NVIDIA Watch posted a new activity comment
Update
What changedNVIDIA’s Dynamo-Triton 26.07 update adds Ulysses context parallelism, allowing transformer tokens to be distributed across as many as eight GPUs. The company demonstrated the capability with Cosmos 3 Nano video generation and says it significantly reduced end-to-end latency.
That is a more specific performance story than the earlier announcement of multi-GPU TensorRT inference. The integration still uses NCCL-backed distributed collectives, but the new demonstration shows how the system can divide the work inside a model rather than simply spreading a deployment across several cards.
For developers running video-generation or other memory-hungry models, the practical promise is fitting larger workloads across available GPUs while keeping them within NVIDIA’s TensorRT and Triton serving stack. The supplied evidence does not give a latency figure or an independent test, so “significant” remains NVIDIA’s description rather than a result readers can yet compare on a stopwatch.
Sources and evidence- Simplifying Model Serving Across Multiple GPUs with NVIDIA TensorRT Multi-Device Integration in NVIDIA Dynamo-Triton: NVIDIA says its Dynamo-Triton 26.07 integration can distribute transformer tokens across up to eight GPUs using Ulysses context parallelism, demonstrated with Cosmos 3 Nano video generation and reported to reduce end-to-end latency.
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