Design Automation


Xilinx design tool with machine-learning optimisation

25 August 2021 Design Automation

Xilinx recently introduced Vivado ML Editions, the industry’s first FPGA EDA tool suite based on machine learning (ML) optimisation algorithms, as well as advanced team-based design flows for design time and cost savings. Vivado ML Editions delivers 5x faster compile time and quality of results (QoR) improvements on average 10% for complex designs, compared to the current Vivado HLx Editions.

Vivado ML Editions enables ML-based algorithms that accelerate design closure. The technology features ML-based logic optimisation, delay estimation and intelligent design runs, which automates strategies to reduce timing closure iterations.

Xilinx is also introducing the concept of an Abstract Shell, which allows users to define multiple modules within the system to be compiled incrementally and in parallel. This enables an average compile time reduction of 5x, and up to 17x, compared to traditional full system compilation. Abstract Shell also helps protect a customer’s IP by hiding the design details outside of the modules, critical for applications like FPGA-as-a-Service and value-added system integrators.

In addition, Vivado ML Editions improves collaborative design with Vivado IP Integrator, which enables modular design using the new ‘block design container’ feature. This capability promotes a team-based design methodology and allows for a divide-and-conquer strategy to handle large designs with multisite cooperation.

Unique adaptability features like Dynamic Function eXchange (DFX) enable more efficient use of silicon resources by loading custom hardware accelerators, dynamically at runtime over-the-air. With the ability of DFX to load design modules in a few milliseconds, it opens up new use cases such as a car swapping different vision algorithms during processing of a frame, or a genomic analysis swapping different algorithms in real-time as it sequences DNA.


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