In 2026 the GPU market has shifted from Nvidia's lone dominance to a competitive arena where Nvidia, AMD, and Intel vie with emerging Chinese players and cloud‑vendor chips, emphasizing architecture, energy efficiency, chiplet packaging, and software ecosystems over sheer core count.
The article analyses how China’s AI chip industry confronts the 7nm process bottleneck by leveraging mature nodes, innovative architectures, chiplet packaging, high‑bandwidth memory and a growing software ecosystem, while projecting rapid market growth and outlining remaining technical gaps.
This article explains how Chiplet technology boosts integration and performance in modern SoCs, compares MCM, CoWoS, and EMIB packaging methods, discusses architectural design strategies and the UCIe standard, and highlights real‑world examples from Intel, AMD, Huawei, and Apple.
This report provides a comprehensive technical analysis of Zhaoxin’s x86 processor lineup—from early ZX‑C chips to the latest KX‑7000 desktop/embedded series and KH‑40000 server CPUs—detailing architecture, process technology, performance specs, security features, and real‑world deployments across government, education, and enterprise sectors.
This article provides a detailed technical overview of Huawei's Ascend AI processors, covering the Da Vinci architecture, core components such as AI Core and DVPP, the chiplet‑based designs of the Ascend 910 and 310 models, and the specific optimizations for high‑performance convolution and cloud‑edge workloads.
The article analyzes why GPUs continue to dominate AI model training, comparing them with ASICs, CPUs, and other chips, and discusses ecosystem advantages, domestic development gaps, emerging edge‑AI demands, high‑bandwidth needs, and chiplet technology as future enablers.
The article analyzes Nvidia's AI chip evolution, assumes consistent storage‑compute‑interconnect ratios and predictable process scaling, and projects the architectures of H200, B100 and X100, highlighting the limits of chiplet packaging and the critical role of low‑latency, high‑reliability interconnect technologies for future AI compute scaling.
The article analyzes current AI hardware options, explains why GPUs continue to dominate model training due to architectural compatibility, ecosystem support, and market maturity, and outlines emerging trends such as model miniaturization, optical interconnects, and chiplet technology that will shape the next generation of AI compute.
The article explains the concept of integrated chips and chiplets, describes their architecture, the role of silicon interposers, outlines three main performance‑boosting pathways—scaling, new device materials, and chiplet integration— and highlights recent industry examples and standards that illustrate the emerging paradigm.
The article outlines the accelerating demand for high‑performance computing driven by AI, AR/VR, biotech and other workloads, examines the limits of Moore's law, and presents emerging solutions such as advanced chip architectures, chiplet integration, near‑memory/in‑memory computing, and distributed xPU‑based systems for scalable, efficient compute.
The 2023 semiconductor industry report forecasts ten key trends, including the dominance of mature process expansion, intensified policy environments, the rise of chiplet technology, FD‑SOI advancements, RISC‑V CPU IP breakthroughs, anti‑globalization shifts, front‑end integration by device makers, smart cockpit evolution, inventory cycle dynamics, and the push toward a fully domestic semiconductor ecosystem.
From multimodal pre‑training models and chiplet integration to compute‑in‑memory, cloud‑native security, predictive networking, dual‑engine decision systems, computational optical imaging, large‑scale digital twins, and generative AI, this overview highlights the key technological trends reshaping AI, hardware, and cloud infrastructures.
DAMO Academy's 2023 top ten technology trends report highlights generative AI, Chiplet modular design, and a new cloud‑centric computing architecture, while also forecasting advances in multimodal large models, cloud‑native security, compute‑in‑memory chips, optical imaging, digital twin cities, and dual‑engine intelligent decision‑making.
The HiPChips workshop at ISCA 2022 gathered leading academia and industry experts to discuss the motivations, recent research breakthroughs, technical challenges, and ecosystem efforts surrounding high‑performance chiplet and interconnect architectures for future computing systems.
The article analyzes how the slowdown of Moore's Law drives a shift from general‑purpose CPUs to specialized XPU, FPGA, DSA and ASIC designs, highlights heterogeneous chiplet integration, edge‑server growth, and the emerging importance of software, algorithms and architecture in boosting performance and efficiency.
The article explains how chiplet technology, as a modular semiconductor IP solution, reduces design cost and time, expands market opportunities, and faces challenges such as standardization, packaging testing, and software integration, while outlining its market outlook and impact on business models.
The article provides a comprehensive technical analysis of AMD’s Zen 3 (Ryzen 5000) microarchitecture, covering its chiplet layout, cache hierarchy, front‑end redesign, integer and floating‑point units, load/store improvements, security features, and overall performance gains compared with Zen 2.
