LiveR enables live reconfiguration for elastic LLM training by asynchronously preparing new parallel worlds and streaming reshaped model state over interconnects, reducing downtime to seconds and achieving 14-23x faster reconfiguration than checkpoint/restart.
Usp: A unified sequence parallelism approach for long context generative ai
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Inferix provides an optimized inference engine for semi-autoregressive block-diffusion decoding to support high-quality, variable-length video generation in world simulation applications.
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LiveR: Fine-Grained Elasticity via Live Reconfiguration for Model Training
LiveR enables live reconfiguration for elastic LLM training by asynchronously preparing new parallel worlds and streaming reshaped model state over interconnects, reducing downtime to seconds and achieving 14-23x faster reconfiguration than checkpoint/restart.
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Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation
Inferix provides an optimized inference engine for semi-autoregressive block-diffusion decoding to support high-quality, variable-length video generation in world simulation applications.