Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Dany Lepage discusses the architectural ...

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 ...

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 ...

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

Cloud data was supposed to enable AI at scale and democratize data. But how do we cope with the new complexities of distributed data? The emerging discipline of DataOps may help us here - along with ...

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 ...