insight

In an era where the scale of AI models is rapidly expanding and data generation is unprecedented, enterprise IT infrastructure faces a significant challenge. Traditional centralized architectures, which focus on single-node computing power, are struggling to cope with the massive and diverse data flowing from the cloud, the edge, and endpoints. Consequently, the role of data is being redefined. It is no longer just a computational aid, but the core asset driving decision-making, innovation, and operational efficiency. Enterprises that fail to upgrade their infrastructure accordingly will face challenges such as data processing bottlenecks, performance degradation, and increased energy consumption, driving up their Total Cost of Ownership (TCO). Facing this strategic turning point, the shift from a "Compute-Centric" to a "Data-Centric" approach is not merely a technical upgrade; it is a critical strategy for enterprise transformation in this new “AI” generation. The 2025 HPC conference, SC25, features the theme "HPC Ignites" and highlights "Data-Intensive Science," clearly reflecting this data-driven change: HPC is no longer confined to science and research, but is accelerating its penetration into the enterprise core and becoming the decisive force in the AI competition.

Generative AI is accelerating the evolution of traditional data centers into next-generation AI Factories - massive, high-performance infrastructures purpose-built for intelligent workloads. In our first article, 《Ready or Not? The Era of AI Factory Has Arrived! AI Factory Era》, we introduced how GIGABYTE is redefining AI infrastructure with a holistic approach to reengineering AI infrastructure, enhancing compute performance, cooling efficiency, and system management. The second article, 《Revolutionizing the AI Factory: The Rise of CXL Memory Pooling》, highlighted that beyond powerful compute and memory, AI factories also demand reliable and ultra-fast data transmission. In this third installment, we focus on the backbone of AI infrastructure: high-speed networking. From single server interconnects to full-scale data center topologies, we’ll explore how cutting-edge transmission technologies enable massive GPU clusters, unlock seamless scalability, and power the AI workloads of tomorrow.

Imagine an AI factory as a bustling, high-end kitchen. Each chef, aka your computing components, is working together to create intricate, multi-course meals (AI workloads). As AI models grow more complex, take Meta’s Llama 3.1 with a staggering 405 billion parameters for example, this kitchen needs to handle an enormous amount of ingredients (data) with efficiency and speed. This is where CXL (Compute Express Link) memory pooling steps in, acting like a shared walk-in refrigerator where every chef can access the freshest ingredients on demand, even chefs from the kitchen next door (other servers). In this article, we explore how CXL memory pooling revolutionizes AI infrastructure by optimizing resources, accelerating data movement, and supporting sustainable growth. GIGABYTE is leveraging this next-gen technology to build smarter, more efficient AI servers.

Deep dive into CXL technology and its advantages for modern AI/HPC applications

AI Infrastructure is more than just stacking cloud servers. It’s a comprehensive system integrating high-performance computing, storage, cooling, and intelligent management, purpose-built for generative AI, large language models, multimodal learning, and even Agentic AI. According to IDC, global spending on AI Infrastructure is projected to reach USD 223 billion by 2028*, making it one of the most significant capital expenditures for enterprises. This article explores the strategic role of AI Infrastructure and how GIGABYTE leverages an integrated-systems approach to build a reliable compute core for AI Factories, laying a high-speed foundation from data center to edge for the AI-powered future.

How ClusterVision, AMD, and Giga Computing enable hydrogen and electric race car development for HyDriven and Formula Student Team Delft

One unmistakable trend this year is that even as the race for next-gen AI hardware continues to heat up, tech giants are also shifting their focus to AI software that can drive hardware to perform at peak capacity and complement the artificial intelligence ecosystem. Particularly, there’s a lot of excitement about DCIM (data center infrastructure management) and AIOps (AI for IT operations), and how they can offer enterprises a decisive competitive edge. In this article, we introduce the concepts of DCIM and AIOps, and what GIGABYTE can do for you.

Discover how Solidigm and GIGABYTE are redefining AI training performance through cutting-edge storage and system integration. Upgrade your AI infrastructure today and unlock new levels of efficiency and scalability.

In "GIGABYTE Deep Dive", we invite our in-house experts to draw back the curtains on the industry-leading innovations that deliver best-in-class computing solutions to our enterprise clients. Today, we are excited to interview our server cooling team and talk about the three "customer-centric insights" that propelled the creation of GIGABYTE Technology's all-in-one DLC solution.

A student team from National Tsing Hua University (NTHU), led by Professor Jerry Chou, secured second place in the ISC 2024 Student Cluster Competition. Leveraging GIGABYTE servers and high-performance computing (HPC) solutions,