CV-CUDA Early Access

CV-CUDA is an open source project that enables developers to build highly efficient, graphics processing unit (GPU)-accelerated pre- and post-processing pipelines in cloud-scale Artificial Intelligence (AI) imaging and computer vision (CV) workloads. With a specialized set of CV and image processing kernels that are hand-optimized for performance on data center GPUs, CV-CUDA assures that your processing pipelines built with these kernels are being executed to deliver a much higher throughput across the entire complex workload. CV-CUDA can offer greater than 10x throughput improvement and lower cloud computing cost. CV-CUDA will offer easy integration into C/C++, Python, and interfaces to common Deep Learning (DL) frameworks like PyTorch.

Key Features:

  • A unified, specialized set of highly performant CV kernels
  • C, C++, and Python APIs
  • Kernel development framework
  • Batching support, with variable shape images
  • Zero-copy interfaces to PyTorch and TensorFlow
  • End-to-end reference samples
  • Use Cases:

    Early access is limited to select enterprises that build accelerated pre- and post-processing pipelines for common AI imaging and CV workloads deployed at scale in the cloud. Common use cases for such tasks include:

  • video content enhancement or analysis
  • three-dimensional (3D) worlds
  • image understanding
  • recommender systems
  • videoconferencing
  • How to Participate:

    To participate, please fill out the short application at the link below and provide details about your use case. You must be a member of the NVIDIA Developer Program and logged in with your organization's email address. We will not approve early access applications from personal email accounts.

    After approval, we will require a Non-Disclosure Agreement before granting access. Early access applications will be granted for Alpha release in December 2022 with the Beta version to follow in Spring 2023.

    CV-CUDA Early Access Developer Application: