The evolution of data architecture is accelerating. In 2025, 85% of DBTA subscribers reported plans to modernize their data platforms-driven largely by the explosive rise of GenAI and large language ...

“Emerging applications such as deep neural network demand high off-chip memory bandwidth. However, under stringent physical constraints of chip packages and system boards, it becomes very expensive to ...

Today at SC19, Intel unveiled its new X e GPU architecture optimized for HPC and AI as well as an ambitious new software initiative called oneAPI that represents a paradigm shift from today’s ...

Intel launches oneAPI, a unified and scalable programming model to harness the power of diverse computing architectures in the era of HPC/AI convergence. Intel introduces a general-purpose GPU ...

VAST Data Introduces End-To-End Fully Accelerated AI Data Stack With NVIDIA. VAST AI OS will leverage NVIDIA libraries to accelerate both compute and data services for RAG, vector search, real-time ...

In an era where data is a strategic asset, organizations often falter not because they lack data—but because their architecture doesn’t scale with their needs. Leaders must design data ecosystems that ...

For exascale hardware to be useful, systems software is going to have to be stacked up and optimized to bend that hardware to the will of applications. This, in many ways, is the hardest part of ...

A headless data architecture means no longer having to coordinate multiple copies of data and being free to use whatever processing or query engine is most suitable for the job. Here’s how it works.

The headless data architecture is the formalization of a data access layer at the center of your organization. Encompassing both streams and tables, it provides consistent data access for both ...