Best IC Design Software for Docker
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Compare the Top IC Design Software that integrates with Docker as of June 2025
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This a list of IC Design software that integrates with Docker. Use the filters on the left to add additional filters for products that have integrations with Docker. View the products that work with Docker in the table below.
What is IC Design Software for Docker?
IC design software is software used to create and simulate integrated circuits (ICs), essential for developing semiconductor chips in electronics. It provides a platform for designing complex circuits, from schematic capture to layout and verification, ensuring that the IC functions as intended. The software incorporates features like circuit simulation, timing analysis, and power optimization to help engineers design efficient and high-performance chips. It is widely used in industries like consumer electronics, telecommunications, and automotive, where precision and innovation in chip design are critical. By streamlining the IC design process, this software reduces development time and cost, while ensuring reliable and scalable semiconductor solutions. Compare and read user reviews of the best IC Design software for Docker currently available using the table below. This list is updated regularly.
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SiLogy
SiLogy
Our next-generation web platform empowers chip developers and verification engineers to design and debug 10x faster. Build and run thousands of tests in parallel at the push of a button with Verilator. Seamlessly share test results and waveforms with anyone in your organization, tag coworkers directly on signals, track test and regression failures. We use Verilator to compile Dockerized simulation binaries and distribute test runs across our compute cluster. Then we collect the results and log files and optionally rerun failing tests to generate waveforms. With Docker, we can ensure that test runs are consistent and reproducible. SiLogy makes chip developers more productive by enabling faster design and debug times. Before SiLogy, the state-of-the-art for debugging a failing test involved copying lines from log files, debugging from waveforms on a local machine, or rerunning a simulation that might have taken days to run.
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