As we said at the top of this review, collaboration is becoming as important as technology itself. This year, our alliances ranged from becoming part of Intel’s foundry services ecosystem alliance to one with SiMa.ai, designed to ease the path for machine learning applications.
We joined the Intel Foundry Services Accelerator EDA and IP Alliance upon launch in February with a view to help chip designers meet what are often punishing product development goals. In the spirit of staying ahead of industry developments, the move has given us early access to Intel’s process roadmap and design kits among other assets, helping to ensure EDA and IP solutions are optimized accordingly, as well as reducing risk and raising productivity for our customers. Given our long history of working with the US government and the aerospace industry, we also joined the trusted Intel Foundry Services’ (IFS’) USMAG (United States Military, Aerospace and Government) Alliance in November.
On the topic of risk mitigation, in March, Samsung Foundry adopted our advanced voltage-timing signoff solution, one of the fruits of another longstanding partnership with Ansys. The technology guards against potentially costly timing failures to support energy efficient design. And speaking of Samsung, we announced multiple successful test chip tapeouts on digital and custom design tools and flows in October as a result of our collaboration with Samsung Foundry. The joint effort has enabled 3nm process technology for challenging mobile, HPC, and AI designs, offering a 50% reduction in power, 30% performance improvement, and 30% smaller area compared to the earlier Samsung SF5E process.
We also deepened our partnership with Arm to help customers develop next-generation mobile applications by optimizing our design, verification, and IP solutions to deliver maximum performance for the latest Arm Total Compute SoCs. This move, built on more than three decades of already close collaboration, addressed the need for secure and specialized processing for next-generation devices, as well as gaming and VR applications.
Considering the role of machine learning and AI in edge computing, we supported SiMa.ai in developing a machine learning system-on-chip (MLSoC) platform. The innovation uses Synopsys design, verification, IP, and design services solutions, and exemplifies the progress that is achievable when hardware and software pioneers come together.
Recognizing the trend towards application-specific silicon to help address the intensive compute demands of advanced high-performance systems, we collaborated with the pioneers who brought RISC-V to the mainstream, SiFive, to accelerate the design and verification of their custom RISC-V-based SoCs.