RightNow AI Integrations

CUDA® is a parallel computing platform and programming model developed by NVIDIA for general computing on graphical processing units (GPUs). With CUDA, developers are able to dramatically speed up computing applications by harnessing the power of GPUs. In GPU-accelerated applications, the sequential part of the workload runs on the CPU – which is optimized for single-threaded performance – while the compute intensive portion of the application runs on thousands of GPU cores in parallel. When using CUDA, developers program in popular languages such as C, C++, Fortran, Python and MATLAB and express parallelism through extensions in the form of a few basic keywords. The CUDA Toolkit from NVIDIA provides everything you need to develop GPU-accelerated applications. The CUDA Toolkit includes GPU-accelerated libraries, a compiler, development tools and the CUDA runtime.

Software is what turns a vehicle into an intelligent machine. The NVIDIA DRIVE™ Software stack is open, empowering developers to efficiently build and deploy a variety of state-of-the-art AV applications, including perception, localization and mapping, planning and control, driver monitoring, and natural language processing. The foundation of the DRIVE Software stack, DRIVE OS is the first safe operating system for accelerated computing. It includes NvMedia for sensor input processing, NVIDIA CUDA® libraries for efficient parallel computing implementations, NVIDIA TensorRT™ for real-time AI inference, and other developer tools and modules to access hardware engines. The NVIDIA DriveWorks® SDK provides middleware functions on top of DRIVE OS that are fundamental to autonomous vehicle development. These consist of the sensor abstraction layer (SAL) and sensor plugins, data recorder, vehicle I/O support, and a deep neural network (DNN) framework.