Search Results for "parallel language"
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Showing 12 open source projects for "parallel language"
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
Julia is a fast, open source high-performance dynamic language for technical computing. It can be used for data visualization and plotting, deep learning, machine learning, scientific computing, parallel computing and so much more. Having a high level syntax, Julia is easy to use for programmers of every level and background. Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. ... -
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Bend
A massively parallel, high-level programming language
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... -
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Starlark in Go
Starlark in Go: the Starlark configuration language, implemented in Go
starlark-go is the official Go implementation of the Starlark programming language, a Python-like, dynamically typed configuration and scripting language originally developed for the Bazel build system. Starlark combines Python’s expressiveness and readability with deterministic execution, making it ideal for defining build configurations, scripting automation, and embedding domain-specific logic in applications. -
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Halide
A language for fast, portable data-parallel computation
Halide is a programming language for fast, portable data-parallel computation. It was designed to make writing high-performance image and array processing code much easier on modern machines. It works on all major operating systems and with several CPU architectures (X86, ARM, MIPS, Hexagon, PowerPC) and GPU Compute APIs (CUDA, OpenCL, OpenGL, among others). It isn't a standalone programming language however; rather it is embedded in C++ which means that you write C++ code, building an in-memory representation of a Halide pipeline using Halide's C++ API. ... -
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gluon
A static, type inferred and embeddable language written in Rust
...Marshalling values to and from gluon requires next to no boilerplate, allowing functions defined in Rust to be directly passed to gluon. Gluon supports Unicode out of the box with utf-8 encoded strings and Unicode codepoints as characters. Gluon is a garbage-collected language but uses a separate heap for each executing gluon thread. This keeps each heap small, reducing the overhead of the garbage collector. Gluon is written in Rust, which guarantees thread safety. Gluon keeps the same guarantees, allowing multiple gluon programs to run in parallel. -
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alexscript
Alexscript Polish programming language
AlexScript is an interpreted, general-purpose scripting language with entire syntax in Polish: keywords, standard library, and error messages included. You write jesli, funkcja and klasa instead of if, function and class. It's dynamically typed and object-oriented, drawing on Ruby and JavaScript, and it's implemented from scratch in Ruby as a tree-walking interpreter (lexer, parser, AST, evaluator). Distributed via source, Homebrew and Docker: brew tap N3BCKN/alexscript brew... -
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OK
Welcome to the future of programming languages
...The language emphasises readability and pushing logic out into functions so cases remain simple. It includes concurrency via a map function that executes callbacks in parallel. The project is illustrative of Duffield’s vision: code should feel “magical to write” by removing what is unnecessary. -
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Accelerate
Embedded language for high-performance array computations
...Embedded in the advanced functional programming language Haskell, Accelerate programs are declarative, statically-typed, pure, functional, and ready to exploit all of the performance of modern parallel hardware. The combination of a strong type system, high-level code, and interactive development environment, allows you to develop code quickly with the confidence that it is correct. -
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Idris-dev
A Dependently Typed Functional Programming Language
Idris‑dev is the development version of Idris 1, a general-purpose functional programming language featuring full dependent types, designed for writing type-safe programs and proofs within the language itself. It compiles to C and JavaScript (for Node.js and browsers), and supports code generation via substitute backends. This repository represents the latest development version of the language, and may contain bugs that are being actively worked on. For those who wish to use a more stable... -
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Pipelines
An experimental programming language for data flow
Pipelines is a language and runtime for crafting massively parallel pipelines. Unlike other languages for defining data flow, the Pipeline language requires the implementation of components to be defined separately in the Python scripting language. This allows the details of implementations to be separated from the structure of the pipeline while providing access to thousands of active libraries for machine learning, data analysis, and processing. -
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Skylark
Skylark in Go: the Skylark configuration language
Skylark, now known as Starlark, is an interpreter for a Python-like language implemented in Go. It is designed as a lightweight, deterministic, and embeddable configuration and scripting language ideal for use within larger applications. Skylark maintains Python’s familiar syntax and high-level data types while omitting features that could cause nondeterminism, such as concurrency and dynamic module imports. -
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Chapel
a Productive Parallel Programming Language
Chapel is an emerging parallel programming language whose design and development are being led by HPE in collaboration with academia, computing labs, and industry. Chapel's goal is to improve the productivity of parallel programmers, from laptops to supercomputers. **Please note that Chapel development has moved to GitHub**
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