Niti Gupta

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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Importance of Testcase in ASIC Verification in VLSI (Complete details with Categorization): A Testcase in any language is used to verify the functional correctness and the integrity of the design. Its basic functionality is to check whether the design is meeting its requirement as per the specification [1] Functional Tests --> In this type of test, the functionality or feature of an IP/module or a subsystem is verified a. Data transfer like read and write cycle, address and data phase, wait states. b. Protocol checks or feature specific to IP, FSM verification c. Command based training, sequence checks and Data Path checks d. Fault and error injection tests, calibration tests [2] Register-based Tests --> RW Tests, RO/WO Tests, Default Read/Hard reset Tests, Soft reset tests, Negative RO/WO Tests, Aliasing, Broadcasting, Special Register test. [3] Connectivity Tests [4] Clock and Reset Tests [5] Boot up Tests, wake up sequence, training sequence tests. For eg. In the case of DDR – MPC Training, RD DQ Calibration, Command Bus training, Write leveling, etc [6] Command and Sequence-based Tests. [7] Overlapping and Unallocated Region tests. [8] Back-to-back data transfer-based tests. [9] UPF Tests --> Power domain, Level Shifter, etc [10] Code Coverage Tests --> In this test toggle, expression, branch, FSM, and conditional coverage holes are measured, and depending on the holes, tests are being written to completely exercise the DUT [11] Functional Coverage Tests --> In these types of test categories, the functionality of DUT is being measured with the help of bins. There are several ways to do it. If there are coverage holes, more bins are coded to cover those areas, complex scenarios are covered with cross coverage. [12] Assertion checks --> Can be thought of as a check against the design. Basically, these are insertion points within the design which improve the observability and debugging ability. [13] C based test for processors and CPU. [14] GLS But to achieve all the above features, testcases are broadly classified into the following two types: [1] Directed Testcase: These are the scenarios that the verification engineers can think of or can anticipate. [2] RandomTestcase: These are the scenarios where the maximum amount of bugs can be caught. The random seeds will hit many different use cases which can not be anticipated earlier and has the probability to catch the design issues. Ideally, random tests can be classified into the following two categories: [1] Corner cases --> This is the bug that is only possible to catch when many different scenarios are processed together or they overlap and the best way to catch this type of scenario is to run more repeated regression with more seeds. [2] Stress testing -->These types of tests are useful to check the performance and the scalability of the DUT under multiple concurrent activities and unpredictable scenarios. #vlsi #asic #electronics #engineering

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Analog vs. Digital Layout in VLSI Design – What Sets Them Apart? When it comes to chip design, layout is where theory meets silicon. While both analog and digital layouts aim to achieve functionality, their design philosophies differ drastically. 1. Nature of Signals Digital Layout: Deals with logic levels (0s and 1s). As long as timing and noise margins are satisfied, small variations don’t matter. Analog Layout: Sensitive to continuous signal variations. Even slight mismatches or parasitics can degrade performance. 2. Design Goals Digital → Maximize speed, density, and power efficiency. Analog → Ensure precision, matching, low noise, stability, and reliability. 3. Symmetry & Matching Digital: Focus on compactness and routing efficiency. Symmetry isn’t critical. Analog: Device matching (current mirrors, differential pairs, capacitors) is vital. Techniques like common-centroid and interdigitated layouts are used. 4. Sensitivity to Parasitics Digital: Parasitics matter mainly for timing (delay). Tools can optimize these automatically. Analog: Parasitics (capacitance, resistance, coupling) directly affect gain, bandwidth, and offset. Careful manual tuning is required. 5. Automation vs. Manual Effort Digital: Highly automated with P&R (Place & Route) tools. Designers focus more on RTL and synthesis. Analog: Still heavily manual, requiring deep circuit understanding + layout expertise. Tools assist, but human judgment is key. 6. Scaling with Technology Digital: Scales well with Moore’s Law. Shrinking nodes → faster & smaller chips. Analog: Scaling is tricky. Precision, voltage headroom, and device matching don’t always improve with smaller nodes. Digital layout is about automation, density, and speed, while analog layout is about art, precision, and intuition. Both are indispensable, but analog layout remains a craft that demands experience and meticulous attention to detail. 📩 Want to Master Analog Design? Apply here → https://lnkd.in/dZi8JDQA 📱 WhatsApp → https://lnkd.in/g9wNMycs 📡 Telegram → https://t.me/AnalogIC_RFIC #Semiconductor #VLSI #AnalogDesign #DigitalDesign #ChipDesign #ICLayout #Cadence #SemiconductorJobs #FutureOfWork #Electronics #MixedSignal

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DMA Engine: A DMA engine is a hardware block responsible for performing direct memory access (DMA) transfers between system memory and devices (or between memory regions), bypassing the CPU. ✅ Key Roles of a DMA Engine: Manages buffer addresses, transfer size, and transfer direction. Can operate in: Memory-to-memory Memory-to-device Device-to-memory 🤔 How DMA Engines Are Represented in Linux Linux provides a generic DMA Engine Framework, which abstracts the DMA controller hardware from clients (like drivers for SPI, UART, MMC, etc.). 👉 DMA Controller Driver This represents the actual hardware-specific driver for the DMA controller on your SoC. Registers a DMA engine using: dma_async_device_register(struct dma_device *device) Populates the dma_device struct with: device_prep_dma_memcpy() device_tx_status() 👉 DMA Client Driver These are device drivers that want to offload memory transfers. Examples: SPI, I2C drivers Network or audio drivers GPU, video encoders/decoders ✅ Uses DMA APIs to allocate and configure DMA transfers: dma_request_channel() or dma_request_chan() dmaengine_prep_slave_single() dma_submit_error() dma_async_issue_pending() device_issue_pending(), etc. 👉 Descriptors and Channels Each DMA engine has channels, representing concurrent DMA pipes. Clients queue DMA descriptors (linked list or ring buffer) to these channels. 👉 User-Space DMA (VFIO, UIO, SPDK) Not directly through DMA engine framework, but, User-space can map device DMA buffers via IOMMU + VFIO. Still relies on hardware DMA engines behind the scenes. 🔍 Debugging DMA Engines in Linux dmesg for controller init logs cat /sys/class/dma/* Use debugfs to inspect descriptors and channels (if supported) ☑️ Flow Summary 1️⃣ Client uses dma_request_chan() to get a DMA channel. 2️⃣ It uses dmaengine_prep_...() to prepare the transfer. 3️⃣ dma_submit_error() queues the descriptor. 4️⃣ dma_async_issue_pending() starts the DMA. 5️⃣ On transfer completion, the controller triggers a callback (e.g., interrupt), which is routed to the client via tx->callback. #dma #memory #smmu #kernel #embedded #learning

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EMIR Checks in VLSI : As process nodes scale to 7nm, 5nm, and beyond, power delivery challenges become critical. EMIR (Electro-Migration & IR drop) analysis isn’t just a signoff formality—it’s the difference between reliable silicon and expensive respins. 🔹 IR Drop Static IR drop: Caused by average current → impacts DC voltage levels, reducing noise margin. Dynamic IR drop: Caused by instantaneous switching activity → leads to timing failures & setup/hold violations. 🔹 Electro-Migration (EM) High current density displaces metal atoms. Leads to void formation (open circuits) or hillocks (shorts). Reliability degradation follows Black’s Equation → failure rate ~ J^n * exp(-Ea/kT), where J is current density. 🔹 Why EMIR Checks Matter ✅ Ensure power integrity across standard cells & macros ✅ Capture voltage droop under realistic switching scenarios ✅ Validate reliability margins of interconnects & vias ✅ Provide lifetime projections for SoCs under actual workloads 🔹 Best Practices Use vector-based dynamic analysis for realistic IR stress conditions. Perform early in-design EMIR closure (not just signoff). Apply localized decap insertion & grid reinforcement where droop hotspots appear. Correlate RTL activity → gate-level simulation → signoff IR analysis for accuracy. With billion-transistor SoCs, EMIR is no longer just a backend task—it’s a design co-pilot. #VLSI #SoC #Semiconductors #ChipDesign #Reliability #EMIR

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𝐕𝐋𝐒𝐈 𝐒𝐞𝐦𝐢𝐜𝐨𝐧𝐝𝐮𝐜𝐭𝐨𝐫 𝐌𝐚𝐫𝐤𝐞𝐭 𝐒𝐞𝐭 𝐭𝐨 𝐑𝐞𝐚𝐜𝐡 $97.49 𝐁𝐧 𝐛𝐲 2032 | 𝐃𝐫𝐢𝐯𝐢𝐧𝐠 𝐭𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐄𝐥𝐞𝐜𝐭𝐫𝐨𝐧𝐢𝐜𝐬 𝐃𝐨𝐰𝐧𝐥𝐨𝐚𝐝 𝐏𝐃𝐅 𝐁𝐫𝐨𝐜𝐡𝐮𝐫𝐞:https://lnkd.in/gS4e6WWA The Global VLSI Semiconductor Market, valued at USD 60.71 Bn in 2024, is projected to grow at a 6.1% CAGR, reaching nearly USD 97.49 Bn by 2032. This growth is powered by advancements in microcontrollers, ASICs, FPGAs, MEMS, and their expanding applications across consumer electronics, telecommunications, automotive, industrial, and healthcare. From enabling IoT devices and AI-powered systems to powering electric vehicles and 5G infrastructure, VLSI technology is becoming the backbone of next-gen innovations. The market is dominated by Asia-Pacific, with China, Japan, South Korea, and Taiwan driving growth due to heavy semiconductor investments and strong electronics demand. North America, led by the United States, also remains a key hub for innovation and semiconductor trade. Industry leaders like Intel, NVIDIA, Samsung, and Applied Materials are competing through cutting-edge technologies such as EUV lithography, 3D integration, and AI-driven chip design, fueling the market’s expansion despite challenges like high production costs and supply chain complexities. 𝐕𝐋𝐒𝐈 𝐒𝐞𝐦𝐢𝐜𝐨𝐧𝐝𝐮𝐜𝐭𝐨𝐫 𝐌𝐚𝐫𝐤𝐞𝐭 𝐊𝐞𝐲 𝐏𝐥𝐚𝐲𝐞𝐫𝐬 Applied Materials  NVIDIA  Intel Corporation  Texas Instruments  Micron Technology  Qualcomm  Broadcom Inc. Advanced Micro Devices (AMD)  Marvell Technology  Synopsys Inc. #VLSI #Semiconductors #ChipDesign #IntegratedCircuits #JICA #XAUUSD #Clinton #taxauditextension #ElectronicsIndustry #ASIC #FPGA #IoT #AI #MachineLearning #5G #EdgeComputing #VR #AR #AutomotiveTech #ConsumerElectronics #TechInnovation #AsiaPacificMarket #SmartDevices #FutureOfTech

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