Hu-mind.ai

Can Gen AI solve the chip specification problem? At DAC last week, a panel of experts from IP, product, and Gen AI EDA companies discussed how rising chip complexity is causing specification quality to decline and documentation time to increase. Key issues raised included: - Incomplete and ambiguous specs that force engineers to fill in gaps. - Critical architecture details remain undocumented in the architect's mind. - Misalignment between Design and Verification teams. - A lack of system behavior requirements, test parameters, and power considerations. While some suggested dedicated agents for IP or SoC architecture, these narrow solutions often break in new scenarios. At Hu-mind.ai, our 30 years of experience in chip architecture has taught us that the solution lies in applying proven methodologies with the speed and scale of AI. As complexity increases, both humans and AI face limits when just digesting data. Experienced human architects address this by creating high-level models to simulate and check hypotheses. Although the industry created SystemC, TLM, and Python for this purpose, these tools are often underutilized because they require specialized expertise and significant time, sometimes leading to costly, late-stage architecture bugs. What if an AI-based VLSI teammate could handle this for you? In our latest white paper, "CPU Subsystem cycle accurate SystemC model", we prove this is a reality. we describe how our VLSI Teammate autonomously created a fully tested, transaction-accurate SystemC model from an existing complex SoC design and verification environment in just 4.5 days. With an AI VLSI teammate, architects can now easily: - Digest documents and datasheets. - Create and iterate on architecture design specifications. - Build software models based on specs and run performance simulations. - Generate SystemC models from existing designs or IPs. - Create full test and performance requirement sections based on simulated scenarios. - Identify peak power consumption scenarios. Read the white paper to learn more about how we are applying the speed and scale of AI to proven methodologies! 👇 https://lnkd.in/g9asCKAr #GenAI #VLSI #DAC2026 #SystemC #HuMindAI

Autonomous VLSI verification is here. And yes, it is 𝟭𝟬𝟬% 𝗮𝗶𝗿-𝗴𝗮𝗽𝗽𝗲𝗱. 🛑🔌 Following up on our recent milestone—where Hu-mind.ai’s 𝗩𝗟𝗦𝗜 𝗧𝗲𝗮𝗺𝗺𝗮𝘁𝗲 autonomously pushed a V-Mate RISC-V System on a Chip coverage from 44% to >90%—we wanted to highlight 𝘩𝘰𝘸 the Teammate operates. We know IP security is non-negotiable. That is why this entire workload was executed using: ✔️ Completely air-gapped systems ✔️ AI models running locally on bare-metal hardware ✔️ Zero external internet access We are bringing autonomous, commercial-grade EDA execution directly to your secure servers. Your data never leaves your environment. Want to learn more about deploying secure, on-prem AI for your next tape-out? Let's connect. #Semiconductors #HumindAI #VLSIDesign #AirGapped #InformationSecurity #AIHardware #RISCV #TapeOut

🚀 Pushing the boundaries of autonomous chip verification with Hu-mind.ai ! We recently put our virtual VLSI Teammate to the test on a complex verification closure task, and the results speak for themselves. We challenged our AI agent to take over the verification of a highly pipelined RISC-V 32-bit (RV32I) privileged core—complete with a Harvard-style memory subsystem, DMA controller, and dynamic clock gating. Here is how our virtual teammate performed using real, commercial EDA tools, entirely autonomously: 📉 The Starting Point: We started with a baseline coverage of roughly ~44% across 26 modules (Line: 44.5%, Condition: 50%, Branch: 38%). 🛠️ The Process: Without manual human intervention, our VLSI Teammate analyzed the design, generated test stimuli, and ran the regressions through commercial EDA pipelines to systematically close coverage holes. It even successfully handled mathematical exclusions for structural toggle bins that couldn't be toggled by any stimulus. 📈 The Final Result: The AI agent successfully drove the DUT coverage to >90% across the board! LINE: 99.62% ✅ COND: 90.58% ✅ BRANCH: 94.15% ✅ TOGGLE: 90.04% (adjusted) ✅ Achieving tape-out ready verification metrics is notoriously time-consuming, but the future of hardware engineering is collaborative. By letting AI handle the heavy lifting of coverage closure, your engineers can focus on architecture, innovation, and solving complex system-level problems. Curious to see how a virtual VLSI Teammate can accelerate your next tape-out? Let's connect! - https://lnkd.in/dv6Pqzhw #VLSI #Semiconductor #ChipDesign #Verification #EDA #RISCV #ArtificialIntelligence #MachineLearning #HumindAI #FutureOfWork

AI in VLSI is no longer just about generating simple code snippets. To evaluate whether AI can handle a realistic industrial-scale semiconductor task, we didn't hold back on the V-Mate architecture. Our VLSI teammate successfully navigated iterative debugging, standards compliance, and performance optimization. The final processor architecture features: - A 5-stage pipelined architecture. - Full forwarding and hazard units. - IEEE-754 compliant floating-point support. - Machine mode support for privileged architecture. - Fine-grain clock gating for power optimization. During development, the Teammate actively resolved highly complex issues, including deadlocks, X-propagation, and floating-point invalid operation handling. It acts as a true engineering teammate. Check out V-Mate [https://lnkd.in/eahu5SEj] #Architecture #Engineering #RTL #ProcessorDesign #HuMind #ChipDesign #AI #RISCV

Get AI Assistance for Your Open-Source VLSI Project!!! Open-source VLSI projects push our industry forward, but hardware design takes a massive amount of time. Maintainers and contributors often get bogged down by tedious verification setups, hunting down RTL bugs, or writing documentation. What if you could delegate those tasks? Today, we are opening up Hu-mind.ai’s virtual VLSI teammates to the open-source community. You can now request an AI agent to join your repo and help you tackle your backlog. Whether you need help with: Resolving tricky RTL bugs Implementing specific design changes Improving your verification environment Updating project documentation Simply drop your repository URL in our portal, tell us what you need, and let an AI teammate do the heavy lifting. Check out the request form here and let us know what you are building: [https://lnkd.in/dPKTC2Nm] #VLSI #OpenSourceHardware #AI #Semiconductors #HardwareDesign #RTL