This is the Linux app named Bend whose latest release can be downloaded as Bend2.0.27sourcecode.zip. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Bend with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start the OnWorks Linux online or Windows online emulator or MACOS online emulator from this website.
- 5. From the OnWorks Linux OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application, install it and run it.
SCREENSHOTS
Ad
Bend
DESCRIPTION
Bend is an interactive programming environment (REPL) built on top of the Kotlin language, designed to allow users to explore, experiment, and learn Kotlin in a live, feedback-driven manner. The tool lets you define variables, functions, or values at the prompt and iteratively refine them—immediately seeing output and types—while preserving state across commands. It emphasizes discoverability and experimentation: users can inspect functions, call them on sample inputs, and evolve logic without a full project scaffold. Because it’s embedded in a graphical or console interface, Bend aims to reduce the friction of switching between editor and runtime when prototyping or debugging ideas in Kotlin. It can also be extended with libraries or domain-specific tools, making it a flexible playground for domain scripting, education, or data exploration.
Features
- A high-level language that feels like Python to write parallel computation for CPU/GPU without deep expertise in concurrency or CUDA etc
- Automatically parallel execution of work that can be parallelized, with runtime handling threading, task scheduling etc
- HVM runtime: capable of scaling to many threads (hundreds / thousands depending on cores) to achieve near-ideal speedups on multi-core hardware
- Support for both CPU and GPU execution to leverage both types of hardware as available
- Simplified concurrency model: developer doesn’t need to manage low level concurrency primitives (locks etc) manually
- Designed for performance: speedup nearly proportional to available cores / hardware, focusing on efficiency of parallel computations
Programming Language
Rust
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/bend.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
