NVIDIA Programmable Vision Accelerator SDK
The NVIDIA Programmable Vision Accelerator (PVA) Software Development Kit (SDK) lets you write, debug, and optimize applications targeting PVA. PVA is a programmable VLIW SIMD DSP accelerator included on NVIDIA DRIVE AGX™, Jetson AGX™ and Jetson NX™ platforms that is optimized for low latency processing, determinism, and power efficiency. PVA programs can be executed concurrently with the CPU, GPU, and other accelerators as part of a heterogeneous compute pipeline, achieving high system performance and low power consumption for image processing, computer vision, and other sensor data processing tasks.
Apply for the PVA SDK for JetsonPVA SDK Documentation
Developer Forum
Key Features
Optimize Performance With PVA Offload
Leverage PVA to offload pre-processing tasks, freeing up the GPU to boost performance, meet latency budgets, and enhance power and thermal efficiency.
Develop Your Own Custom PVA Algorithms
The software development kit offers tools that let you build and deploy custom algorithms on PVA, accelerating AI applications with greater efficiency.
Accelerate Developing With Customizable PVA Solutions
Jumpstart development with PVA Solutions that provide source-code implementations of common algorithms—fully customizable for quick transition to production.
How the PVA SDK Works
PVA on NVIDIA Jetson and DRIVE AGX platforms offers a low-power solution to tackle compute and efficiency challenges in AI applications. It boosts system performance by offloading non-AI tasks—like feature extraction and object localization in multi-object tracking—to free up GPUs for AI-driven detection, tracking, and safety-critical functions.
The PVA SDK provides runtime APIs, tools, and tutorials for the development and deployment of CV and DL/ML algorithms. It gives you a seamless build-to-deploy framework that enables efficient PVA code development, verification using an x86 native emulator, validation through debuggers and profiling utilities, and cross-compilation of code into a binary executable. It also provides interoperability APIs to enable seamless integration with NVIDIA® CUDA® applications. With extensive documentation, beginner to expert-level tutorials, and PVA Solutions, you can easily get started developing your own production-ready algorithms using the PVA SDK.
PVA Solutions provide operators, primitives, and samples powered by the PVA SDK. Source-code availability lets you use them as-is or customize them as needed. PVA Solutions are designed to accelerate application development across a diverse range of domains that include vision, lidar, and radar. Learn more. (link to getting started in PVA Solutions doc)and openness in how we speak about our products.
Learn More About PVA Solutions
Quick-Start Guide
Access step-by-step guidance to develop, test, and deploy PVA algorithms—from foundational basics to expert-level implementations.
Real-World Applications
Learn how automotive manufacturers like NIO are optimizing their CV pipelines on the DRIVE AGX platform using PVA.
Boosting AI Performance on Jetson Orin
Learn how developers can use multiple compute engines like PVA, GPU, and DLA to boost system performance and efficiency on NVIDIA Jetson Orin™.
Jetson Partner Ecosystem for PVA
Access partners like RidgeRun to support your development effort on PVA.
Get Started With the PVA SDK
Use the right development and learning tools to start developing your algorithms on PVA.
Explore and Learn
Begin with exploring and learning the PVA hardware and SDK capabilities using the comprehensive documentation and step-by-step tutorials.
Develop Locally
Create PVA algorithms from scratch or start with source samples in PVA Solutions on your local machine using an x86 emulator, without requiring a Synopsys ASIP Programmer license.
Build and Deploy
Get a Synopsys ASIP Programmer evaluation license to build and deploy your application with PVA implementation.
Case Study: Real-Time Multi-Object Tracking on NVIDIA Jetson
Developers on Jetson implement state-of-the-art multi-object tracking pipelines containing processing algorithms with multiple streams using trackers like NvDCF in NVIDIA DeepStream. In these applications, it’s critical to achieve real-time performance without compromising accuracy within the energy and thermal constraints. These compute-demanding systems can use the PVA backend to free up the GPU for AI-specific and more critical tasks.
Multi-object tracking (using nvDCF) deployed on the Jetson platform.
.jpg)
Leveraging PVA to offload an object-tracking algorithm and free up the GPU.
