Whether modifying an existing application or writing entirely new code, parallel applications can be much more challenging to work with than their sequential counterparts. Without a doubt, the ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

AI success depends on whether enterprise data is ready, reachable, and close enough to the workloads that need it. In this eSpeaks episode, Dell Technologies’ Vrashank Jain explains why fragmented ...

Programming languages are evolving to bring the software closer to hardware. As hardware architectures become more parallel (with the advent of multicore processors and FPGAs, for example), sequential ...

LONDON – Universal Parallel Computing Research Center (UPCRC) at the University of Illinois has issued a first release of Deterministic Parallel Java (DPJ), a computer programming language that it is ...

Multicore chip designs, large symmetrical multiprocessing (SMP) systems, and clustering can bring many processors to bear on an application. But without proper software, they're simply large ...

OpenCL, created to support parallel programming in Apple's Snow Leopard operating system, may become the new world standard for parallel programming on all platforms. Peter N. Glaskowsky is a computer ...

A new evaluation of popular parallel programming languages finds that the C++ library provides the best combination of usability and performance Multicore programming is a tricky problem. Developers ...

Python’s lead narrows again, C holds the runner-up spot, C++ returns to third, and SQL climbs back above R in June’s top 10 ...