Increasing investment in computing technologies and the advancements in silicon technology has fueled rapid growth in advanced driver assistance systems (ADAS) and corresponding SoC developments. An ADAS SoC represents a heterogeneous architecture that consists of CPUs, GPUs and artificial intelligence (AI) accelerators. In order to guarantee its safety and reliability, it must process massive amount of raw data collected from multiple redundant sources such as high-definition video cameras, Radars, and Lidars to recognize objects correctly and to make the right decisions promptly. A domain specific memory architecture is essential to achieve the above goals. We present a shared memory architecture that enables high data throughput among multiple parallel accesses native to the ADAS applications. It also provides deterministic access latency with proper isolation under the stringent real-time QoS constraints. A prototype is built and analyzed. The results validate that the proposed architecture provides close to 100\% throughput for both read and write accesses generated simultaneously by many accessing masters with full injection rate. It can also provide consistent QoS to the domain specific payloads while enabling the scalability and modularity of the design.

介绍一种共享内存架构，以实现高吞吐量的数据流入，并具备适当隔离措施，能满足实时的质量要求；在多个访问主机同时读写的情况下，能够提供高达近100%的吞吐量；同时，使该架构具有可扩展性和模块化的设计。

用于高性能ADAS SoC的多端口和共享存储器架构