Tag: #nvidia
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 36 posts
2026 Semiconductor Industry Trends — 1nm Process, HBM4, AI Chip Wars, US-China Tensions
Samsung 1nm process announcement, NVIDIA B200, Intel-Google partnership, HBM4 competition, and US-China semiconductor tensions — everything about the 2026 semiconductor industry.
2026-04-11 · 15 min read #ai#semiconductor#samsung#tsmc#nvidiaAI's Power Crisis: Why Data Centers Need Nuclear Plants (The Numbers Don't Lie)
Global data centers 415TWh to 980TWh by 2030, a 2x increase. Microsoft $16B nuclear restart, Amazon $20B nuclear campus, Google SMR deal. AI water usage equals global bottled water consumption. B200 at 1,000W per chip: e
2026-03-22 · 22 min read #ai#energy#power#nuclear#datacenterAI Hardware War 2025: NVIDIA Blackwell vs AMD MI350 vs Cerebras WSE-3 vs Google TPU v7
NVIDIA B200 with 208B transistors, Samsung HBM4 first to mass produce, Cerebras 4T transistor wafer, AMD MI350 with 288GB — a complete comparison of every player in the AI chip war by specs, benchmarks, and roadmaps.
2026-03-22 · 26 min read #nvidia#samsung#cerebras#amd#intel10 Voices Shaping the AI Era: From Jensen Huang to Yann LeCun, the Defining Quotes of 2025
Jensen Huang's "1 trillion dollar AI infrastructure," Sam Altman's "GPT-5 is smarter than me," Dario Amodei's "trillions in revenue before 2030," Yann LeCun's "LLMs are complete nonsense" — the defining quotes of 10 lead
2026-03-22 · 24 min read #ai#nvidia#openai#anthropic#googleMarch 2025 Tech·AI·K-POP Weekly Digest: From GTC to BTS Comeback
A comprehensive roundup of March 2025 highlights: NVIDIA GTC Blackwell Ultra announcement, Gemini 2.5 Pro topping benchmarks, MCP becoming the industry standard, DeepSeek-R1 open-source shock, BTS full-group comeback aft
2026-03-21 · 12 min read #culture#ai#kpop#nvidia#gtcAI Supercomputer at Home: Study LLMs on NVIDIA DGX Spark and Create Content with ComfyUI
Run 200B-parameter LLMs locally on NVIDIA DGX Spark ($3,999) and generate FLUX/SDXL images with ComfyUI. Complete guide with specs, benchmarks, setup instructions, and cost analysis — the era of personal AI supercomputer
2026-03-21 · 37 min read #nvidia#dgx-spark#comfyui#local-ai#llmNVIDIA GPU and CUDA Architecture Deep Dive: Why GPUs Dominate AI
From H100 hardware specs to Tensor Core WMMA API. A complete breakdown of the SIMT execution model, shared memory tiling, warp divergence, and why GPUs are purpose-built for AI workloads.
2026-03-18 · 14 min read #cuda#gpu#nvidia#matrix-multiplication#parallel-computingGPU Hardware Complete Guide for AI: From Architecture to Selection Criteria
A comprehensive guide to GPU hardware for AI research and training. Covers NVIDIA GPU architectures (Hopper, Blackwell), Tensor Core, NVLink, HBM memory, A100/H100/H200/B200 comparisons, and cloud GPU options in detail.
2026-03-17 · 23 min read #gpu#hardware#nvidia#cuda#gpu-cudaCUDA Programming Complete Guide: GPU Parallel Computing Zero to Hero
A comprehensive guide to mastering CUDA programming from fundamentals to advanced optimization. Covers GPU architecture, kernel writing, memory optimization, mixed precision training, and cuDNN/cuBLAS usage with practica
2026-03-17 · 30 min read #cuda#gpu#gpu-cuda#parallel-computing#nvidiaNVIDIA Triton Inference Server Production Guide: GPU Model Serving Optimization Strategies
A guide to GPU model serving optimization with NVIDIA Triton Inference Server. Covers Dynamic Batching, Model Ensemble, TensorRT integration, multi-model serving, Kubernetes deployment, performance profiling, and product
2026-03-08 · 29 min read #ai-platform#triton#inference-server#gpu#model-servingNeMo Guardrails Complete Guide: Building Programmable Safety Controls for LLM Applications
A hands-on guide to building programmable safety controls for LLM-based applications using NVIDIA NeMo Guardrails, covering input/output moderation, topic control, and hallucination detection.
2026-03-03 · 23 min read #ai-papers#nemo-guardrails#llm-safety#nvidia#guardrailsNVIDIA GPU Operator Complete Guide: Components, Installation, and KubeVirt GPU Passthrough
A detailed analysis of NVIDIA GPU Operator architecture and the roles of its 7 core components (Driver, Container Toolkit, Device Plugin, DCGM, MIG Manager, Node Feature Discovery, GFD), covering Helm-based installation,
2026-03-01 · 18 min read #gpu-operator#nvidia#kubernetes#kubevirt#gpuCUDA Hands-on Complete Guide: Everything About GPU Computing
A comprehensive guide covering NVIDIA CUDA from fundamental concepts to GPU architecture, C/C++ kernel programming, memory optimization, Python integration (PyTorch, Numba, CuPy), Multi-GPU training, profiling, and troub
2026-03-01 · 51 min read #cuda#gpu#nvidia#deep-learning#machine-learningThe Peak of the AI Memory Supercycle: 5 Decisive Moments for HBM That Will Shake the 2026 Semiconductor Market
From HBM4 16-layer stacking technology, the emergence of custom HBM (cHBM), the strategic clash between SK Hynix, Samsung, and Micron, to the memory supercycle market outlook and HBM vs GDDR comparison — an in-depth anal
2026-03-01 · 37 min read #hbm#semiconductor#memory#ai-hardware#sk-hynixKubernetes GPU Workload Management: The Complete NVIDIA GPU Operator Guide
A comprehensive analysis of how to efficiently manage GPU resources and operate AI workloads in Kubernetes clusters, based on the official NVIDIA GPU Operator documentation.
2026-03-01 · 21 min read #kubernetes#gpu#nvidia#gpu-operator#aiCUDA Programming Fundamentals: Complete Guide to GPU Parallel Computing
Systematically analyze the core concepts of CUDA programming including thread hierarchy, memory model, and kernel development based on NVIDIA official documentation.
2026-03-01 · 24 min read #gpu#cuda#parallel-computing#nvidia