Advanced Tools & Libraries


Speed development of high-performance, power-efficient designs for in-vehicle and cloud data center platforms.

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Intel® GO™ Automotive SDK Beta

Data scientists, system designers, and developers of applications and algorithms can use this SDK to:

  • Build high-performance, power-efficient designs for in-vehicle and cloud-based data center platforms
  • Accelerate performance from car to cloud
  • Advance perception sensor and deep learning algorithms
  • Boost programmer productivity and simplify development across multiple end-to-end workflows

The SDK is customizable depending on your workflows and development needs. It includes optimizing compilers, highly tuned libraries, analyzers, and debug tools to enable both in-vehicle and data center software development.

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Intel® Computer Vision SDK Beta

Cars need visual data to interpret their surroundings in real time. Use this SDK to integrate computer vision and visual understanding into your autonomous driving solutions.

  • Easily harness the performance of computer vision accelerators from Intel
  • Add custom kernels (using C, C++, or OpenCL™ code) into workload pipelines
  • Innovate solutions with computer vision and deep learning neural network inference

Intel® Media SDK

Complete the experience for the next generation of driving with this cross-platform API that provides access to fast video playback, encoding, and processing. Benefits include:

  • Outstanding encoding and decoding performance
  • Quick time-to-market with an easy-to-use API with embedded Linux*, Windows*, and open-source versions
  • Supports HEVC, AVC, MPEG-2, and more codec types
  • Hardware-accelerated video filters

Intel® SDK for OpenCL™ Applications

The SDK supports offloading compute-intensive parallel workloads to Intel® Graphics Technology using an advanced OpenCL™ kernel compiler, runtime debugger, and code performance analyzer.

  • Create richer and more immersive cockpit experience by increasing the graphics abilities of car interfaces
  • Use heterogeneous programming across CPUs, GPUs, and FPGAs
  • Dramatically increase graphics processing using processor resources