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Awesome GitHub RepositoriesHardware Slice Virtualization
Partitioning large physical accelerator pods into smaller, independent virtual compute slices.
Distinct from Compute Graph Slicing: No candidate covers the partitioning of physical hardware pods into virtual slices; others focus on graph slicing or memory slicing.
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Awesome Hardware Slice Virtualization GitHub Repositories
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- tensorflow/tpu
tensorflow/tpu
5,281Ver en GitHubThis repository provides a collection of reference implementations, toolkits, and orchestration tools for training and deploying large-scale AI models on Cloud TPU hardware. It serves as a framework for managing the lifecycle of accelerator clusters, including hardware orchestration and the provisioning of high-performance compute infrastructure for machine learning workloads. The project specifically enables the pre-training of foundation models, large language models, and complex reasoning architectures through distributed training toolkits and multi-host scaling recipes. It further provide
Partitions large compute pods into smaller independent slices to support multiple independent machine learning workloads.
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