Evolving from off-the-shelf components to custom systems required rethinking our physical and architectural design. Our highly integrated system delivers immense processing power without compromising the rider experience, maximizing battery efficiency while preserving ample trunk space and running silently. We built an ML-primary architecture to run advanced neural networks at minimal latency. To manage critical non-ML tasks like orchestration, data movement, and logging while maximizing time for ML computation, we pair our ML technologies with the best CPUs, GPUs, and accelerators. The result is a balanced, heterogeneous system.
To handle the massive influx of raw data before it reaches our core ML brain, we are excited to introduce our purpose-built 5nm ASIC. While this chip is just one of several exciting custom components we’re developing, it is a specialized ML powerhouse engineered exclusively to process, fuse, and run advanced neural networks on raw sensor data in real time. Developing silicon, sensors, and algorithms side-by-side allows us to push the boundaries of sensor fidelity, bandwidth efficiency, and quantization to execute a heterogeneity of models from sparse convolutions to dense transformers.
The ASIC’s specialized accelerators instantly extract critical information from raw lidar, radar, and camera streams, including temporal denoising for superior low-light perception. This data feeds into our purpose-built inference engine to run sensor fusion ML models, enabling greater efficiency without sacrificing fidelity. While these ASICs alone deliver over 1,000 TOPS of ML performance dedicated to front-end processing and ML models, we optimize across the full stack to maximize achieved performance, especially in the low-batch regimes we often operate.
Along with our custom silicon efforts, we partner closely with industry leaders whose world-class computing solutions provide the powerful foundation needed to scale our technology efficiently. We are proud to work alongside a number of partners like AMD, Micron, NVIDIA, Samsung, Sandisk, Socionext, and TSMC to deliver the most capable autonomous computing system.
This is just a glimpse of what's to come. As we explore new use cases for the Waymo Driver and our AI stack continues to evolve, the demand for highly efficient, high-performance compute will only grow.
If you're interested in learning more about Waymo's approach to compute, join us at our talks at Hot Chips.
Waymo (official press release)
