Sameer Sahasrabuddhe

𝐈𝐧𝐝𝐢𝐚’𝐬 𝐒𝐞𝐦𝐢𝐜𝐨𝐧𝐝𝐮𝐜𝐭𝐨𝐫 𝐇𝐢𝐫𝐢𝐧𝐠 𝐒𝐮𝐫𝐠𝐞 𝐢𝐬 𝐑𝐞𝐝𝐞𝐟𝐢𝐧𝐢𝐧𝐠 𝐂𝐚𝐫𝐞𝐞𝐫𝐬! The semiconductor industry in India is experiencing an unprecedented hiring boom — gradually chipping away at IT placements and opening exciting opportunities for engineers across domains. 🔹 End-to-end hiring: RTL/SoC design, verification, embedded systems, manufacturing (process, packaging, yield). 🔹 Freshers’ salaries: ₹6–12 LPA (vs. ₹3–4 LPA in IT). 🔹 Aggressive campus recruitment from tier-2 & tier-3 colleges, not just IITs. 🔹 Internships: ₹40k–50k/month stipends to build hands-on chip design skills. 🔹 Hiring scale: ~12,000 freshers annually (up from 8,000 last year). 🔹 Career growth: Roles extend up to ₹20–120 LPA for architects & leaders. Fuelled by global supply chain shifts, EVs, telecom, defence, and government initiatives (DLI, PLI, ECMS), this hiring surge is reshaping student aspirations, especially in ECE and core engineering branches. With India projected to hit $103B semiconductor market by 2030, this is the right time for students and professionals to align their skills with VLSI, Embedded Systems, AI/ML hardware, and semiconductor manufacturing. The future is semiconductor — and India is powering ahead as a global hub! https://lnkd.in/gKtU5Gn2 #Semiconductor #VLSI #ChipDesign #EmbeddedSystems #Electronics #SoC #SemiconductorIndia #SemiconductorJobs #SemiconductorTalent #HiringTrends #Careers #ECE #Engineering #SemiconductorEcosystem #MakeInIndia #Innovation #ElectronicsManufacturing #FutureOfWork #AI #ML #Hardware #Manufacturing #IndiaSemiconductorMission

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🔍 Bandwidth in Analog Circuits — Beyond 3dB and Into the Designer’s Mind “If Gain is the height of your design, Bandwidth is its reach.” And when you chase both… welcome to the world of tradeoffs. Whether you’re designing a simple op-amp or a cutting-edge ADC driver, Bandwidth (BW) is always watching you. Too low? Your signal gets sluggish. Too high? You start pulling in noise, power, and instability. Let’s break this down — not with formulas first — but with intuition, design scenarios, and the real art behind numbers. ⸻ 🧠 What Is Bandwidth, Really? • Bandwidth is the frequency range over which your circuit maintains intended behavior. • In amplifiers: it’s how far the gain stays useful. • In buffers or drivers: it’s how fast they respond without distortion. • In filters: it’s the edge that shapes the signal. 📌 Technically: BW is the frequency at which the gain drops by 3dB (or 70.7% of midband gain). But real designers ask: Why did it drop? What caused it? Can I fight it? ⸻ 🧩 What Limits Your Bandwidth? Let’s decode this with real knobs on your circuit: 🔹 Capacitance (C) – The invisible villain. • Input caps, load caps, Miller effect, wire parasitics. • If your gain stage has a big node to drive, RC delay starts ruling your life. 🔹 Resistance (R) – Sometimes desired, sometimes not. • High output impedance = more gain but slower BW. • Input resistor? Say hello to RC filtering. 🔹 gm (Transconductance) – The hidden hero. • BW ∝ gm/C — more gm = faster transitions. • But gm costs power. Always. 🔹 Gain-BW Product – The ultimate handshake. • Want more gain? You’ll pay with BW. • Want wider BW? Your gain has to shrink or your design must evolve. ⸻ 📚 Case Study Circuits: 📌 1. Common-Source Amplifier • BW ≈ 1 / (2π·Rout·Cout) • Key Insight: The drain node is the slowest. Keep it lean. • Fixes: Reduce load cap, boost gm, or lower Rout. 📌 2. Source Follower (Buffer) • BW ≈ gm / (2π·CL) • Looks simple, but gate-to-drain cap (Cgd) feeds back and ruins high-frequency response. • Intuition: It’s fast, but not always linear. 📌 3. Op-Amp with Miller Compensation • Dominant pole added on purpose via compensation cap. • BW ≈ gm / (2π·Cc·A) → Shrinks with gain. • Case: You don’t just calculate this, you shape it based on phase margin and loop gain. 📌 4. OTA Driving a Sampling Cap (like in ADC) • BW ≈ gm / Cload • But Cload here is not just the cap—it includes switches, parasitics, and layout. • Tip: Always model switches with Ron + C. 📌 5. Differential Pair with Active Load • BW depends on tail current and load cap. • Higher tail current → more gm → better BW. ⸻ 🧠 How to Intuitively Estimate Bandwidth? When you’re on the whiteboard (or fighting with layout), here’s how to think: ✅ See nodes like water tanks • Big capacitance? Big tank. • Small gm? Narrow pipe. ✅ Use the Golden Rule: BW ≈ gm / Ceff Estimate Ceff from layout or parasitic reports. gm from your sizing. ✅ Phase Margin = BW Controller

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This is not a joke post. People are genuinly experimenting with verilog, systemverilog and VHDL. That is a good thing. So, what are the chances that an AI LLM will be trained on non-curated github repo's with HDLs? Well, if we look at a pure sw language, like Python, we see a lot of libraries and code of high quality, written by 10x engineers at trillion dollar companies. LLMs will reach maturity in 2025 with software languages like Python. But for HDLs, even if there would be crazy good code (have you ever seen IP cores and their code quality?) internally to train an LLM, the hardware abstraction part is a difficult one for an LLM. Because it LOOKS like software syntax, for example like embedded software that single threaded executes instructions, but a HDL describes mainly parallel hardware circuitry. You need a very niche trained LLM (MoE?) that is not confused by being trained on any sw language.

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Memory paging in OS: Memory paging is a memory management scheme that eliminates the need for contiguous allocation of physical memory, thereby making more efficient use of available memory and simplifying memory allocation. 👉 Basic Idea 1️⃣ Paging: Divides the virtual memory into fixed-size blocks called pages and the physical memory into blocks of the same size called frames. 2️⃣ Virtual Memory: An abstraction that provides each process with the illusion of a large, contiguous address space. 3️⃣ Physical Memory: The actual RAM available in the system. 👉Key Components 1️⃣ Pages: Fixed-size blocks of virtual memory. Common sizes are 4 KB, 2 MB, or 1 GB. 2️⃣ Frames: Fixed-size blocks of physical memory that correspond in size to pages. 3️⃣ Page Table: A data structure used by the operating system to keep track of the mapping between virtual pages and physical frames. 👉 How Paging Works 1️⃣ Address Translation: When a program accesses a memory address, the virtual address is translated into a physical address using the page table. The virtual address consists of: Page Number: Indexes into the page table. Offset: Specifies the exact location within the page. 2️⃣ Page Table Lookup: The page table entry (PTE) for the page number provides the frame number. The frame number is combined with the offset to produce the physical address. 3️⃣ Page Faults: A page fault occurs if the required page is not in physical memory (not mapped to any frame). The operating system must bring the page from disk (swap space) into a free frame in physical memory and update the page table. 💪 Benefits of Paging 1️⃣ Eliminates Contiguous Allocation Requirement: Physical memory can be used more efficiently since any free frame can be used for any page. 2️⃣ Isolation and Protection: Each process operates in its own virtual address space, preventing one process from accessing the memory of another process. 3️⃣ Simplifies Memory Management: The operating system can manage memory in fixed-size blocks, simplifying allocation and deallocation. ✅ Summary Memory paging is a powerful technique that provides the benefits of virtual memory without the drawbacks of contiguous physical memory allocation. It allows systems to efficiently manage memory, ensure process isolation, and simplify memory allocation and deallocation through the use of fixed-size pages and frames. #paging #os #kernel #linux #embedded #learning #systemdesign

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Why we have to worry about setup and hold time in flip flops? Setup and hold times are critical timing parameters in flip-flops because they ensure reliable and predictable data capture. Violating these constraints can lead to incorrect data being latched, causing functional errors in digital circuits. Here’s a clear breakdown: ⸻ 🔧 What are Setup and Hold Times? • Setup Time (Tsetup): The minimum time before the clock edge that the data input (D) must be stable. • Hold Time (Thold): The minimum time after the clock edge that the data input must remain stable. ⸻ 🔍 Why Do We Worry About Them? 1. To Ensure Reliable Data Capture Flip-flops work by sampling the data at the rising or falling clock edge. If data changes too close to the clock edge: • The flip-flop may enter a metastable state (undefined or oscillating output). • It may capture incorrect data. • This can propagate errors through the rest of the system. 2. Prevent Metastability When setup or hold times are violated: • The internal circuitry may not resolve cleanly to a ‘1’ or ‘0’. • Metastability can persist for unpredictable durations, leading to random system behavior. 3. Timing Closure in Design In digital design (ASIC/FPGA): • Static Timing Analysis (STA) checks all paths to meet setup and hold constraints. • Violations can prevent the chip from working at the desired clock frequency. ⸻ 🧠 Real-world Analogy: Imagine taking a photograph with a camera: • Setup time: The subject must be still before you press the shutter. • Hold time: The subject must remain still immediately after the shutter clicks. If they move during either, you get a blurry photo — the flip-flop’s output is like that blurry photo: unusable. In Summary Setup Time => Data Must be stable Before clock edge … If violated… Data may not be captured correctly Hold Time=> Data Must be stable After clock edge If violated… May cause metastability or wrong data So, we worry about setup and hold times to guarantee proper functionality, avoid timing violations, and ensure robust digital system performance.

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India’s digital economy will touch $1T by 2030. We’ll need chips for everything—from smart remotes to rockets. But despite a ₹76,000 Cr incentive, a $100Bn domestic electronics market, and the world's largest VLSI talent pool, India still isn’t building its own semiconductors at scale. Here’s why the “garage startup” mindset doesn’t work for fabless semicon. And what we must do to break the cycle. 👇 BigEndian Semiconductors #semiconductors #makeinindia #fabless #ic #startupindia #startup

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🚀 ChipIN Centre is now empowering ~350 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 across India 🇮🇳 (𝘪𝘯𝘤𝘭𝘶𝘥𝘪𝘯𝘨 280 𝘢𝘤𝘢𝘥𝘦𝘮𝘪𝘤 𝘪𝘯𝘴𝘵𝘪𝘵𝘶𝘵𝘪𝘰𝘯𝘴 𝘢𝘯𝘥 70 𝘴𝘵𝘢𝘳𝘵-𝘶𝘱𝘴) with access to cutting-edge EDA tools, Compute Hw, Emulator & FPGA, Fab VCA, Trainings and R&D funding. 💡Driving innovation and capability in semiconductor design in collaboration with - Synopsys Inc | Cadence | Siemens | Keysight Technologies | Ansys | Silvaco Inc | Xilinx | IBM | Renesas Electronics | imec | #SCLMohali 👉 𝐋𝐢𝐬𝐭 𝐨𝐟 280+ 𝐚𝐜𝐚𝐝𝐞𝐦𝐢𝐜 𝐢𝐧𝐬𝐭𝐢𝐭𝐮𝐭𝐢𝐨𝐧𝐬 𝐬𝐮𝐩𝐩𝐨𝐫𝐭𝐞𝐝 𝐮𝐧𝐝𝐞𝐫 𝐂2𝐒 𝐏𝐫𝐨𝐠𝐫𝐚𝐦𝐦𝐞 🌐 https://lnkd.in/d4jcb7e2 👉 𝐋𝐢𝐬𝐭 𝐨𝐟 70+ 𝐬𝐭𝐚𝐫𝐭-𝐮𝐩𝐬 𝐬𝐮𝐩𝐩𝐨𝐫𝐭𝐞𝐝 𝐮𝐧𝐝𝐞𝐫 𝐃𝐋𝐈 𝐒𝐜𝐡𝐞𝐦𝐞 🌐 https://lnkd.in/d928jFbF Read for available support for National chip design infrastructure at https://lnkd.in/dUPA4r4f #ChipsforViksitBharat #DigitalIndia #IndiaTechade #C2SProgramme #DLIScheme Ashwini Vaishnaw | S Krishnan | Abhishek Singh | ashok chandak | Sanjeev Keskar

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Topic :UVM TLM -Transaction Level Modeling Post No: 25 WHAT IS TLM ? 1. Message passing system 2. TLM Interface 1. Ports- set of methods Ex. Get(), Put(), Peek() etc 2. Exports/Imp- Implementation for the METHODS WHY TLM ? 1. TLM Stands for Transaction Level MODELING 2. TLM Promoted Re-usability as they have same .interface 3. Interoperability for mixed language verification environment 4. Maximizes reuse and minimize the time and effort Benefits of using TLM in Chip Design Verification 1. High-Level verification 2. Code Reusability 3. Reduced risk of errors 4. Easy component swapping #Happy_learning 😊 #learn_without_limitations_ #learning_phase_

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Chip Validation is Broken—And It's Costing the Industry Billions NVIDIA ($2T market cap), Intel ($150B+), AMD ($300B) — all pushing the limits of chip design. But nobody’s talking about the hidden bottleneck slowing their progress: Validation inefficiencies that delay launches and burn resources. These aren’t isolated issues. They’re systemic failures. Before a chip hits the market, it undergoes extensive testing to ensure it performs as expected under real-world conditions. This process—chip validation—is crucial for verifying functionality, performance, and reliability. But validation today is painfully slow. Engineers spend weeks scripting and running tests manually, dealing with fragmented tools, and sifting through scattered data to debug issues. The result? Delays, inefficiencies, and skyrocketing costs. The Broken Playbook -Weeks spent scripting tests instead of analyzing results -Scattered data across tools, slowing debugging cycles -Manual processes introducing errors and inefficiencies Behind the cutting-edge innovation lies a brutal truth: Validation is stuck in the past the last software that was built for validation released in 2001 (LabView). The Future of Validation: A new era is emerging: Automated, AI-driven validation workflows. And the results are game-changing: 20x faster test execution Fewer errors, more actionable insights Seamless collaboration across teams At Atoms, we’re not just talking about the future—we’re building it: One platform to automate and accelerate chip validation AI-assisted workflows to streamline debugging Real-time insights for faster decision-making Because while traditional validation burns months, the companies of the future are already moving at light speed. The old methods had their time. The age of AI-powered validation has begun. #Semiconductors #ChipValidation #FasterTimeToMarket #TestFlow

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Direct Memory Access (DMA) is a critical feature in VLSI design that enhances data transfer efficiency between memory and I/O devices without burdening the CPU. ### What is DMA? DMA allows peripherals to access the main memory independently of the CPU, enabling faster data transfer rates and freeing up CPU resources for other tasks. This is particularly useful in applications requiring high-speed data transfer, such as video processing, audio streaming, and network communications. ### Key Features of DMA: 1. **Efficiency**: Reduces CPU involvement in data transfers, allowing it to perform other computations. 2. **Speed**: Enables higher data transfer rates compared to programmed I/O methods. 3. **Multitasking**: Facilitates concurrent operations, improving overall system performance. ### DMA Operations: Steps of DMA Transfers The DMA operation typically involves several key steps, which can be summarized as follows: 1. **Initialization**: - The CPU configures the DMA controller by setting parameters such as source address, destination address, and the number of bytes to transfer. - The DMA controller is also enabled to begin the transfer process. 2. **Requesting Transfer**: - The peripheral device that needs to transfer data sends a request to the DMA controller (often referred to as a "DMA request"). - Upon receiving the request, the DMA controller checks if the bus is available for data transfer. 3. **Bus Arbitration**: - If multiple devices request access to the bus, the DMA controller arbitrates to determine which device gets access first. - Once granted access, the DMA controller gains control of the system bus. 4. **Data Transfer**: - The DMA controller initiates the data transfer from the source (e.g., peripheral) to the destination (e.g., memory). - The transfer occurs without CPU intervention, allowing the CPU to execute other tasks simultaneously. 5. **Transfer Completion**: - After the specified amount of data has been transferred, the DMA controller sends an interrupt signal to the CPU to indicate that the transfer is complete. - The CPU can then check the status of the transfer and proceed with any required follow-up actions. 6. **Deactivation**: - The DMA controller releases the bus, allowing other devices or the CPU to use it for their operations. - The controller can be reconfigured for subsequent transfers as needed. ### Example Use Case Consider a scenario where a video camera captures frames and needs to transfer them to memory for processing. Using DMA, the following occurs: - The CPU initializes the DMA controller with the frame buffer's starting address and size. - The camera sends a DMA request to transfer the frame data. - The DMA controller gains control of the bus and transfers the frame data directly into memory. - Upon completion, the DMA controller interrupts the CPU, signaling that the frame is ready for processing. #dma #dmacontroller #bus #arbitration #vlsi

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