Aeva Leverages Cadence Tensilica Vision DSP to Boost 4D LiDAR Performance and Efficiency

Cadence (Cadence Design Systems) has announced that Aeva (Aeva Technologies), a developer of next-generation sensing and perception systems, has licensed its Tensilica Vision DSP IP to enhance signal processing capabilities in its 4D LiDAR platforms. The move is aimed at improving performance, scalability, and power efficiency for applications in automotive systems, industrial robotics, and other autonomous technologies.

LiDAR technology plays a critical role in enabling real-time 3D mapping and object detection across robotics, autonomous vehicles, and industrial automation. Aeva’s 4D LiDAR expands on traditional systems by simultaneously capturing both position and velocity data, allowing machines to make faster and more accurate decisions in dynamic environments.

By integrating Cadence’s Tensilica Vision DSP, Aeva gains a highly programmable and efficient processing architecture designed for low-latency workloads. The DSP’s customizable design, enabled through the Tensilica Instruction Extension (TIE) language, allows tailored optimizations for complex LiDAR signal processing tasks while maintaining low power consumption.

According to Aeva chief engineer James Reuther, the integration of Tensilica technology provides the flexibility and performance needed to accelerate innovation and bring advanced sensing solutions to market more efficiently. He noted that the combination of Cadence’s hardware architecture and software ecosystem helps speed up development for next-generation autonomous systems.

Cadence’s Amol Borkar added that the company continues to focus on enabling high-performance, low-power solutions for edge and physical AI applications. He emphasized that Tensilica DSPs are well suited for real-time workloads such as LiDAR, computer vision, radar processing, and simultaneous localization and mapping (SLAM).

The Tensilica Vision DSP platform also includes optimized software libraries and the NeuroWeave SDK, supporting neural network acceleration and modern AI workloads used in perception systems. With established use across ADAS, radar, audio, and vision applications, the DSP family continues to be positioned as a key enabler for advanced, energy-efficient autonomous technologies.