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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Redmond, Wash. — Multicore processors are driving a historic shift to a new parallel architecture for mainstream computers. But a parallel programming model to serve those machines will not emerge for ...

HAVE computers stopped getting faster? If you looked only at the clock speeds of microprocessor chips, you might well think so. A modern PC typically has a processor running at 3.0GHz (3 billion clock ...

Many hands make light work, or so they say. So do many cores, many threads and many data points when addressed by a single computing instruction. Parallel programming – writing code that breaks down ...

For example, an engineer may develop a real-time embedded control system at the same time as its human-machine interface. Maybe the system also has a computation-intensive task such as high-speed ...