In an era where unplanned IT downtime now averages $14,056 per minute, and over 90% of mid-size and large enterprises ...

The tide is changing for analytics architectures. Traditional approaches, from the data warehouse to the data lake, implicitly assume that all relevant data can be stored in a single, centralized ...

Introduction to parallel computing for scientists and engineers. Shared memory parallel architectures and programming, distributed memory, message-passing data-parallel architectures, and programming.

The sheer volume of ‘Big Data’ produced today by various sectors is beginning to overwhelm even the extremely efficient computational techniques developed to sift through all that information. But a ...

Hadoop, an open source framework that enables distributed computing, has changed the way we deal with big data. Parallel processing with this set of tools can improve performance several times over.

In a recent article, “The Rise Of Distributed Data Centers In The AI Era,” I explored why enterprises are moving beyond a single, centralized data center to a fabric of compact, powerful data centers ...

AI is inspiring organizations to rethink a fundamental IT concept: the data center. For decades, the data center was a centralized place. It was a handful of large, secure facilities where ...

Enterprise AI workloads require infrastructure designed for large-scale data processing and distributed computing. Organizations are modernizing AI data center infrastructure with GPU computing, ...