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Multi-Threaded Compiled Performance for JavaScript and Python


Canadian multi-threading specialist Fabric Engine has officially launched v1.0 of its eponymously named high-performance computing (HPC) platform this week under the AGPL license. This new release aims to combine the power of multi-core hardware to bring multi-threaded and compiled performance to dynamic languages such as JavaScript and Python.

Fabric Engine has highlighted the speed of usability advantages of dynamic languages, but says that they are ultimately slow compared to compiled languages unless rebuilt to provide performance — which in turn introduces additional costs.

The company's USP rests upon its claim that Fabric Engine will give the "same performance" as multi-threaded C++, yet retain the ease of use and speed of iteration of dynamic languages.

The firm's customers have gone on the record saying that Fabric Engine also benefits from using a language very similar to JavaScript for high-performance operators (vanilla JavaScript/node.js for everything else) -- and that this reduces the need to use C++. The upshot being that developers can then potentially avoid the whole code-compile-run cycle and use a more immediate execute model.

According to the company's official news stream, "On the server and in the cloud, Fabric Engine is ideal for addressing compute-bound problems that require raw execution performance. With node.js, Fabric Engine provides an asynchronous compute model that works well alongside the other services that node provides."

NOTE: High-performance applications (HPC) encompass such apps as those used in game development, animation, film production, GIS, medicine, and other industries that are greedy for performance.

Fabric Engine currently runs as a browser plug-in and is currently in beta for a Python/QT desktop framework.


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