Jensen Huang Founder, President and CEO at NVIDIA | Official website
On March 27, 2024, NVIDIA announced significant advancements in AI acceleration for RTX PCs and workstations, as part of the AI Decoded series aimed at demystifying AI for users. The focus is on unlocking peak generations through the use of TensorRT, which enhances the performance of generative AI applications on local devices.
The integration of TensorRT with Stable Video Diffusion and ControlNets has been a game-changer, as highlighted by Automatic1111, "Stable Video Diffusion is now optimized for the NVIDIA TensorRT software development kit, which unlocks the highest-performance generative AI on the more than 100 million Windows PCs and workstations powered by RTX GPUs." This optimization allows users to refine generative outputs with more control and guidance.
Furthermore, the performance benefits of TensorRT are evident in benchmarks like the UL Procyon AI Image Generation, where a substantial 50% speedup was achieved on a GeForce RTX 4080 SUPER GPU compared to non-TensorRT implementations.
TensorRT not only boosts AI performance but also enables more efficient and precise AI experiences, doubling AI performance compared to other frameworks. Stable Video Diffusion and other popular generative AI models have seen significant speedups and enhancements with TensorRT integration.
The impact of TensorRT extends beyond Stable Video Diffusion, as seen in applications like DaVinci Resolve and Topaz Labs, where performance boosts of over 50% and up to 60% were achieved, respectively, on RTX GPUs.
In addition to performance gains, TensorRT provides users with advantages such as lower latency, cost savings by eliminating the need for cloud services, and enhanced data privacy by keeping proprietary data on the user's device.
Overall, the combination of Tensor Cores with TensorRT software brings unmatched generative AI performance to local PCs and workstations, unlocking new possibilities for developers and users alike.
