Learn how parallel processing can speed up, scale up, and enhance your program's performance, and how to use different tools and techniques for parallel processing in different operating systems.

a comparison of sequential vs parallel group-by data processing. Writing “loops” is a common coding/programming practice. A loop is a process for iterating and repeating a block of code. Such a ...

This project aims to provide a hands-on experience with parallel and distributed computing. We dive into the intricacies of parallel processing using the mpi4py library, a Python binding for the ...

An interesting example is the sensor-fusion application. It has different types of sensors, like temperature, humidity, pressure, vibration, frequency and ultrasound. All these sensors, each with ...

The key challenge is exposing the parallelism that is inherent in these applications but that is obscured by artifacts imposed by sequential programming languages. This paper presents a ...

This paper descibes an infrastructure that enables transparent development of image processing software for parallel computers. The infrastructure's main component is an image processing library ...