Tag: #gpu
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 69 posts
Mastering Slurm: A Practical Guide to the HPC/AI Cluster Workload Manager
A comprehensive, hands-on guide to the Slurm workload manager. Covers architecture (slurmctld/slurmd/slurmdbd), core concepts (Partitions/QoS/Fairshare), essential commands (sbatch/srun/salloc), GPU scheduling (GRES/MIG/
2026-03-01 · 15 min read #slurm#hpc#gpu#distributed-training#clusterCUDA Hands-on Complete Guide: Everything About GPU Computing ♪ Listenable
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 ♪ Listenable
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-hynixThe New Throne Beyond vLLM: 5 Reasons SGLang Is Changing the LLM Inference Landscape ♪ Listenable
From SGLang's RadixAttention-based KV cache management and 29% throughput advantage through hyper-specialized design, to its 4,000-line Python zero-overhead scheduler, Prefill-Decode Disaggregation, and Compressed FSM-ba
2026-03-01 · 35 min read #sglang#llm-inference#vllm#radix-attention#model-servingKubernetes GPU Workload Management: The Complete NVIDIA GPU Operator Guide ♪ Listenable
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#aiFlashAttention: Optimizing Attention Through GPU Memory Hierarchy
A review of the FlashAttention paper with an in-depth analysis of IO-aware attention optimization leveraging the GPU HBM/SRAM memory hierarchy.
2026-03-01 · 18 min read #ai-papers#flash-attention#gpu#optimization#transformerCUDA Programming Fundamentals: Complete Guide to GPU Parallel Computing ♪ Listenable
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#nvidiaThe Complete Guide to vLLM & Ollama: LLM Serving Engine Setup, Parameters, and Environment Variables ♪ Listenable
A comprehensive deep dive comparing vLLM PagedAttention architecture and Ollama local LLM runtime environments. Covers everything from installation, server startup, API calls, key CLI arguments, sampling parameters, envi
2026-03-01 · 46 min read #vllm#ollama#model-serving#inference#gpuComplete Guide to GPU Memory Optimization and Mixed Precision Training ♪ Listenable
Analyze GPU memory components based on NVIDIA official documentation and cover memory optimization techniques including Mixed Precision Training and Gradient Checkpointing.
2026-03-01 · 22 min read #gpu#cuda#mixed-precision#optimization#deep-learning