SolvEx Group

✅ Beyond 1nm: The Future of VLSI, Emerging Technologies, and the Evolution of Microelectronics ✅ Most recommended for Undergraduates and VLSI Aspirants, do follow for daily updates Outline •Challenges of Scaling Below 1nm • Is VLSI Dead? • Future Trends in VLSI • Emerging Technologies • Neuromorphic Computing • Quantum Computing 👉 👉 Please do follow & do share 👉 👉 For more information do follow ProV Logic or Prasanthi Chanda

This is cool a Lattice FPGA on a Micro SD Card from Signaloid, it uses OS tools and can be programmed just by dropping it in to the SD Port on your PC.

Apply Now for MeitY-HARTRON-nasscomCoE Incubation Program Are you a startup ready to grow and scale? The CoE Incubation Program is here to help you reach new heights. What we offer: - Expert Mentorship -Market Connects -Subsidized Co-working Space -Investor Connects   -Prototype Lab Additionally, CoE partners with industry leaders and enterprises, providing you with valuable use case opportunities that foster both learning and growth. This is your chance to be part of an ecosystem that supports innovation and scale. Apply Now for Zero Equity Incubation Program via https://lnkd.in/dADFeJ4J Should you have any inquiries or require additional information, feel free to reach us at Sudhanshu@nasscom.in. #nasscomCoE #indianstartups #innovationinindia #techrevolution #AI #machinelearning #quantumcomputing #biotechnology #startupecosystem #investment #disruptiveinnovations #indianinnovation #startupindia #marketpotential #hic #healthtech #healthcareinnovation #robotics #dronetechnology #startupincubation

OSS-ECAL Introduction in PDF format. You can also download it from the site. https://lnkd.in/guVdYUtN We will continue to do our best to help everyone understand OSS-ECAL as much as possible! Thank you. Best regards, Mitsuaki.

Disseminating information A System on Chip (SoC) integrates essential electronic components into a single microchip, including: Central Processing Units (CPUs): Execute instructions and manage tasks. Memory Units: Store data and instructions temporarily. Graphics Processing Units (GPUs): Handle rendering of images and videos. Connectivity Modules: Enable communication via Wi-Fi, Bluetooth, and other protocols. SoCs are designed by tech giants like Apple, Qualcomm, MediaTek, Samsung Semiconductor, and NVIDIA. They are manufactured by cutting-edge foundries like TSMC, Global Foundries, Foundry Samsung, Intel Corporation and many more. Today let's explore the main components inside an SoC and the key players who design or manufacture those. 🥇Note:"In my earlier post,as the final slide included the credits,I chose not to list them separately."✍️ 🥇"I aimed to share practical insights from my daily experiences, serving as a link between diverse groups of people."💡 Credits:Dr. Anu Asokan

OpenAI has announced o3, which appears to be the most powerful AI model to date. There has been some attention given to the massive dollar costs of running this model, but its environmental costs have been ignored. Using cost data from OpenAI's benchmark results, we can estimate the energy and carbon footprint of a single task on the ARC-AGI benchmark (for the high-compute version of o3). Each task consumed approximately 1,785 kWh of energy—about the same amount of electricity an average U.S. household uses in two months. This translates to 684 kg CO₂e, based on last month's U.S. grid emissions factor. To put that into perspective, that's equivalent to the carbon emissions from more than 5 full tanks of gas! While o3 is meant to show the cutting edge of AI capability, we need to be paying more attention to the tradeoffs as we start to scale and integrate this technology. There are sustainable ways to use AI to positively impact the world. Assumptions/Sources: - o3 cost data: https://lnkd.in/gTUix3uv - $1.50 per H100 GPU Hour (low end assumed) - 700W TDP of H100 (assumes compute at full TDP) - 1.125 PUE (Microsoft ave) - 12154 kWh per home per year (EPA) - 383 gCO2e/kWh (Nov 2024 US average per Electricity Maps) - 8.89 kg CO2e/gallon of gas (EPA) - 15 gallons of gas per car (EPA) Note that this doesn't include embodied carbon and is focused just on the GPU, so is likely an underestimate. Edit: here's the underlying math - if anything seems off please let me know: $3,400 per task (high tuned o3) $1.5 per H100 GPU hour (I believe this is realistic because ARC-AGI says "retail cost") =2,267 H100 GPU hours 700 watt TDP (this is obviously on the highest side, but there are some underestimates later that I think outweigh this) 1.125 PUE (Microsoft average) =1,785 kWh

🔥 70 pitch decks of top startups that raised over >$1bn in 2024📈🤑 Curious what the pitch decks of the top startups look like that are currently raising massive rounds? So here I am! Access over 70 decks my friend Maximilian Fleitmann designed that were used to raise money in 2024. This swipe file is perfect if you need inspiration on: - What to include in your pitch deck - How to tell your story - How to design your deck I've recently featured them in my newsletter focused on resources for founders and investors. To make it easier for you to explore I've just enabled a free trial so you can access all the decks. Take a look here 👇 https://lnkd.in/dKKZASXM

Verilog: comb & seq. Codes

Debugging Low-Level Device Drivers: Techniques for Success🛠️ Developing low-level device drivers is challenging enough, but debugging them can be a whole new level of complexity. When you're working close to the hardware — initializing peripherals, managing registers, or handling interrupts — small errors can lead to system crashes, silent failures, or unpredictable behavior. Here are some essential techniques for debugging low-level drivers effectively: 🧰 Key Debugging Techniques 🧰 1️⃣ Logging with UART/Serial Output - 📡 Why It Helps: When traditional debugging tools can't be used, adding debug messages via UART or serial output can provide real-time insights. - 🔍 Best Practice: Use concise messages to track the flow of execution, register values, and error states. Ensure logs can be toggled on/off to reduce overhead. 2️⃣ Hardware Breakpoints and JTAG Debuggers - 🛑 Why It Helps: Hardware breakpoints stop the system at specific points, allowing you to inspect memory, registers, and call stacks. - 🔧 Tools to Consider: JTAG/SWD debuggers (e.g., Segger J-Link, Lauterbach, or OpenOCD) enable detailed real-time analysis of the system state. 3️⃣ LED Indicators - 💡 Why It Helps: A simple LED can be invaluable in pinpointing where a driver hangs or fails during initialization. - 🏁 Use Case: Flash different patterns to indicate various states or errors. It's a simple but effective method for quick diagnostics when other options are unavailable. 4️⃣ Oscilloscopes & Logic Analyzers - 📊 Why It Helps: Visualizing signals (e.g., SPI, I2C, GPIO) can confirm if the hardware communication matches expectations. - ⚙️ Use Case: Verify timing constraints, clock signals, and data transfers to detect glitches or protocol issues. 5️⃣ Memory Inspection and Analysis - 🧠 Why It Helps: Low-level bugs often involve incorrect memory access or corruption. - 🔎 Technique: Use debuggers to inspect stack/heap regions or leverage tools like valgrind and memwatchfor dynamic analysis (where applicable). 6️⃣ Kernel Debugging (for OS-Based Drivers) - 🐧 Why It Helps: If you're working with Linux or RTOS-based drivers, tools like kgdb, ftrace, and dmesg, can provide detailed logs and live debugging. - 📄 Tip: Always check kernel logs for error messages and warnings related to driver failures. 7️⃣ Assertions and Watchpoints - ✅ Why It Helps: Adding assertions ensures that critical conditions are met during execution. Watchpoints let you track specific memory addresses for unexpected changes. - 🚨 Best Practice: Use assertions to catch anomalies early and identify code paths that lead to hardware misbehavior. 🛠️ Practical Tips 🛠️ ✅ Incremental Development: Develop and test driver functions step-by-step to isolate issues more easily. ✅ Code Reviews: Peer reviews plays very important role.

Most researchers make a fatal mistake in their proposal's introduction, but understanding the "Why-What" sequence can change everything... Here's a 15-part structure I use that makes it simple. Let's break it down into 7 broad steps: 1. Start with why it matters in context • State your research purpose • Hook readers with significance 2. Back up claims in literature • Map the existing knowledge • Find the gaps to fill 3. Define your focus • Research problem • Research questions • Clear objectives 4. Plan your approach • Pick your theory • Choose methods • Set data collection strategy 5. Get practical • Plan your analysis • Address ethics upfront 6. Look ahead • Create timeline • Show impact • List expected results 7. Finish strong • Add references • Include appendices Each section answers one or more of these key questions: Why? What? How? Who? When? This structure works because it flows from broad context to specific details. No complexity needed. Just clear thinking and focused writing. Get a FREE guide here: https://lnkd.in/eev8U5K5 P.S. Have you written a research proposal yet? #phd #research #gradschool