Purpose built for Automotive Intelligence Applications


(*) Tensor unit: Conv operations
Data reshape unit: Padding, reorder, Concat …
Domain specific unit: Pool, resize, warp …
Vector unit: Elem wise calc. on vector and matrices (row-by-row, column-column or tile-by-tile)
Highly parallel AI processing with multiple concurrent compute units
Powerful systolic array of tensor core for efficient CNN operations
Flexible, large scale near-compute-memory for local execution
High-flexibility high-bandwidth custom concurrent data bridge
Data parallelism. Kernel parallelism. Computation unit parallelism
Instruction parallelism. Layer parallelism. Model parallelism
Solutions Served
Journey AI processors are scalable from ADAS to Robotaxi applications as well as in-cabin AI systems. Journey 2 has won the coveted Product-of-the-Year award in the category of Automotive Solutions in June 2020