurt Seifried
    in

    Source URL: https://www.theregister.com/2025/02/11/deepmind_distributed_model_training_research/ Source: The Register Title: DeepMind working on distributed training of large AI models Feedly Summary: Alternate process could be a game changer if they can make it practicable Is distributed training the future of AI? As the shock of the DeepSeek release fades, its legacy may be an awareness that alternative approaches…