The eIQ Auto toolkit allows customers to develop for automotive production on desktop/cloud/GPU environments and to deploy their neural network onto a supported S32 processor. NXP’s toolkit and automotive grade inference engine enable easier deployment of neural networks in applications with intensive safety requirements. A good example is speeding up the transition from traditional computer vision algorithms to deep learning-based algorithms in vision-based systems.
Deep Learning holds the promise of delivering better accuracy and better maintainability in object detection and classification over “traditional” computer vision algorithms, but the barriers to full automotive implementation bring complexity and steep costs.
The eIQ Auto toolkit aims to help customers reduce time to market by lowering the investment costs required to select and program embedded compute engines for each layer of a deep learning algorithm. The automated selection process leads to 30 times higher performance for given models compared to other embedded deep learning frameworks. This performance is achieved by optimizing the use of available resources and reducing time and development effort1. These dividends allow developers to evaluate, fine tune and deploy their applications for maximized overall performance.
Compliance with automotive-grade development standards and Functional Safety requirements are key benefits of eIQ Auto and S32V integration. eIQ Auto’s inference engine was developed in accordance with stringent requirements and is Automotive SPICE® compliant. The S32V processors offer the highest levels of functional safety supporting ISO 26262 up to ASIL-C, IEC 61508, and DO 178.
“Next generation automotive applications, like those found in current Autonomous test vehicle implementations, are bulky, power hungry and impractical for volume automotive production,” said
Together, NXP’s eIQ Auto Deep Learning toolkit and automotive qualified S32V provide a strong foundation of performance, safety and quality for next generation automotive applications.
NXP eIQ Auto Toolkit Includes:
About eIQ Machine Learning Software
The NXP® eIQ™ machine learning software development environment enables the use of ML algorithms on NXP MCUs, i.MX RT crossover MCUs, and i.MX family SoCs. eIQ software and eIQ Auto toolkit include inference engines, neural network compilers, and optimized libraries. Learn more at www.nxp.com/eiq and www.nxp.com/eiqauto.
1 Based on Internal NXP benchmarks. Comparisons using single thread tensor flow tf lite model with floating point versus eIQ quantized version, running on dual apex 2 on S32V234.
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Source: NXP USA, Inc.