The article analyzes current server market dynamics, covering rising CPU core counts, accelerating network speeds, expanding SSD capacities, evolving DDR5 memory architectures, and the competitive landscape of AI‑focused GPUs as the industry prepares for 2025.
The rapid growth of large‑language models—from GPT‑1 to the upcoming GPT‑5—has dramatically increased compute demand, prompting cloud providers and hardware vendors to accelerate GPU performance, interconnect bandwidth, and chip localization, reshaping the AI‑driven capital‑expenditure landscape for 2024.
The article examines challenges of traditional server‑based distributed storage in cloud and internet workloads and proposes a new disaggregated compute‑storage architecture leveraging emerging hardware such as EBOF, DPU, CXL, and NVMe to improve resource utilization, performance, reliability, and efficiency.
The article analyzes the limitations of current server‑based distributed storage—such as data‑lifecycle mismatches, performance‑resource trade‑offs, serverless workload demands, and the costly "datacenter tax"—and presents emerging hardware trends and a novel compute‑storage separation architecture that promises higher efficiency, reliability, and scalability for cloud and internet data centers.
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 analyzes the storage challenges faced by cloud and internet services, outlines hardware trends such as Ethernet‑based flash, DPU and CXL, and proposes a new disaggregated compute‑storage architecture that improves resource utilization, reliability, performance and efficiency for data‑intensive workloads.
The article analyzes the mismatched data‑preservation cycles, performance‑reliability trade‑offs, server‑centred data‑center tax, and the need for new storage‑compute disaggregation, then outlines hardware trends such as Ethernet‑based flash, CXL, DPUs, and proposes a novel storage‑compute separation architecture to improve resource utilization, reliability, and efficiency for cloud and internet workloads.
The report provides a comprehensive overview of enterprise‑grade SSD technology, covering NAND flash market share and advancements, DRAM role and growth, SSD production trends, emerging 3D/4D NAND technologies, and the competitive landscape of major storage manufacturers worldwide.
