ADAS Heterogeneous Compute Parallel Processing Works

A revolution is being driven by an optimised automatic driving system that leverages heterogeneous compute

The growing reliance of the automotive industry on autonomous driving has resulted in a notable need for advanced driver assistance systems

The level of productivity and effectiveness has been enhanced. ADAS systems necessitate a substantial amount of computational capacity to handle data processing from several sensors

These novel architectures can vary from simple sensor-to-trajectory models to complex artificial intelligence models

Qualcomm’s System-on-Chips (SoCs) are specifically engineered to handle diverse types of computation, including heterogeneous tasks

The ability to respond immediately is extremely important in the fast-paced field of Advanced Driver Assistance Systems (ADAS)

This DSP has been specially tuned to deliver optimal performance in speech, visual, and audio processing applications