Deep analysis of AI chip architecture, HBM, interconnect, packaging
View all tagsIn 2026, AI compute growth has hit a hard constraint — electric power. With NVIDIA Rubin NVL576 single-rack power consumption at 1 MW, the xAI Colossus cluster at 200 MW, and OpenAI's planned Stargate campus at 5 GW, power supply is becoming the biggest bottleneck for AI development. This article provides an in-depth analysis of this "power crisis" and the solutions.
The bottleneck for AI compute has shifted from compute itself to memory bandwidth and capacity. HBM (High Bandwidth Memory) , as a core component of AI chips, has a 2026 market size of $80B+, but there are only 3 suppliers globally — SK Hynix, Samsung, Micron. This article provides an in-depth analysis of this "memory three kingdoms" battle.
2026 AI compute enters the "rack-scale" era. Single-chip comparisons have receded, and full-rack solutions have become the main battleground. This article provides an in-depth comparison of the five major rack-scale solutions: NVIDIA Rubin NVL72/NVL576, AMD Helios, Groq 3 LPX, AWS Trn3 UltraServer, and Google TPU 8t pod.
LLM inference performance = Algorithm + Software + Hardware. Hardware (H100, B300, Rubin) only determines the theoretical ceiling. Actual inference performance can be improved 5-30× through algorithmic optimization. This article provides a deep analysis of the three major inference optimization technologies: PagedAttention, FlashAttention, and Speculative Decoding.
Apple Silicon is staging a comeback in the AI era. The M3 Ultra in a single Mac Studio packs 192GB unified memory (UMA) and an 80-core GPU, capable of running 70B-200B parameter LLMs locally without quantization. This is a revolution in consumer/workstation-class AI inference. This article provides an in-depth analysis of Apple Silicon's AI advantages, current ecosystem, and future.
In 2026, AMD launched MI400 (CDNA Next) + Helios 72-GPU rack, AMD's flagship solution targeting NVIDIA NVL72. This article analyzes MI400's key specifications, the Helios rack's open interconnect (UALoF) strategy, and a comparison with Rubin R200.
The NVIDIA Vera Rubin platform is NVIDIA's next-generation flagship computing platform after Blackwell. This article provides an in-depth analysis covering the naming origin, 6-chip packaging, memory subsystem, compute matrix, networking architecture, rack-scale solution, and software ecosystem.