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    AWS Semiconductor EDA & Integrated SoC Strategy Advisory

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    Expert-led strategic advisory on the Integrated SoC landscape. Align your "in-house" silicon R&D, on-device AI accelerators, and Electronic Design Automation (EDA) securely on Amazon Web Services (AWS).

    Overview

    Overview

    This Professional Service engagement helps semiconductor manufacturers, fabless designers, and hardware OEMs design their digital and R&D strategies for the Global Integrated System-on-Chip (SoC) market. As the industry moves toward 2nm nodes and on-device Generative AI, raw data is insufficient for making multi-billion dollar IT, R&D, and procurement decisions. Our industry experts guide your leadership team through the nuances of the market, helping you digitize your semiconductor pipelines and identify the PPA (Power-Performance-Area) gains required to justify bringing SoC design in-house.

    AWS Architecture & Semiconductor Strategy

    A critical component of bringing custom silicon design in-house is building highly scalable compute environments for Electronic Design Automation (EDA) and silicon simulation. We guide hardware leaders on how to operationalize chip design using Amazon Web Services (AWS). Our insights help clients strategize the deployment of massively parallel simulation environments using AWS ParallelCluster, optimize hardware verification using compute-optimized Amazon EC2 instances, and train the machine learning models that will run on edge AI accelerators leveraging Amazon SageMaker on cloud infrastructure.

    What You Receive

    Live Analyst Strategy Session (60 Minutes): Consult directly with a lead Semiconductor analyst to benchmark 3nm/2nm PPA metrics. This private session is tailored to your specific hardware roadmap and AWS cloud integration for EDA workloads.

    Complete Market Data Repository: Gain full access to our underlying research architecture for the Global Integrated SoC Market (2026–2035). Includes granular CAGR data, regional demand shifts for Generative AI silicon, and performance benchmarking for leading fabless designers.

    Executive Action Brief: A custom analysis translating complex chiplet and NPU signals into actionable IT and R&D roadmaps for CPOs and VPs of Engineering to scale silicon innovation on AWS.

    Who Should Engage

    • Chief Technology Officers (CTOs) and VPs of Engineering at Hardware OEMs
    • Semiconductor IT Directors & EDA Infrastructure Leads
    • Venture Capital & Private Equity Partners assessing fabless silicon targets

    Highlights

    • 60-Minute Live Analyst Briefing: Consult directly with a lead Semiconductor analyst to benchmark "Power-Performance-Area" (PPA) metrics for 3nm and 2nm nodes. This session is tailored to your specific hardware roadmap, moving beyond data to address the integration of 5G/6G modems and NPU accelerators.
    • Comprehensive 2035 Market Data Access: Gain full access to our underlying research architecture for the Global Integrated SoC Market. Includes granular CAGR data, regional demand shifts for Generative AI silicon, and performance benchmarking for fabless designers like Qualcomm and MediaTek.
    • AWS Cloud Alignment: Actionable intelligence for hardware leaders, including guidance on scaling EDA workloads with AWS ParallelCluster and optimizing simulations on Amazon EC2.

    Details

    Delivery method

    Deployed on AWS
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    Pricing

    Custom pricing options

    Pricing is based on your specific requirements and eligibility. To get a custom quote for your needs, request a private offer.

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    Support

    Vendor support

    Support Availability: Our analyst team is available Mon-Fri, 9:00 AM - 6:00 PM EST for scheduling briefings and answering follow-up questions.

    Contact Process: Upon purchase, please email us at info@nextmsc.com  with your order ID to schedule your 60-minute analyst briefing. We typically respond to all scheduling requests within 24 hours.

    Scope of Support: Support includes assistance with accessing the market data files, scheduling the advisory session, and clarifying specific data points within the analysis.