Has your system's database become enormous? Are you having to add more users to the system than you anticipated? Is your application beginning to perform like a subcompact towing a trailer uphill?

GPU-based sorting algorithms have emerged as a crucial area of research due to their ability to harness the immense parallel processing power inherent in modern graphics processing units. By ...

[Housekeeping]: There are two sets of posts going out in this series – the series here and the series in our guest blog. Today’s guest post is from David Stewart at CriticalBlue about multicore ...

Digital signal processing has been melded to medical-imaging tasks almost from the outset. The biggest medical applications for DSP have been in meeting the image-processing requirements for computed ...

As manufacturing processes transition to more advanced technologies at 90nm and below, design signoff requirements become increasingly more rigorous and time-consuming. With each step to more advanced ...

And how will they play a greater role in the future? Is it safe to say that once the limitations of a given processor are reached, Multiprocessing will extend it functionality further? How about ...

Python's "multiprocessing" module feels like threads, but actually launches processes. Many people, when they start to work with Python, are excited to hear that the language supports threading. And, ...

High Performance Computing (HPC) and parallel programming techniques underpin many of today’s most demanding computational tasks, from complex scientific simulations to data-intensive analytics. This ...

In this video from EuroPython 2019, Pierre Glaser from INRIA presents: Parallel computing in Python: Current state and recent advances. Modern hardware is multi-core. It is crucial for Python to ...

I'm running some simulations using the joblib library. For that, I have some number of parameter combinations, each of which I run 100,000 times. I'd now like to write the result of each simulation to ...