Before programming
The machine is highly configurable before the workload is mapped, making it adaptable to the algorithm graph.
Solutions
A practical architecture for next-generation AI integration
Daidalos combines a direct mapping approach, hardware flexibility, and industrial compatibility to deliver AI accelerator IP that fits real product timelines.
Mapping flow
Flexible before programming Deterministic after deployment
Mapper and compiler
The neural network is translated into a precise hardware setting without relying on heavy runtime orchestration.
On-chip execution
Once programmed, the workload runs as deterministic dataflow with reduced control, fetch, and sync overhead.
Use cases
Built for companies that need integration speed and efficiency at the same time.
Application: machine vision
For edge computing deployments, discover how to run YOLO networks in real time on constrained systems, including battery-powered devices. Discover the IP for FPGA.
Application: autonomous systems
Bring agentic solutions based on small language models onto edge devices. Discover the use case: autonomous satellite management.
AI accelerator for SoC
Production-oriented accelerator IP designed for custom silicon integration across technology nodes from 22 nm down to 12 nm.
AI accelerator for FPGA
Xilinx-based acceleration solutions tailored for space applications and high-reliability programmable hardware environments.