As the automotive industry continues to progress toward automated driving, advanced driver assistance systems (ADAS) are in high demand. These systems rely on processing vast amounts of diverse sensor data in real time to make critical decisions. To meet these challenging requirements, Qualcomm Technologies, Inc. has developed Snapdragon Ride solutions based on heterogeneous compute systems on chips (SoCs), a transformative technology that seeks to revolutionize ADAS systems. 

The power of heterogeneous compute

Heterogeneous compute refers to the use of different processing units — such as Central Processing Units (CPU), Neural Processing Units (NPUs), Digital Signal Processors (DSPs), and Graphics Processing Units (GPU) and computer vision accelerators — in a system to perform specific tasks more efficiently. 

Our ADAS platform harnesses the power of heterogenous compute to unlock:

Enhanced performance and efficiency: ADAS systems require immense computational power to process data from multiple sensors and perform complex algorithms, and efficient handling of large data movement. By leveraging the strengths of different processing units, heterogeneous compute allows for workload distribution, optimizing power consumption and improving overall system performance in ADAS applications. Moreover, advanced data compression, AI compilers and optimized memory architecture enables highly optimized data handling while minimizing offloading to DDR.  

Efficient sensor fusion: Sensor fusion lies at the heart of ADAS systems, combining data from various sensors to create a comprehensive understanding of the environment. ADAS systems can include both early fusion using transformer based AI architectures, and late fusion depending on the safety concepts.