2030 Data Center AI Chip Winners: The Trillion Dollar Club


At the start of 2025, I believed AI was overhyped, ASICs were a niche, and a market pullback was inevitable. My long-term view has changed dramatically. AI technology and adoption is accelerating at an astonishing pace. One of the GenAI/LLM leaders, or Nvidia, will be the first $10 Trillion market cap company by 2030. Large language models (LLMs) are rapidly improving in both capability and ... » read more

New Data Center Protocols Tackle AI


Compute nodes in AI and HPC data centers increasingly need to reach out beyond the chip or package for additional resources to process growing workloads. They may commandeer other nodes in a rack (scale-up) or employ resources in other racks (scale-out). The problem is there currently is no open scale-up protocol. So far this task has been dominated by proprietary protocols, because much of ... » read more

Application Of External CFD Modeling In Data Center Design


Rising IT densities and AI workloads demand smarter heat management and equipment placement. This paper "Application of External CFD Modeling in Data Center Design" explores how external computational fluid dynamics (CFD) modeling provides crucial insights by resolving airflow patterns around buildings. Why Choose External CFD Modeling? Recommended by The Green Grid, it helps predict: ... » read more

Chiplets: A Technology, Not A Market


Chiplets are big business, and that business is growing. The total chiplet market today is roughly $40 billion annually. Chiplets account for roughly 15% of TSMC's revenues, and they account for about 25% of all DRAMs. All of the major AI/HPC semiconductor companies (NVIDIA, AMD, Marvell, Broadcom) and the major hyper scalers (Amazon, Google, etc) are looking to chiplets to build superior... » read more

Lines Blurring Between Supercomputing And HPC


Supercomputers and high-performance computers are becoming increasingly difficult to differentiate due to the proliferation of AI, which is driving huge performance increases in commercial and scientific applications and raising similar challenges for both. While the goals of supercomputing and high-performance computing (HPC) have always been similar — blazing fast processing — the mark... » read more

Key Challenges In Scaling AI Clusters


AI is evolving at an unprecedented pace, driving an urgent need for more powerful and efficient data centers. In response, nations and companies are ramping up investments into AI infrastructure. According to Forbes, AI spending from the Big Tech sector will exceed $250 billion in 2025, with the bulk going towards infrastructure. By 2029, global investments in AI infrastructure, including dat... » read more

Optimizing Data Center TCO With CXL And Compression


In the ever-evolving landscape of data centers, Total Cost of Ownership (TCO) remains a critical metric. It encompasses all costs associated with data center infrastructure throughout its lifecycle, including initial purchase, installation, utilization, maintenance, energy consumption, and eventual replacement. By understanding and optimizing TCO, hyperscalers can make informed decisions that e... » read more

Data Center Solutions: Reducing the Risk of Change


A panel of thermal and operational experts discuss the evolving challenges in the data center industry and the tools they’re using to overcome them. This eBook details the panel insights, which cover new applications, evolving thermal requirements, innovative cooling technology, and more. Download the eBook for a snapshot of how data center professionals are overcoming the current changes ... » read more

Why HPC Chip Designers Are Looking Into Linear Pluggable Optics


This paper delves into the technical complexities and emerging trends in integrating linear pluggable optics within AI chip design. The rapid growth of hyperscale data centers, driven by the demands of LLMs and transformative AI applications, requires innovative solutions optimized for power, latency, and bandwidth. Emerging industry standards are ensuring interoperability between independently... » read more

Silent Data Errors Still Slipping Through The Cracks


Silent data corruption errors in large server farms have become a major concern of cloud users, hyperscalers, processor manufacturers and the test community. Silent data errors (also called silent data corruption errors) are hardware errors that occur when an incorrect computational result from a processor core goes undetected by the system. The data is silently corrupted because neither sof... » read more

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