Search Results for "compute"
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Showing 123 open source projects for "compute"
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CUDA Core Compute Libraries (CCCL)
CUDA Core Compute Libraries
CCCL, or CUDA Core Compute Libraries, is a unified repository that consolidates several foundational CUDA C++ libraries into a single, cohesive development platform. 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. -
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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. -
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AWS Node Termination Handler
Gracefully handle EC2 instance shutdown within Kubernetes
...If not handled, your application code may not stop gracefully, take longer to recover full availability, or accidentally schedule work to nodes that are going down. Secure and resizable compute capacity for virtually any workload. Amazon Elastic Compute Cloud (Amazon EC2) offers the broadest and deepest compute platform, with over 500 instances and a choice of the latest processor, storage, networking, operating system, and purchase model to help you best match the needs of your workload. We are the first major cloud provider that supports Intel, AMD, and Arm processors, the only cloud with on-demand EC2 Mac instances, and the only cloud with 400 Gbps Ethernet networking. -
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Bacalhau
Community-driven, simple, yet powerful framework
Bacalhau is a decentralized compute platform for running jobs on data stored across distributed networks, like IPFS or Filecoin, without moving the data to centralized cloud environments. It allows developers to run containerized workloads close to where the data lives, reducing latency, cost, and privacy risks. Bacalhau supports various runtime environments and is designed to make decentralized data processing as accessible as traditional cloud computing. -
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.
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Amazon ECS Container Agent
Amazon Elastic Container Service Agent
...Launch thousands of containers across the cloud using your preferred continuous integration and delivery (CI/CD) and automation tools. Optimize your time with AWS Fargate serverless compute for containers, which eliminates the need to configure and manage control plane, nodes, and instances. Save up to 50 percent on compute costs with autonomous provisioning, auto-scaling, and pay-as-you-go pricing. Integrate seamlessly with AWS management and governance solutions, standardized for compliance with virtually every regulatory agency around the globe. ... -
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AWS .NET deployment tool
The tooling that simplifies deployment of .NET applications
...The tool will generate a Dockerfile if needed, otherwise, an existing Dockerfile will be used. The tool builds the deployment artifacts, generates a deployment CDK project, provisions the infrastructure and deploys your application to the chosen AWS compute. -
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Session Manager Plugin
This plugin helps you to use the AWS Command Line Interface (AWS CLI)
This plugin helps you to use the AWS Command Line Interface (AWS CLI) to start and end sessions to your managed instances. Session Manager is a fully managed AWS Systems Manager capability that lets you manage your Amazon Elastic Compute Cloud (Amazon EC2) instances, on-premises instances and virtual machines. Session Manager provides secure and auditable instance management without the need to open inbound ports. When you use the Session Manager plugin with the AWS CLI to start a session, the plugin builds the websocket connection to your managed instances. Session Manager supports connecting to Amazon Elastic Compute Cloud (Amazon EC2) instances, in addition to servers or virtual machines (VMs) in your hybrid environment that use the advanced-instances tier. ... -
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Silk.NET
About The high-speed OpenGL, OpenCL bindings library
...Silk.NET caters for anything you could need in swift development of multimedia, graphics, compute applications. Silk.NET is an all-in-one solution, complete with Graphics, Compute, Audio, Input, and Windowing. -
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AWS ParallelCluster Node
Python package installed on the Amazon EC2 instances
...AWS ParallelCluster is an AWS-supported Open Source cluster management tool that makes it easy for you to deploy and manage High-Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources and a shared filesystem and offers a variety of batch schedulers such as AWS Batch and Slurm. AWS ParallelCluster facilitates both quick start proof of concepts (POCs) and production deployments. You can build higher-level workflows, such as a Genomics portal that automates the entire DNA sequencing workflow, on top of AWS ParallelCluster. -
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Reselect
Selector library for Redux
Simple “selector” library for Redux (and others) inspired by getters in NuclearJS, subscriptions in re-frame and this proposal from speedskater. Selectors can compute derived data, allowing Redux to store the minimal possible state. Selectors are efficient. A selector is not recomputed unless one of its arguments changes. Selectors are composable. They can be used as input to other selectors. Reselect provides a function createSelector for creating memoized selectors. createSelector takes an array of input-selectors and a transform function as its arguments. ... -
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The Futhark Programming Language
A data-parallel functional programming language
...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. The language supports regular nested data-parallelism, as well as a form of imperative-style in-place modification of arrays, while still preserving the purity of the language via the use of a uniqueness type system. While the Futhark language and compiler is an ongoing research project, it is quite usable for real programming and can compile nontrivial programs which then run on real machines at high speed. -
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Halide
A 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. This representation can then be compiled to an object file, or a JIT-compile and run in the same process. ... -
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VulkanSceneGraph
Vulkan & C++17 based Scene Graph Project
VulkanSceneGraph (VSG), is a modern, cross-platform, high-performance scene graph library built upon Vulkan graphics/compute API. The software is written in C++17 and follows the CppCoreGuidelines and FOSS Best Practices. The source code is published under the MIT License, with the exception of vulkan.h, used for Vulkan extensions, which is under Apache License 2.0. This repository contains C++ headers and source and CMake build scripts to build the libvsg library. -
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TypeGPU
A modular and open-ended toolkit for WebGPU
TypeGPU is a modular TypeScript toolkit for working with WebGPU in a more type-safe and developer-friendly way. It lets developers define GPU logic with advanced type inference while still targeting WebGPU and WGSL-based execution. The project is designed for graphics, compute shaders, GPU programming, and high-performance browser or React Native experiments. It can generate WGSL from TypeScript-style functions, helping developers keep GPU code closer to the rest of their application logic. TypeGPU is useful for teams that want the power of WebGPU without losing the safety and tooling benefits of TypeScript. ... -
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Hono
Web framework built on Web Standards
Hono is a small, simple, and ultrafast web framework built on Web Standards. It works on any JavaScript runtime: Cloudflare Workers, Fastly Compute, Deno, Bun, Vercel, AWS Lambda, Lambda@Edge, and Node.js. The router RegExpRouter is really fast. The hono/tiny preset is under 14kB. Using only Web Standard APIs. Works on Cloudflare, Fastly, Deno, Bun, AWS, or Node.js. The same code runs on all platforms. Hono has built-in middleware, custom middleware, third-party middleware, and helpers. ... -
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AWS ParallelCluster Cookbook
The Chef cookbook used to build and bootstrap AWS ParallelCluster
AWS ParallelCluster is an AWS supported Open Source cluster management tool that makes it easy for you to deploy and manage High Performance Computing (HPC) clusters in the AWS cloud. Built on the Open Source CfnCluster project, AWS ParallelCluster enables you to quickly build an HPC compute environment in AWS. It automatically sets up the required compute resources and a shared filesystem and offers a variety of batch schedulers such as AWS Batch and Slurm. AWS ParallelCluster facilitates both quick start proof of concepts (POCs) and production deployments. You can build higher-level workflows, such as a Genomics portal that automates the entire DNA sequencing workflow, on top of AWS ParallelCluster. ... -
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Argo Workflows
Workflow engine for Kubernetes
...Define workflows where each step in the workflow is a container. Model multi-step workflows as a sequence of tasks or capture the dependencies between tasks using a directed acyclic graph (DAG). Easily run compute intensive jobs for machine learning or data processing in a fraction of the time using Argo Workflows on Kubernetes. Run CI/CD pipelines natively on Kubernetes without configuring complex software development products. Argo Workflows is the most popular workflow execution engine for Kubernetes. It can run 1000s of workflows a day, each with 1000s of concurrent tasks. ... -
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Google Cloud's buildpacks
Builders and buildpacks designed to run on Google Cloud's container
...It is built around full compatibility with the Cloud Native Buildpacks specification, which means it can participate in standardized build workflows while still being tailored to Google Cloud environments. The project supports major runtime destinations such as Cloud Run, GKE, Anthos, and Compute Engine with Container-Optimized OS, and it also powers build flows for App Engine and Cloud Functions. One of its strengths is that it does not only provide buildpacks themselves, but also builder images that work with tools such as pack, kpack, Tekton, and Skaffold, giving developers flexibility in how they incorporate it into CI/CD systems. -
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Micro Cloud
A distributed OS built for the Cloud
...Micro is the all encompassing end to end platform experience from source to running and beyond built with a developer first focus. Micro’s goal is to abstract away the complexity of building services for the Cloud. The cloud itself has gone through a huge boom through managed Compute and infrastructure services from the likes of AWS and others. It’s taken what was an operational burden and turned it into a suite of fully managed on demand services which can be used via APIs. Micro is built as a microservices architecture and abstracts away the complexity of the underlying infrastructure. -
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SwissGL
SwissGL is a minimalistic wrapper on top of WebGL2 JS API
...Acting as a "Swiss Army knife" for WebGL2, it simplifies shader, texture, and framebuffer management into a single, expressive interface that enables developers to write complex GPU workflows in just a few lines of code. The library centers around one main function that unifies rendering and compute operations, allowing the creation of particle systems, GPGPU effects, and real-time simulations entirely on the GPU. Despite its simplicity and small size (under 1000 lines of code), SwissGL demonstrates remarkable flexibility, from basic visual experiments to complex multi-pass rendering pipelines. It’s also designed as an exploration of minimalist graphics API design, serving as an early experimental step toward the upcoming WebGPU era. -
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FlashMLA
FlashMLA: Efficient Multi-head Latent Attention Kernels
...The library supports both BF16 and FP16 data types, and includes a paged KV cache implementation with a block size of 64 to efficiently manage memory during decoding. On very compute-bound settings, it can reach up to ~660 TFLOPS on H800 SXM5 hardware, while in memory-bound configurations it can push memory throughput to ~3000 GB/s. The team regularly updates it with performance improvements; for example, a 2025 update claims 5 % to 15 % gains on compute-bound workloads while maintaining API compatibility. -
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BentoML
Unified Model Serving Framework
...Standard .bento format for packaging code, models and dependencies for easy versioning and deployment. Integrate with any training pipeline or ML experimentation platform. Parallelize compute-intense model inference workloads to scale separately from the serving logic. Adaptive batching dynamically groups inference requests for optimal performance. Orchestrate distributed inference graph with multiple models via Yatai on Kubernetes. Easily configure CUDA dependencies for running inference with GPU. Automatically generate docker images for production deployment. -
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SpaceWasm
A flight-compliant WebAssembly interpreter
...Its custom memory model uses fixed-size pages to provide deterministic allocation behavior and avoid panic on allocation failure. Embedders can expose controlled host functions while restricting program access, compute time, and system interactions. The project emphasizes sandboxing, portability, predictable resource use, and compatibility with flight-software requirements. Tests, fuzzing, benchmarks, requirements, and integration components are included in the Rust codebase. -
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NVTX (NVIDIA Tools Extension Library)
C-based Application Programming Interface (API)
...It allows developers to insert markers, ranges, and events directly into their applications, providing contextual insight into how code executes on CPUs and GPUs. These annotations are visualized in tools such as NVIDIA Nsight Systems and Nsight Compute, enabling developers to identify performance bottlenecks, track execution flow, and correlate application behavior with hardware activity. The API is written in C and includes wrappers for C++ and Python, making it accessible across different programming environments and workloads. NVTX is particularly valuable in high-performance computing and AI workloads where understanding concurrency, memory usage, and kernel execution is critical for optimization. -
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oneDNN
oneAPI Deep Neural Network Library (oneDNN)
This software was previously known as Intel(R) Math Kernel Library for Deep Neural Networks (Intel(R) MKL-DNN) and Deep Neural Network Library (DNNL). oneAPI Deep Neural Network Library (oneDNN) is an open-source cross-platform performance library of basic building blocks for deep learning applications. oneDNN is part of oneAPI. The library is optimized for Intel(R) Architecture Processors, Intel Processor Graphics and Xe Architecture graphics. oneDNN has experimental support for the...
