Search Results for "parallel"
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Showing 15 open source projects for "parallel"
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The Futhark Programming Language
A data-parallel functional programming language
Futhark is a small programming language designed to be compiled into efficient parallel code. It is a statically typed, data-parallel, and purely functional array language in the ML family, and comes with a heavily optimizing ahead-of-time compiler that presently generates either GPU code via CUDA and OpenCL, or multi-threaded CPU code. Futhark is not designed for graphics programming, but can instead use the compute power of the GPU to accelerate data-parallel array computations. ... -
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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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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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Starlark in Go
Starlark in Go: the Starlark configuration language, implemented in Go
...The Go-based interpreter allows developers to run or embed Starlark programs directly within Go applications, extending them with user-defined scripts and configurable logic. Unlike Python, Starlark supports parallel execution across multiple threads and maintains deterministic behavior, making it suitable for scalable and reproducible workloads. It offers familiar syntax features such as dictionaries, lists, and first-class functions with lexical scoping. -
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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. Libraries from Python, R, C/Fortran, C++, and Java can also be used. -
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Triton
Development repository for the Triton language and compiler
...Triton enables users to write optimized kernels for machine learning workloads while maintaining readability and control over performance-critical aspects like memory access patterns and parallel execution. The project leverages LLVM and MLIR to compile code into efficient GPU instructions, supporting both NVIDIA and AMD hardware. It is widely used in research and production environments where custom tensor operations are required, offering both high performance and developer-friendly syntax. -
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BMDFM
Binary Modular DataFlow Machine (BMDFM)
...The BMDFM dynamic scheduling subsystem performs a symmetric multiprocessing (SMP) emulation of a tagged-token dataflow machine to provide the transparent dataflow semantics for the applications. No directives for parallel execution are needed. More info: http://www.bmdfm.com -
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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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gluon
A static, type inferred and embeddable language written in Rust
...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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Accelerate
Embedded language for high-performance array computations
...These computations are online-compiled and executed on a range of architectures. Accelerate is a free, general-purpose, open-source library that simplifies the process of developing software that targets massively parallel architectures including multicore CPUs and GPUs. 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
...Because it runs deterministically and isolates execution from system state, it’s well-suited for reproducible build systems and other sandboxed environments. The Go implementation focuses on parallel scalability and easy integration into Go-based projects. -
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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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PARUS
Dataflow parallel programming language for clusters
PARUS is a data-flow parallel programming language that allows to build parallel programs for clusters and MPP multiprocessors. The data-flow graph is automatically converted to the C++/MPI source and linked with the libparus runtime library. Also there are available tools for benchmarking cluster interconnect and visualize it.
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