Sharing project experiences, insights into cutting-edge architectures, focusing on cloud computing, microservices, big data, hyper-convergence, storage, data protection, artificial intelligence, industry practices and solutions.
Nvidia’s latest GTC briefing details the Blackwell and Rubin GPU roadmaps, highlighting massive GPU shipments, new NVLink 6.0 interconnects, 448 Gbps SerDes, and architectural innovations aimed at boosting AI compute performance, efficiency, and scalability across data‑center workloads.
This article systematically reviews the development background, core technologies, industry challenges, and practical progress of optical computing, highlighting its strategic value as a new post‑Moore computing paradigm for AI workloads in the future.
This article traces the evolution of Nvidia’s GPU architectures—from the early Tesla series through Fermi, Kepler, Maxwell, Pascal, Volta, Turing, Ampere, and the latest Hopper—detailing their specifications, key features, and offering a systematic decision‑making guide for AI server designers to select the optimal GPU based on workload, model size, precision, scalability, and total cost of ownership.
This comprehensive analysis examines the strategic importance, technical challenges, innovation pathways, and market landscape of domestic AI chips in China, highlighting key players, regional clusters, core applications such as intelligent computing, autonomous driving, and robotics, and projecting future industry bottlenecks and opportunities.
The article explains Alibaba’s ALink System, detailing its data‑plane ALS‑D and control‑plane ALS‑M, the backplane‑free orthogonal hardware design, copper and optical interconnect layers, and the UPN512 architecture’s optical options, transmission semantics, and in‑network computing techniques that together reshape AI scale‑up networking.
The article examines the emerging AI Super Node ecosystem, detailing its core concepts, four‑layer architecture, key enabling technologies, current challenges such as compatibility and energy consumption, and future directions like quantum‑classic hybrids and green low‑carbon designs, illustrating how it overcomes scaling bottlenecks in modern AI deployments.
This article explains how modern data centers rely on the coordinated operation of compute, networking, and storage components—detailing server architectures, AI accelerator trends, high‑speed network designs, and evolving storage technologies—to achieve high performance, scalability, and energy efficiency.
As AI models grow to massive scales, the demand for ultra‑high‑performance, low‑latency networking in xPU clusters intensifies, prompting a shift from dense to MoE architectures and driving the evolution of Scale‑up networks, where Alibaba Cloud’s UPN design tackles bandwidth, cost, and reliability challenges.
This article explains the fundamentals of high‑performance computing (HPC), covering serial and parallel processing, the roles of CPUs and GPUs, system architectures, FLOPS metrics, current supercomputer capabilities, and the scale needed to reach the next exa‑FLOPS era.
This article compares four cutting‑edge high‑performance processors—Fujitsu A64FX, NVIDIA H100, AMD MI250X, and Intel PonteVecchio—examining their architectures, parallelism strategies, domain‑specific accelerators, supported data types, performance metrics, and power consumption to inform future E‑level computing designs.
