Scaling AI Inference Across Multiple GPUs Using NVIDIA TensorRT with Multi-Device Inference Support
NVIDIA introduces multi-device inference support in TensorRT to help scale generative AI workloads across multiple GPUs without losing key optimizations, addressing memory and compute limitations of single GPUs.
Generative AI workloads are rapidly outgrowing the memory and compute budget of single GPUs. For inference developers building media generation pipelines, the challenge is scaling across multiple devices without sacrificing the critical optimizations—like kernel fusions, memory planning, and quantization—that NVIDIA TensorRT delivers for production deployments. Multi-device inference support in TensorRT enables developers to efficiently distribute AI inference workloads across multiple GPUs, overcoming memory and compute constraints of single devices. This capability is essential for scaling generative AI models in production environments, ensuring high performance and resource utilization.