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今天

  • A Synopsys Webinar Detailing IP Requirements for Advanced AI Chips

    ➀ The webinar discusses the impact of generative AI on technology evolution and the rise in compute power demand.

    ➁ It covers the trends in larger compute chips, multi-die systems, advanced packaging, and memory architectures.

    ➂ Key technologies like die-to-die communication, custom HBMs, and 3D stacking are explored in detail.

  • March 31

  • CEO Interview with Matthew Stephens of Impact Nano

    ➀ Matthew Stephens of Impact Nano has over 20 years of experience in advanced materials commercialization.

    ➁ Impact Nano is a tier 2 supplier specializing in advanced materials for semiconductor manufacturing.

    ➂ The company addresses challenges in materials innovation, scale-up, and manufacturing sustainability.

  • An Important Advance in Analog Verification

    ➀ Mach42的发现平台利用机器学习创建一个代理模型,以实现更快的电路设计探索,而无需进行完整的SPICE模拟。

    ➁ 平台的目标是达到90%的准确率,允许快速迭代,同时保留在最终确认时进行完整准确性的选项。

    ➂ Mach42正在与Cadence合作开发Spectre,并计划开发Verilog-A模型,这可能会显著增强模拟-数字设计验证。

  • March 30

  • Semiconductor CapEx Down in 2024 up in 2025

    ➀ Semiconductor capital expenditures (CapEx) are expected to decrease to $155 billion in 2024, before increasing to $160 billion in 2025.

    ➁ TSMC plans a significant increase in CapEx for 2025, estimating between $38 billion and $42 billion, while Micron Technology is projecting $14 billion.

    ➂ The CHIPS Act has allocated $32 billion in grants and $6 billion in loans to support semiconductor manufacturing in the U.S.

  • March 28

  • CEO Interview with Dr Greg Law of Undo

    ➀ Undo's technology enables engineers to see exactly what their code did, facilitating root-cause analysis and improving collaboration.

    ➁ Undo is prominent in industries such as semiconductor design, databases, and networking, where debugging efficiency is critical.

    ➂ Undo's solution helps customers overcome challenges like development bottlenecks and missed deadlines by improving debugging processes.

  • March 27

  • Upcoming Webinar: Accelerating Semiconductor Design with Generative AI and High-Level Abstraction

    ➀ Rise Design Automation has developed a solution that integrates generative AI with human expertise to improve RTL design productivity.

    ➁ The webinar hosted by RDA and SemiWiki will showcase how generative AI can enhance semiconductor design through high-level abstraction.

    ➂ The Rise AI solution translates natural-language intent into high-level design code, reducing manual effort in the design process.

  • March 26

  • CEO Interview with Jonathan Klamkin of Aeluma

    ➀ Aeluma通过结合高性能材料和可扩展的硅制造技术,重新定义了半导体技术;

    ➁ Aeluma的技术在AI基础设施、国防、量子计算和下一代传感等领域产生了重大影响;

    ➂ Aeluma正在解决AI和高性能计算在扩展方面遇到的挑战,通过集成化合物半导体和大型衬底来实现大规模生产。

  • March 25

  • Webinar: RF board design flow examples for co-simulating active circuits

    ➀ This webinar series focuses on 3D passive vendor component models for accurate EM-circuit co-simulation of high-frequency RF board designs.

    ➁ It explores simulating active circuits on boards using Modelithics models in Keysight EDA software.

    ➂ The Modelithics COMPLETE Library supports accurate simulations and provides a ready bill of materials.

  • Ceva-XC21 and Ceva-XC23 DSPs: Advancing Wireless and Edge AI Processing

    ➀ Ceva recently unveiled the XC21 and XC23 DSP cores for advanced wireless and edge AI processing;

    ➁ The XC21 is optimized for low-power, high-performance applications in cost-sensitive markets;

    ➂ The XC23 provides significant performance improvements for high-end communications with AI capabilities.

  • March 24

  • CEO Interview with Brad Booth of NLM Photonics

    ➀ Brad Booth, CEO of NLM Photonics, discusses his background in technology strategy.

    ➁ NLM Photonics aims to reduce power consumption in photonics by 50%.

    ➂ The company addresses the high power demands of AI data centers and focuses on energy-efficient modulation.

  • Going Beyond DRC Clean with Calibre DE

    ➀ Achieving design rule compliance and optimal electrical performance in advanced semiconductor designs is crucial for minimizing design iterations and ensuring product reliability.

    ➁ Siemens Digital Industries Software's Calibre DesignEnhancer (DE) provides analysis-based EMIR solutions that enhance power integrity and reduce IR drop.

    ➂ Both Google and Intel utilized Calibre DE to address IR drop issues, demonstrating significant improvements in power grid robustness and electrical performance.

  • March 20

  • Cut Defects, Not Yield: Outlier Detection with ML Precision

    ➀ Aggressive testing in chip manufacturing often leads to the discarding of marginally functional chips, causing waste.

    ➁ Traditional testing methods like PAT have limitations in detecting subtle defects.

    ➂ proteanTecs' outlier detection solution uses machine learning to enhance chip reliability and performance.

  • March 19

  • 2025 Outlook with James Cannings QPT Limited

    ➀ QPT Limited致力于通过高频GaN电机驱动创新降低全球电力消耗5%;

    ➁ 2024年,与ABB合作开发了世界上首个1MHz GaN基7.5KW电机驱动;

    ➂ 预计2025年通过与ABB项目成果的战略合作伙伴关系,推动公司增长。

  • Compute and Communications Perspectives on Automotive Trends

    ➀ Automotive electronics is advancing rapidly, focusing on autonomy, electrification, and car cockpit improvements.

    ➁ The need for advanced functionality is high, but OEMs aim to minimize costs and maximize software-driven features.

    ➂ Modern cars are equipped with multiple sensors, including cameras, radar, and lidar, requiring advanced fusion and processing techniques.

  • March 17

  • How FD-SOI Powers the Future of AI in Automobiles

    ➀ The automotive industry is experiencing a revolution with the rise of software-defined vehicles and AI integration.

    ➁ Traditional ECU architectures are shifting towards centralized and zonal designs for efficiency and data handling.

    ➂ Soitec's FD-SOI technology is crucial for enhancing performance, energy efficiency, and reliability in next-generation automotive applications.

  • March 14

  • CEO Interview with Fabrizio Del Maffeo of Axelera AI

    ➀ Axelera AI, founded in 2021, aims to provide scalable edge AI hardware and software solutions.

    ➁ The company has raised USD 120 million and has a world-class team of over 190 employees.

    ➂ Axelera AI's Metis platform offers high performance with low power consumption, targeting applications like computer vision, automotive, and healthcare.

  • March 13

  • A Realistic Electron Blur Function Shape for EUV Resist Modeling

    ➀ The resolution in lithography is influenced by image blur in addition to wavelength and numerical aperture, which impacts image contrast and sensitivity to stochastic effects.

    ➁ Blur originates from various factors including flare, image fading, stage desynchronization, and electron behavior.

    ➂ Incorporating electron blur into lithography models is crucial for improving image resolution and reducing defectivity in advanced semiconductor manufacturing.

  • Siemens Fleshes out More of their AI in Verification Story

    ➀ Siemens EDA在AI方面的深度,包括1400名AI专家和近4000项专利;

    ➁ 随着芯片复杂性的增加,行业预计到本世纪末将短缺27,000名专家设计师;

    ➂ Siemens利用三种类型的AI在验证领域:基于无监督学习的分析型AI、基于机器学习和统计分析的预测型AI,以及基于大型语言模型的生成/代理支持型AI。

  • March 12

  • CEO Interview with Dinesh Bettadapur of Irresistible Materials

    ➀ Dinesh Bettadapur is the CEO of Irresistible Materials, a company specializing in EUV resist materials for semiconductor manufacturing.

    ➁ The company's MTR™ platform addresses limitations of traditional resist materials and offers significant cost savings.

    ➂ Irresistible Materials focuses on collaboration with leading semiconductor manufacturers and developing innovative solutions for EUV lithography.

  • March 11

  • CEO Interview with Pierre-Yves Lesaicherre of Finwave CEO

    ➀ Finwave Semiconductor CEO Pierre-Yves Lesaicherre discusses his extensive experience in the semiconductor industry and his leadership at Finwave.

    ➁ The company's strategic partnership with GlobalFoundries for GaN-on-Si technology development and licensing is highlighted.

    ➂ Lesaicherre addresses the challenges of introducing new technology and the company's solutions for high-frequency RF communications.

  • March 10

  • Speeding Up Physical Design Verification for AMS Designs

    ➀ This article discusses the challenges of physical design verification for custom and analog/mixed-signal IC designs.

    ➁ It introduces Siemens' Calibre Pattern Matching tool for early-stage physical verification.

    ➂ The tool allows for interactive symmetry checking and early IP placement verification, reducing design time and improving quality.

  • March 7

  • S2C: Empowering Smarter Futures with Arm-Based Solutions

    ➀ S2C在亚太地区2024年Arm技术研讨会后,推出了针对智能视觉物联网和下一代汽车技术的解决方案;

    ➁ S2C的基于Arm的智能视觉参考设计和混合MCU原型设计平台,帮助开发者加速产品开发,提高效率;

    ➂ S2C与Arm的合作,为开发者提供了加速创新和满足对更智能、更高效解决方案不断增长需求的途径。

  • March 6

  • AlphaDesign AI Experts Wade into Design and Verification

    ➀ The article discusses the role of AI experts in advancing AI for design and verification.

    ➁ It highlights the potential of AI in revolutionizing productivity and the challenges it poses in terms of precision in engineering.

    ➂ The company AlphaDesign, founded by William Wang, is introduced, focusing on their solution ChipAgents™ which uses LLM agents for design and verification tasks.

  • March 5

  • CEO Interview with Pradyumna (Prady) Gupta of Infinita Lab

    ➀ Dr. Prady Gupta is the Founder and Chief Scientist at Infinita Lab and Infinita Materials, focusing on materials testing and specialized chemicals for high-tech industries.

    ➁ Infinita Lab offers a network of over 2,000 accredited labs for comprehensive materials testing services.

    ➂ Infinita Materials specializes in custom inorganic chemicals for sectors like semiconductors and batteries.

  • March 4

  • Executive Interview: Steve Howington of the High Performance Flooring Division of Sherwin-Williams

    ➀ Sherwin-Williams is a global leader in protective coatings for semiconductor fabs.

    ➁ The company addresses challenges like tight deadlines and labor shortages with efficient solutions.

    ➂ Steve Howington emphasizes the company's partnership approach and expertise in semiconductor construction.

  • Unlocking the cloud: A new era for post-tapeout flow for semiconductor manufacturing

    ➀ The complexity of semiconductor chip design has increased the demand for scalable cloud solutions in post-tapeout flow management.

    ➁ Cloud platforms offer dynamic scaling and cost-effective resource management.

    ➂ Strategic partnerships and cloud services like Siemens EDA and AWS are revolutionizing PTOF processes.

  • March 3

  • SemiWiki Outlook 2025 with yieldHUB Founder & CEO John O’Donnell

    ➀ yieldHUB在2024年扩展了其数据科学团队,推动了AI集成和现有客户基础的扩大;

    ➁ 公司面临在开发下一代平台的同时满足当前平台增长需求的挑战;

    ➂ yieldHUB即将推出yieldHUB Live,这是一款AI驱动的实时监控系统,旨在改进测试流程和减少停机时间。

  • Powering the Future: How Engineered Substrates and Material Innovation Drive the Semiconductor Revolution

    ➀ Engineered substrate technology is driving the semiconductor industry from traditional planar scaling to innovative materials and 3D integration.

    ➁ Companies like Soitec, Intel, and Samsung are leading the adoption of this technology.

    ➂ Foundries are increasingly recognizing the strategic importance of engineered substrates like Fully Depleted SOI (FD-SOI) for their benefits in cost and performance.

  • February 28

  • CEO Interview: Dr. Andreas Kuehlmann of Cycuity

    ➀ Cycuity specializes in semiconductor security products and services.

    ➁ The Radix platform provides early detection of security weaknesses.

    ➂ Dr. Kuehlmann emphasizes the importance of security in semiconductor design.

  • February 27

  • The Double-Edged Sword of AI Processors: Batch Sizes, Token Rates, and the Hardware Hurdles in Large Language Model Processing

    ➀ AI software modeling represents a significant shift from traditional programming, enabling systems to learn from data.

    ➁ The complexity of AI systems lies in their model parameters, which can number in the billions or trillions.

    ➂ GPUs have become essential for AI processing, but they face efficiency challenges, particularly during inference with large language models.

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