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 ...

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

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 ...

Oracle Corp. announced today that its Globally Distributed Autonomous Database is generally available. Aimed at customers that have strict data sovereignty requirements, usually because of regulations ...

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.

Parallel Data Lab researchers Henggang Cui, engineering manager at Latitude AI and a Carnegie Mellon University electrical and computer engineering alumnus; Hao Zhang, a postdoctoral researcher at ...

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

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 ...