Cloud Electronic Design Automation Market By Deployment Mode (Public Cloud, Private Cloud, Hybrid Cloud); By EDA Tool Type (Simulation and Verification, Synthesis, Layout, Physical Verification, Timing Analysis); By Application (SoC Design, Analog & Mixed-Signal, MEMS, Automotive Electronics); By End User (Fabless Companies, Foundries & IDMs, OEMs, Academia); By Region, Segment Revenue Estimation, Forecast, 2024–2030.

1. Introduction and Strategic Context

The Global Cloud Electronic Design Automation (EDA) Market will witness a robust CAGR of 12.8% , valued at $6.2 billion in 2024 , and is expected to appreciate and reach $14.4 billion by 2030 , confirms Strategic Market Research.

 

Cloud EDA is a transformative software delivery paradigm that shifts traditional on-premises electronic design tools to scalable, elastic, and collaborative cloud environments. It enables semiconductor designers, electronic engineers, and embedded system developers to execute simulation, layout, synthesis, and verification processes on virtualized infrastructure. In 2024, this transition is becoming critical, driven by intensifying demands for chip complexity, shrinking time-to-market, and global design collaboration across regions.

 

At a strategic level, the shift to cloud-native EDA solutions is intertwined with major industry themes:

• Moore’s Law pressure on chipmakers to innovate faster while managing cost

• Rising complexity in SoC (System on Chip) and 3D IC (Integrated Circuit) design

• Need for real-time global collaboration across distributed teams

• Integration of AI/ML into design workflows, which requires scalable cloud GPU compute

• Rapid growth of edge devices, EVs, and 5G pushing up design cycles and verification requirements

The adoption of cloud-based EDA is also being fueled by regulatory clarity around IP protection in virtual environments, along with OEM-level mandates for secure, flexible design tools.

 

Key stakeholders driving this market include:

• EDA Software Vendors (e.g., traditional and emerging cloud-native tool developers)

• Semiconductor Foundries and OEMs (demanding advanced design capabilities)

• Cloud Infrastructure Providers (e.g., AWS, Azure, GCP)

• Venture Capital Firms backing EDA startups

• Electronics Design Houses and Fabless Companies

• Government Agencies funding next-gen chip design initiatives

According to industry experts, “the cloud EDA ecosystem is no longer a question of if, but when — and the tipping point will likely occur by 2026, with over 40% of design workloads shifting to the cloud.”

As we enter the 2024–2030 horizon, cloud EDA is no longer a niche—it is rapidly becoming the default for collaborative, high-velocity chip innovation.

 

2. Market Segmentation and Forecast Scope

The cloud electronic design automation (EDA) market can be comprehensively segmented based on Deployment Mode , EDA Tool Type , Application , End User , and Region . These segmentation dimensions capture the breadth of adoption, use cases, and technological variation across global markets.

By Deployment Mode

• Public Cloud

• Private Cloud

• Hybrid Cloud

Public cloud environments dominate adoption as of 2024, accounting for approximately 61% of global revenue, owing to their cost-efficiency and scalability. However, hybrid cloud is emerging as the fastest-growing segment due to rising concerns over IP security and data localization regulations.

By EDA Tool Type

• Simulation and Verification Tools

• Synthesis Tools

• Layout and Physical Design Tools

• IC Physical Verification Tools

• Timing Analysis Tools

• Others (e.g., PCB Design Tools)

Simulation and verification tools hold strategic importance as they are resource-intensive and benefit significantly from elastic compute in cloud environments. This segment is projected to see accelerated growth due to increased tape-out complexities and functional verification needs.

By Application

• Semiconductor IP Design

• System-on-Chip ( SoC ) Design

• Analog and Mixed-Signal Design

• MEMS and Sensor Design

• Automotive Electronics Design

SoC design remains the leading application area, driven by demand for multi-functional chips in 5G, AI, and automotive platforms.

By End User

• Fabless Semiconductor Companies

• Foundries and Integrated Device Manufacturers (IDMs)

• Original Equipment Manufacturers (OEMs)

• Research & Academia

• EDA Service Providers and Consultants

Fabless semiconductor firms are currently the largest contributors to cloud EDA adoption, given their asset-light nature and higher design outsourcing tendencies.

By Region

• North America

• Europe

• Asia Pacific

• Latin America

• Middle East & Africa (MEA)

North America led the global market in 2024, owing to early cloud adoption, proximity to hyperscalers , and leadership in semiconductor innovation. Asia Pacific, however, is set to register the highest CAGR through 2030, driven by China, Taiwan, and South Korea’s push for chip sovereignty.

This segmentation framework ensures accurate market forecasting, investment prioritization, and go-to-market alignment for stakeholders. Each segment reflects distinctive user behavior, compute requirements, and cloud maturity levels.

 

3. Market Trends and Innovation Landscape

The cloud electronic design automation (EDA) market is experiencing rapid transformation, driven by a convergence of advanced compute capabilities, intelligent software integration, and new design paradigms. As the semiconductor landscape becomes increasingly complex and fast-paced, EDA tools are being reimagined for the cloud—introducing new models for collaboration, acceleration, and cost optimization.

Key Innovation Trends Reshaping the Cloud EDA Landscape

1. AI and Machine Learning in Design Workflows Artificial intelligence is being embedded directly into EDA tools to enhance functions like layout generation, simulation prediction, anomaly detection, and test coverage optimization. When deployed in cloud environments, AI models can be trained across vast datasets with parallel compute, enabling smarter and faster design iterations . Companies are also exploring reinforcement learning for architecture optimization and IP reuse modeling.

2. Cloud-Native Architectures and Microservices Modern EDA platforms are being refactored into microservices and containerized modules, making them highly scalable and interoperable. This modularization allows users to execute specific design tasks (e.g., RTL synthesis or floorplanning ) independently while benefiting from granular billing and elastic resource allocation .

3. High-Performance Computing (HPC) and GPU Acceleration The integration of GPU-optimized workloads and FPGA-as-a-Service ( FaaS ) is reshaping simulation and verification processes. By leveraging cloud-based HPC , engineers can run multiple regression tests simultaneously, significantly reducing tape-out time and accelerating time-to-market.

4. IP Protection and Zero Trust Security Models With increased IP movement over public cloud networks, security has become paramount. Industry leaders are implementing zero trust architecture , end-to-end encryption, and role-based access to protect sensitive design data. Additionally, confidential computing and hardware-backed enclaves are gaining ground for secure multi-party collaboration.

5. Real-Time Collaboration and Global Access Cloud EDA enables teams across time zones to work on the same chip design project in real-time. Integrated development environments (IDEs) are becoming web-based, with built-in support for version control, live simulation previews, and design annotation tools— greatly enhancing productivity and reducing silos .

Innovation-Led Collaborations and Ecosystem Dynamics

• EDA leaders are forming partnerships with hyperscalers (e.g., AWS, Azure, and Google Cloud) to optimize their toolchains for cloud execution and offer usage-based pricing models.

• Startups are challenging legacy vendors with browser-first, collaborative-first platforms aimed at startups and academic institutions.

• Cloud-first verification farms , where companies can “rent” thousands of compute cores for intensive testing, are rapidly gaining traction in functional verification.

Expert Insight

“The future of EDA will be measured in petaflops per design—only the cloud can offer that kind of power flexibly. From RTL to GDSII, the entire design cycle is being optimized for parallelism and AI acceleration,” notes a senior engineering director at a leading chip design firm.

As we approach the end of the decade, the innovation landscape in cloud EDA will not only redefine tool performance but also disrupt pricing models, team structures, and competitive advantages in the semiconductor sector.

 

4. Competitive Intelligence and Benchmarking

The cloud electronic design automation market is led by a mix of established EDA giants and emerging cloud-native innovators. Each player is adopting distinct go-to-market strategies to navigate the shift from traditional license-based software to consumption-based cloud platforms.

Below are 7 key companies shaping this competitive landscape:

1. Synopsys

As a legacy leader in EDA, Synopsys has made a strong pivot to the cloud with its Fusion Design Platform and strategic partnerships with AWS and Microsoft Azure . It offers full-stack cloud EDA support for digital and analog design flows. Its pricing flexibility, robust IP portfolio, and end-to-end integration make it a preferred vendor for enterprise semiconductor clients.

Synopsys is investing in cloud-optimized verification and ML-powered design assistants, aiming to reduce tape-out cycles by up to 30%.

2. Cadence Design Systems

Cadence is a dominant player focusing on hybrid cloud delivery for its Allegro and Virtuoso suites. It has introduced CloudBurst Platform , allowing clients to scale compute resources during peak demand periods. Cadence also emphasizes multi-cloud compatibility , giving clients flexibility across different infrastructures.

Cadence’s strategic focus lies in high-value AI-driven automation for analog and RF designs, particularly in 5G and automotive applications.

3. Siemens EDA (formerly Mentor Graphics)

Backed by Siemens' broader industrial portfolio, Siemens EDA offers a cloud-optimized toolchain anchored by its Calibre verification suite and PAVE360 platform for automotive SoC design. The company positions itself strongly in the digital twin and digital thread ecosystem, which appeals to OEMs in transportation and industrial verticals.

Siemens is leveraging its edge in industrial digitalization to offer cloud-integrated design and test environments that simulate full lifecycle performance.

4. Ansys

Ansys focuses on simulation-centric EDA tools and cloud-based multi-physics solutions. Its RedHawk suite for power and thermal analysis is now available as a cloud-native module, attracting customers in data center chip design. The company collaborates with AWS and Google Cloud for HPC-accelerated workloads.

With semiconductor reliability becoming mission-critical, Ansys is betting on cloud-powered physical modeling as a growth engine.

5. Keysight Technologies

A newer entrant in cloud EDA, Keysight brings strength from its test and measurement legacy. It offers PathWave Design Cloud , which integrates RF and high-speed digital design tools with AI-enhanced optimization.

Keysight is carving a niche in wireless system design and verification for 6G, where cloud-based multi-domain modeling is essential.

6. Empyrean Technology

This China-based EDA firm is gaining momentum with its cloud-enabled analog design platform , offering localized services and compliance with regional IP laws. Empyrean is expanding rapidly across Asia, offering cost-competitive solutions to local design houses and fabs .

Its domestic-first strategy aligns with China’s semiconductor independence goals, making it a favored partner in national R&D projects.

7. Agile Analog

A cloud-native startup , Agile Analog delivers analog IP blocks through a virtual design-as-a-service model. It leverages cloud infrastructure to rapidly customize IP for clients, reducing the analog design cycle by up to 50%.

Agile Analog’s disruptive model could reshape how analog design is approached—via online configuration and API-driven deployment.

Together, these companies represent a competitive spectrum from cloud-enabling incumbents to born -in-the-cloud challengers . The battle now hinges on platform extensibility, ecosystem integration, and the ability to deliver design acceleration through intelligent, scalable, and secure cloud workflows.

 

5. Regional Landscape and Adoption Outlook

The cloud electronic design automation (EDA) market demonstrates highly asymmetrical growth patterns across geographies, influenced by factors such as semiconductor R&D intensity, cloud infrastructure maturity, and national chip strategies. While North America currently leads in terms of adoption and revenue, Asia Pacific is emerging as the fastest-growing region, catalyzed by sovereign chip initiatives and hyperscaler expansion.

North America

North America is the largest and most mature market , accounting for over 38% of global revenue in 2024 . The region benefits from:

• The presence of major EDA vendors ( Synopsys , Cadence , Ansys )

• Advanced semiconductor fabs and fabless firms

• Strong collaboration with hyperscalers ( AWS , Google Cloud , Microsoft Azure )

The U.S. CHIPS Act has further accelerated R&D investment, particularly in universities and startups that prefer cloud-first design tools due to affordability and remote access.

“We’ve seen a 2x increase in cloud EDA demand from North American fabless startups post-CHIPS funding approvals,” notes an AWS executive.

Europe

Europe’s cloud EDA market is characterized by cautious but steady adoption, driven by:

• Automotive chip design dominance in Germany , France , and Italy

• Emphasis on security and compliance (GDPR-aligned cloud strategies)

• The rise of RISC-V and open hardware consortia in The Netherlands and Switzerland

Despite modest growth, European OEMs are increasingly using hybrid cloud tools for in-vehicle systems , ADAS , and EV powertrain designs .

Regional security laws and IP sensitivity are nudging vendors toward private and sovereign cloud deployments.

Asia Pacific

Asia Pacific is the fastest-growing regional market , expected to expand at a CAGR of 15.3% through 2030 . Key growth drivers include:

• National chip independence missions in China , India , South Korea , and Japan

• Cloud-native design adoption among fabless startups in Taiwan and Vietnam

• Government investment in HPC and AI-based chip design infrastructure

China is a strategic hotspot, where domestic players like Empyrean Technology are building localized EDA clouds to bypass Western IP restrictions. South Korea is also scaling cloud-based verification for 3D memory and AI chips.

Latin America

Adoption in Latin America is nascent, with pockets of demand in Brazil and Mexico . Cloud EDA usage is largely limited to academic institutions , contract engineering firms , and a few electronics manufacturers. Limited local chip production and cloud bandwidth constraints remain barriers.

Middle East & Africa (MEA)

In MEA, the market is embryonic. However, innovation hubs in Israel and the UAE are making strides in advanced design tools, particularly for aerospace , cybersecurity chips , and cryptographic hardware . Adoption is mostly facilitated through partnerships with U.S.-based cloud EDA vendors.

White Space and Underserved Regions

• Africa and Central Asia remain underpenetrated

• Lack of trained IC designers and high compute costs are primary inhibitors

• Opportunity exists for open-source cloud EDA tools or government-subsidized platforms

Regional outlook over the forecast period points to Asia Pacific surpassing Europe by 2027 , and North America maintaining its lead due to its vendor ecosystem and infrastructure dominance.

 

6. End-User Dynamics and Use Case

The cloud electronic design automation (EDA) market serves a diverse set of end users, each with distinct operational needs, resource constraints, and adoption triggers. Whether accelerating chip development or facilitating collaborative prototyping, cloud EDA is reshaping workflows for both commercial and academic entities.

Key End-User Groups

1. Fabless Semiconductor Companies These asset-light companies are the earliest adopters of cloud EDA. Without owning fabrication facilities, they rely heavily on advanced, agile design environments. Cloud platforms allow them to:

• Access cutting-edge simulation tools without capex

• Scale verification tasks during peak development

• Collaborate in real time across globally distributed teams

For startups, cloud EDA transforms fixed design costs into scalable operational expenses—critical for budget flexibility.

2. Integrated Device Manufacturers (IDMs) and Foundries IDMs are cautiously integrating cloud EDA into specific stages like functional verification or thermal analysis. While large foundries maintain secure on-premise clusters, they are increasingly evaluating hybrid models to:

• Offload peak compute tasks

• Shorten product tape-out cycles

• Support ecosystem partners and IP vendors

Cloud is used surgically where it offers demonstrable speed and efficiency gains.

3. OEMs and Consumer Electronics Giants Electronics OEMs are using cloud EDA to co-design chips with suppliers, especially in automotive , IoT , and wearables . These companies benefit from:

• Cloud-based design reviews and version tracking

• Better integration of hardware and software teams

• Accelerated design-to-validation timelines

Cloud tools are often embedded into digital twin workflows, especially for EVs and smart devices.

4. Research Institutions and Academia Universities and chip research labs have embraced cloud EDA due to affordability and flexibility. Public cloud platforms provide:

• Instant lab environments for VLSI courses

• Shared access for student teams

• Cross-institution collaboration

This democratizes access to industry-grade tools, preparing students for real-world design challenges.

5. EDA-as-a-Service Providers A growing cohort of consulting firms and IP design houses now offers "EDA-as-a-Service" using cloud platforms. These third-party vendors manage toolchains, versioning, and compute provisioning for clients, adding value in:

• Quick prototyping for fabless clients

• IP block customization for SoCs

• Workflow automation across cloud environments

Use Case: Automotive Chip Development in South Korea

A leading automotive electronics firm in South Korea adopted a hybrid cloud EDA platform for the design of a next-gen ADAS (Advanced Driver Assistance System) chip. Previously dependent on local servers, the company migrated its simulation and verification tasks to a cloud platform co-hosted on AWS Seoul Region.

• Design teams in Seoul and Detroit collaborated via shared cloud environments

• Parallel regression tests reduced verification time by 40%

• Cost savings were achieved by only scaling resources during nighttime batch runs

The project went from prototype to tape-out in six months—a 20% acceleration compared to previous cycles.

Cloud EDA is no longer a cost-saving alternative—it is becoming a strategic enabler across industries where time, security, and innovation are critical to chip success.

 

7. Recent Developments + Opportunities & Restraints

Recent Developments (2023–2025)

• Synopsys and AWS Partnership Expansion (2024): Synopsys extended its collaboration with AWS to enhance cloud-native deployment of its flagship EDA suite, enabling subscription-based pricing models for fabless clients.

• Cadence Launches CloudBurst Platform Enhancements (2024): Cadence introduced AI-powered job scheduling and multi-cloud workload balancing in its CloudBurst platform, improving resource utilization and reducing simulation bottlenecks.

• Siemens EDA Acquires Analog Cloud Start-up (2023): Siemens acquired a boutique cloud analog design platform to strengthen its mixed-signal and automotive EDA offerings, accelerating hybrid cloud adoption in the automotive vertical.

• Empyrean Technology Expands Cloud Data Centers in China (2023): Empyrean opened new cloud data centers compliant with China’s cybersecurity laws to support domestic semiconductor design firms with low latency and enhanced data security.

• Keysight Integrates AI Modules into PathWave Cloud Suite (2025): Keysight introduced AI-driven optimization tools for RF and high-speed digital chip design in its PathWave cloud platform, targeting 6G and aerospace chip developers.

 

Opportunities

• Emerging Markets Penetration: Rising semiconductor design activity in India, Vietnam, and Eastern Europe presents significant untapped demand for cloud EDA services.

• AI and Automation Integration: Expanding AI-augmented design workflows and cloud-based automated verification offer compelling efficiency and cost-saving gains.

• Remote Work and Collaboration: Increasing acceptance of distributed teams post-pandemic is accelerating adoption of cloud tools that enable real-time collaboration.

 

Restraints

• Data Security and IP Concerns: Despite advances, reluctance around IP theft, regulatory compliance, and data sovereignty remains a barrier for fully public cloud deployments.

• High Initial Integration Costs: Transitioning from legacy on-premise EDA to cloud-based workflows involves significant upfront investment in training, migration, and workflow redesign.

 

Report Coverage Table

Report Attribute	Details
Forecast Period	2024 – 2030
Market Size Value in 2024 USD	$6.2 Billion
Revenue Forecast in 2030 USD	$14.4 Billion
Overall Growth Rate	CAGR of 12.8% (2024 – 2030)
Base Year for Estimation	2023
Historical Data	2017 – 2023
Unit	USD Million, CAGR (2024 – 2030)
Segmentation	By Deployment Mode, By EDA Tool Type, By Application, By End User, By Region
By Deployment Mode	Public Cloud, Private Cloud, Hybrid Cloud
By EDA Tool Type	Simulation and Verification, Synthesis, Layout, Physical Verification, Timing Analysis
By Application	SoC Design, Analog & Mixed-Signal, MEMS, Automotive Electronics
By End User	Fabless Companies, Foundries & IDMs, OEMs, Academia
By Region	North America, Europe, Asia Pacific, Latin America, Middle East & Africa
Market Drivers	- Rapid adoption of cloud infrastructure in semiconductor design - Growing chip complexity demands - Rising remote collaboration trends
Customization Option	Available upon request