August 27, 2019 — Appentra released the latest version of the Parallelware Trainer, which now supports the detection of defects and recommendations for concurrency and parallelism. Details of the release are the Appentra blog below.
We’re happy to announce the release of Parallelware Trainer 1.3 which now supports the detection of defects and recommendations for concurrency and parallelism. We expect this new feature to further improve the learning process by providing feedback about code issues right in the integrated editor.
Parallelware Trainer provides an enhanced interactive learning environment, including provision for a knowledge base designed around the code being developed and several parallelization paradigms: multithreading, tasking and offloading to GPUs. Parallelware Trainer is an essential tool to fulfill Appentra’s mission: to make parallel programming easier, enabling everyone to make the best use of parallel computing hardware, from the multiple cores in a laptop to the fastest supercomputers.
New in Parallelware Trainer 1.3 version
- Defects and recommendations for concurrency and parallelism. Now Parallelware Trainer analyzes your code looking not only for opportunities for parallelization but also for defects and recommendations related to concurrency and parallelism. When such an issue is found, a warning icon is displayed in the code editor providing information about the problem and how to fix it.
- Export file versions. Experimentation by creating different versions of the same source file implementing different parallelization strategies plays a central role in learning through Parallelware Trainer. Now you can take your work with you by exporting those versions!
- Latest Parallelware technology. Each new release includes the latest version of the Parallelware core technology which is in constant evolution to support more code bases and parallelization features.
Try Parallelware Trainer for free here.
Appentra is a Deep Tech global company that delivers products based on the Parallelware technology, a unique approach to static code analysis specialized in concurrency and parallelism. Our aim is to make parallel programming easier, enabling everyone to make the best use of parallel computing hardware from the multi-cores in a laptop to the fastest supercomputers.