Synopsys (SNPS.US) expands chip IP business; Amazon (AMZN.US) becomes the first major customer for application-optimized design

According to Zhitong Finance App, Synopsys (SNPS.US) is expanding its chip intellectual property (IP) business into the field of application-optimized design and has signed a new multi-year agreement with Amazon (AMZN.US). As the business’s first major customer, Amazon will further increase its use of Synopsys chip IP and electronic design automation (EDA) technology to support the development of its own general-purpose computing and artificial intelligence chips.

This agreement further deepens the 15-year cooperation between the two parties. With Amazon Web Services (AWS) continuously expanding its self-developed chip portfolio, Synopsys will provide technical support in multiple areas including chip IP, design tools, simulation and analysis, as well as AI-assisted engineering.

Amazon Expands Its Proprietary Chip Portfolio

Chip IP refers to functional modules that can be reused across different chip designs. According to the new agreement, Amazon will expand its usage of Synopsys IP beyond traditional general-purpose modules to chip designs optimized for specific application scenarios.

In recent years, Amazon has been increasing its investment in custom chips. The Graviton series of processors under AWS are mainly aimed at general computing, while Trainium is designed for AI model training and inference tasks. In addition, Amazon utilizes the Nitro system, moving networking, storage, and security functionality from the main processor to dedicated hardware to enhance the operating efficiency of its cloud computing infrastructure. This year, AWS launched cloud computing instances based on its fifth-generation Graviton5 processor, further advancing its proprietary chip strategy that began in 2018 with the first-generation Graviton chip.

This expanded cooperation with Synopsys means Amazon’s chip development will receive additional external design technology support. In addition to chip IP, Amazon will also increase its use of Synopsys EDA tools as well as simulation and analysis technologies.

EDA tools are among the core software in modern chip design, assisting engineers with completing chip designs and simulating and testing expected chip performance before actual manufacturing, thus identifying potential design issues.

AI Further Enters the Chip Engineering Workflow

This cooperation will also extend to multiphysics analysis for Trainium and Graviton chips. As advanced chips and computing systems become increasingly complex, engineers need to consider the interactions between multiple factors such as temperature, power consumption, and mechanical effects. Synopsys and Amazon plan to use related technologies to conduct comprehensive simulation and analysis of these factors to improve chip and system design.

At the same time, the two companies also plan to further implement AI in Synopsys’s “chip-to-system” engineering workflow and develop customized agent-based AI capabilities for Amazon engineers.

These AI tools will assist engineers with chip and system design, analysis, optimization, and verification. As demand for AI chips continues to grow rapidly, this will further introduce AI technology into the chip R&D process.

Synopsys Shares Still Down Over 11% This Year

Although the new collaboration has driven Synopsys’s share price higher, its overall performance so far this year has remained relatively weak. To date, Synopsys shares are down more than 11% for the year, while Amazon has risen more than 9%. In comparison, the Nasdaq 100 ETF (QQQ.US), which holds both Synopsys and Amazon shares, is up more than 21% year-to-date.

Data from Stocktwits shows that retail investor sentiment toward both Synopsys and Amazon stocks remains "bearish." This cooperation shows that as cloud computing and generative AI drive rapid growth in demand for custom chips, Amazon is further strengthening its in-house capabilities from chip design to system optimization, while Synopsys is seeking to extend its business beyond traditional chip design IP and EDA software toward application-optimized design and AI-driven engineering workflows.