Preliminary Approach to Parallelizing Autonomous Driving Applications Using High-Performance Many-core Processor
Xuankeng He, Takuya Azumi · 2024
Advancements in autonomous driving technologies leverage real-time computing and embedded systems to enable vehicles to make quick decisions based on dynamic road conditions. These increasingly complex systems face rising computational demands. This study introduces a preliminary approach to parallelizing autonomous driving applications using a high-performance many-core processor. By distributing tasks across multiple cores, the approach enhances concurrent execution, reduces conflicts, and minimizes resource contention, improving the efficiency and performance of autonomous driving systems.