Search Results for "parallel programming frameworkc++"
Sort By:
Showing 183 open source projects for "parallel programming frameworkc++"
View related business solutions-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
$300 Free Credits to Build on Google CloudPut your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
-
1
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. ... -
2
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... -
3
Apache Beam
Unified programming model for Batch and Streaming
Apache Beam is an open source, unified programming model to define both batch and streaming data-parallel processing pipelines, as well as certain language-specific SDKs for constructing pipelines and Runners. These pipelines are executed on one of Beam’s supported distributed processing back-ends, which include Apache Apex, Apache Flink, Apache Spark, and Google Cloud Dataflow. -
4
OpenCL.jl
OpenCL Julia bindings
Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
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... -
6
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). -
7
ChainForge
An open-source visual programming environment
...The platform enables rapid experimentation by generating permutations of prompts and inputs, making it possible to test hundreds of variations in parallel and analyze performance trends more effectively. It also includes evaluation nodes that allow developers to define scoring functions, enabling automated benchmarking of outputs based on custom criteria such as accuracy, formatting, or relevance. -
8
ParallelStencil.jl
Package for writing high-level code for parallel stencil computations
ParallelStencil empowers domain scientists to write architecture-agnostic high-level code for parallel high-performance stencil computations on GPUs and CPUs. Performance similar to CUDA C / HIP can be achieved, which is typically a large improvement over the performance reached when using only CUDA.jl or AMDGPU.jl GPU Array programming. For example, a 2-D shallow ice solver presented at JuliaCon 2020 [1] achieved a nearly 20 times better performance than a corresponding GPU Array programming implementation; in absolute terms, it reached 70% of the theoretical upper performance bound of the used Nvidia P100 GPU, as defined by the effective throughput metric, T_eff. ... -
9
HDF5
Official HDF5® Library Repository
HDF5 (Hierarchical Data Format v5) is a widely-used data management library and file format for storing large and complex scientific data sets efficiently. -
Host LLMs in Production With On-Demand GPUsDeploy your model, get an endpoint, pay only for compute time. No GPU provisioning or infrastructure management required.
-
10
CUDA Core Compute Libraries (CCCL)
CUDA Core Compute Libraries
...It brings together Thrust, CUB, and libcudacxx, which collectively provide high-level abstractions, low-level performance primitives, and a CUDA-compatible standard library for GPU programming. The goal of CCCL is to simplify CUDA development by offering reusable building blocks that enable developers to write efficient and scalable parallel code without starting from scratch. Thrust provides a high-level interface for parallel algorithms, while CUB delivers highly optimized primitives for device-level operations, and libcudacxx ensures compatibility with modern C++ standards. ... -
11
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. -
12
GPU Puzzles
Solve puzzles. Learn CUDA
...By solving progressively more complex puzzles, learners gain a practical understanding of how parallel algorithms operate on graphics processing units. The project emphasizes experimentation and problem solving, encouraging learners to discover GPU programming techniques through trial and exploration. It can be run in cloud environments such as Google Colab, making it easy for beginners to start experimenting without configuring local GPU hardware. -
13
Triton
Development repository for the Triton language and compiler
Triton is a programming language and compiler framework specifically designed for writing highly efficient custom deep learning operations, particularly for GPUs. It aims to bridge the gap between low-level GPU programming, such as CUDA, and higher-level abstractions by providing a more productive and flexible environment for developers. 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. ... -
14
Sogou C++ Workflow
C++ parallel computing and asynchronous networking engine
As Sogou`s C++ server engine, Sogou C++ Workflow supports almost all back-end C++ online services of Sogou, including all search services, cloud input method, online advertisements, etc., handling more than 10 billion requests every day. This is an enterprise-level programming engine in light and elegant design which can satisfy most C++ back-end development requirements. -
15
Numaflow
Kubernetes-native platform to run massively parallel data/streaming
Numaflow is a Kubernetes-native tool for running massively parallel stream processing. A Numaflow Pipeline is implemented as a Kubernetes custom resource and consists of one or more source, data processing, and sink vertices. Numaflow installs in a few minutes and is easier and cheaper to use for simple data processing applications than a full-featured stream processing platform. -
16
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. -
17
CUDA Python
Performance meets Productivity
...It acts as a metapackage composed of multiple submodules that provide both high-level and low-level access to CUDA functionality, including runtime APIs, driver APIs, and JIT compilation tools. The project is designed to simplify GPU programming by offering Pythonic abstractions while still exposing the full power of CUDA for advanced users. It integrates tightly with the broader Python GPU ecosystem, including Numba for kernel compilation and CCCL for parallel primitives, allowing developers to write performant code without leaving Python. The toolkit also includes utilities for profiling, memory management, distributed computing, and numerical operations, making it suitable for scientific computing, AI, and data processing workloads. -
18
CubeCL
Multi-platform high-performance compute language extension for Rust
CubeCL is a low-level compute language and compiler framework designed to simplify and optimize GPU programming for high-performance workloads, particularly in machine learning and numerical computing. It provides an abstraction layer that allows developers to write portable, hardware-efficient compute kernels without directly dealing with complex GPU APIs such as CUDA or OpenCL. CubeCL focuses on delivering predictable performance and composability by exposing explicit control over memory... -
19
ispc
Intel SPMD Program Compiler
ispc is a compiler for a variant of the C programming language, with extensions for single programs, and multiple data programming. Under the SPMD model, the programmer writes a program that generally appears to be a regular serial program, though the execution model is actually that a number of program instances execute in parallel on the hardware. ispc compiles a C-based SPMD programming language to run on the SIMD units of CPUs and GPUs; it frequently provides a 3x or more speedup on architectures with 4-wide vector SSE units and 5x-6x on architectures with 8-wide AVX vector units, without any of the difficulty of writing intrinsics code. ... -
20
Scala 2
Scala 2 compiler and standard library
Scala combines object-oriented and functional programming in one concise, high-level language. Scala's static types help avoid bugs in complex applications, and its JVM and JavaScript runtimes let you build high-performance systems with easy access to huge ecosystems of libraries. Scastie is Scala + sbt in your browser! You can use any version of Scala, or even alternate backends such as Dotty, Scala.js, Scala Native, and Typelevel Scala. You can use any published library. You can save and... -
21
AWS SDK for Go v2
AWS SDK for the Go programming language
Welcome to the AWS SDK for Go. The AWS SDK for Go V2 provides APIs and utilities that developers can use to build Go applications that use AWS services, such as Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Simple Storage Service (Amazon S3). The SDK removes the complexity of coding directly against a web service interface. It hides a lot of the lower-level plumbing, such as authentication, request retries, and error handling. The SDK also includes helpful utilities. For example, the... -
22
nbdev
Create delightful software with Jupyter Notebooks
nbdev is a notebook-driven development platform (by fast.ai/AnswerDotAI) enabling you to write code, tests, documentation, and deploy software, all from Jupyter Notebooks. It provides a unified literate programming workflow where you can tag notebook cells for export to Python modules, auto-generate documentation via Quarto (and host it on GitHub Pages), run tests embedded in notebooks, manage clean notebooks with Git-friendly metadata hooks, and seamlessly publish packages to PyPI/conda,... -
23
SimpleITK
A layer built on top of the Insight Toolkit (ITK)
SimpleITK is an image analysis toolkit with a large number of components supporting general filtering operations, image segmentation and registration. It is built on top of the Insight Segmentation and Registration Toolkit ITK with the intent of providing a simplified interface to ITK. SimpleITK itself is written in C++ but is available for a large number of programming languages. Wrapping of the C++ code is accomplished through SWIG, in principle, any language wrapped by SWIG should be... -
24
Bazel
Fast, scalable, multi-language and extensible build system
...Share and re-use language rules written by the growing Bazel community. Bazel is the common build tool throughout Pinterest and has been instrumental in achieving fast, reproducible builds across our programming languages and platforms. -
25
Artichoke Ruby
Artichoke is a Ruby made with Rust
Artichoke is an experimental implementation of the Ruby programming language written primarily in Rust, aiming to provide a modern, embeddable, and portable Ruby runtime. It is designed to be compatible with MRI Ruby while exploring new approaches to performance, safety, and execution models through Rust’s systems programming capabilities. One of its key goals is to enable Ruby to run in environments where traditional implementations struggle, including WebAssembly and sandboxed or untrusted execution contexts. ...
