This article explores the powerful parallelization and distributed computing capabilities of the HPX framework. Starting with installation on macOS, it walks through configuring, compiling, and testing HPX on a modest machine, highlighting key features like asynchronous programming, task-based parallelism, and HPX components. Whether new to HPX or looking for practical examples, this guide offers a hands-on approach to understanding and utilizing HPX in real-world scenarios.
C++
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Writing HDAs with htmx and C++-
Yesterday, I discovered an experimental Big Data processing framework written in C++ called Thrill. As most of you surely know, the well-known frameworks of this kind are mostly based on JVM, like Apache Spark or Apache Flink. This, of course, has many advantages, like easily accessible interfaces and a more domain-oriented approach, as we don’t have to deal with “Ceremony Code” or any internals that don’t touch our domain logic. However, everything comes at a cost and utilizing a VM is a price to be paid no matter how optimized your code is. It’s no wonder these projects often resort to […]
A few months ago I discovered a Project from Louisiana State University led by Prof. Kaiser that designs and develops a new execution model for future high performance architectures. It’s called ParalleX and its C++ implementation is named HPX (High Performance ParalleX). It supports operating systems like Linux or Windows and several Build-Toolchains (GNU, MSBuild, CMake etc.). In this article we’ll use Windows 10 x64 and Visual Studio 2015 to build up the base structure of HPX itself plus a small collection of demos showing some of the key aspects of it. The sources can be found here. Building HPX Before we can […]