Search Results for "distributed shared memory" - Page 2
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173 projects for "distributed shared memory" with 1 filter applied:
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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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Go from Code to Production URL in SecondsSkip the Kubernetes configs. Cloud Run handles HTTPS, scaling, and infrastructure automatically. Two million requests free per month.
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DLRM
An implementation of a deep learning recommendation model (DLRM)
DLRM (Deep Learning Recommendation Model) is Meta’s open-source reference implementation for large-scale recommendation systems built to handle extremely high-dimensional sparse features and embedding tables. The architecture combines dense (MLP) and sparse (embedding) branches, then interacts features via dot product or feature interactions before passing through further dense layers to predict click-through, ranking scores, or conversion probabilities. The implementation is optimized for... -
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Liveblocks
Liveblocks gives you the building blocks and infrastructure
Liveblocks is an open-source collaboration infrastructure and toolkit that enables developers to integrate real-time collaborative features into web and mobile applications with minimal effort. It provides building blocks like multiplayer cursors, comments, notifications, and AI-agent hooks that can be composed to support shared experiences such as collaborative editing, synchronized state, or embedded AI collaboration within apps. Rather than building real-time synchronization from scratch, developers can leverage Liveblocks’ SDKs and APIs to focus on their product’s unique logic while relying on robust back-end support for distributed state and event propagation. ... -
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OpenTinker
OpenTinker is an RL-as-a-Service infrastructure for foundation models
...Traditional RL setups can be monolithic and difficult to configure, but OpenTinker separates concerns across agent definition, environment interaction, and execution, which lets developers focus on defining the logic of agents and environments separately from how training and inference are run. It introduces a centralized scheduler to manage distributed training jobs and shared compute resources, enabling workloads like reinforcement learning, supervised fine-tuning, and inference to run across multiple settings. The architecture supports a range of single-turn and multi-turn agentic tasks with a design that abstracts away infrastructure complexity while offering flexible Python APIs to define environments and workflows. -
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rxRust
Zero-cost & Type-safe Reactive Extensions for Rust
...It enables developers to model asynchronous data streams and event-driven systems declaratively, using composable operators that transform and combine streams over time. The library is designed to leverage Rust’s ownership and type systems to ensure memory safety and efficient resource management without sacrificing performance. It supports both single-threaded and multi-threaded execution contexts, allowing developers to choose between lightweight local execution or synchronized shared concurrency depending on their needs. rxRust is particularly well-suited for building responsive systems such as GUIs, real-time data pipelines, and asynchronous services. ... -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Extractous
Fast and efficient unstructured data extraction
...Its purpose is to extract text and metadata efficiently from formats such as PDF, Word, HTML, email archives, images, and more, without depending on external APIs or separate parsing servers. The project emphasizes performance and low memory usage, and its maintainers describe it as a local-first alternative to heavier extraction stacks. For broader format support, the system combines its Rust core with ahead-of-time compiled Apache Tika shared libraries, which allows it to extend parsing coverage while still avoiding traditional server-based overhead. It also supports OCR for images and scanned documents through Tesseract, making it useful for document ingestion pipelines that include image-based or scanned inputs. -
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Refly
The first open-source agent skills builder
...With a focus on making automation accessible, it provides a visual canvas and low-code components that feel similar to drag-and-drop builders but backed by powerful AI orchestration, memory handling, and integrations with external services. Refly’s approach bridges the gap between workflow ideas and stable, deterministic infrastructure: skills become governed capabilities that can be versioned, shared, and monetized, not just temporary scripts. -
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lua-resty-openidc
OpenID Connect Relying Party and OAuth 2.0 Resource Server
...It maintains sessions for authenticated users by leveraging lua-resty-session thus offering a configurable choice between storing the session state in a client-side browser cookie or use in of the server-side storage mechanisms shared-memory|memcache|redis. -
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super-agent-party
All-in-one AI companion! Desktop girlfriend + virtual streamer
Super Agent Party is an open-source experimental framework designed to demonstrate collaborative multi-agent AI systems interacting within a shared environment. The project explores how multiple specialized AI agents can coordinate to solve complex tasks by communicating with each other and sharing information. Instead of relying on a single monolithic model, the framework organizes agents with different roles or capabilities that cooperate to achieve goals. Each agent may handle different... -
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Apache Flink
Stream processing framework with powerful stream
Apache Flink is a distributed engine for stateful computations over data streams and batches, designed for low-latency processing at scale. Its core runtime executes dataflow graphs with fine-grained backpressure and checkpointing, allowing applications to recover consistently from failures. Flink’s event-time model and watermarks enable accurate out-of-order processing, windowing, and complex time semantics that typical real-time systems struggle with. Developers program against high-level... -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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DynaMix
A new take on polymorphism
DynaMix (Dynamic Mixins) is an alternative take on object-oriented programming and dynamic polymorphism. It lets users compose and modify polymorphic objects at run time. The main target language is C++, but C is also supported. The library is a means to create a project's architecture rather than achieve its purpose. It helps with extensibility, readability, scalability, and interoperability. It focuses on maximal performance and minimal memory overhead. The library uses the type... -
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Apache Spark
A unified analytics engine for large-scale data processing
Apache Spark is a unified engine for large-scale data processing, offering APIs for batch jobs, streaming, machine learning, and graph computation. It builds on resilient distributed datasets (RDDs) and the newer DataFrame/Dataset abstractions to provide fault-tolerant, in-memory computation across clusters. Spark’s execution engine handles scheduling, shuffles, caching, and data locality so users can focus on transformations rather than infrastructure plumbing. With Spark Streaming (microbatches) and Structured Streaming, it delivers low-latency event processing suitable for real-time analytics. ... -
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Swarms
Enterprise multi-agent orchestration framework for scalable AI apps
...Swarms also includes mechanisms for agent lifecycle management, memory handling, and dynamic composition, making it adaptable to evolving workloads. Additionally, it focuses on developer productivity through APIs, CLI tools, and templates that simplify building and deploying agent-based applications. -
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Light-4J
A fast, lightweight and more productive microservices framework
Light means lightweight, lightning-fast and shedding light on how to program with modern Java SE for cloud-native deployment. I had been working on the Java EE platforms since early 2000 and suffered performance and productivity issues. In 2014, I realized that the IT industry was moving from Monolithic to Microservices and from on-premise data centers to the public clouds. To reduce the production cost for my applications, I need to find a lightweight platform that has a small memory... -
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Chitu
High-performance inference framework for large language models
...It supports heterogeneous computing environments, including CPUs, GPUs, and various specialized AI accelerators, allowing models to run across a wide range of infrastructure configurations. Chitu is designed to scale from small single-machine deployments to large distributed clusters that handle high volumes of concurrent inference requests. The system also includes performance optimizations for large models, including support for quantized formats and efficient computation operators that reduce memory usage and latency. Its architecture aims to support enterprise adoption by ensuring stable long-term operation under production workloads. -
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Workerman
An asynchronous event driven PHP socket framework
Workerman is an open source high-performance asynchronous PHP socket framework . Supports high concurrency, ultra-high stability, and is widely used in mobile apps, mobile communications, WeChat applets, mobile game servers, online games, PHP chat rooms, hardware communications, smart homes, Internet of Vehicles, Internet of Things and other fields Development. Support TCP long connection, support Websocket, HTTP and other protocols, support custom protocol. It has many high-performance... -
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EasyZSwoole
swoole, easyswoole, swoole framework
EasySwoole is a distributed swoole framework with a permanent memory. It is born specifically for API and supports the simultaneous monitoring of HTTP, WebSocket, self-defined TCP, UDP protocol, and has rich components, such as collaboration Connect Pool, TP style co-process ORM, co-process microcredit SDK, co-process Kafka client, co-process ElasticSearch client, co-process Consul client, co-process Redis client, co-process Apollo client, co-process NSQ client, co-process self-definition queue、 Many components such as the Memcached client, the co-process view engine, JWT, the co-process RPC, the co-process SMTP client, the co-process HTTP client, the co-process Actor, and the Crontab timer. ... -
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Laravel Haystack
Supercharged job chains for Laravel
Laravel Haystack provides supercharged job chains for Laravel. It comes with powerful features like delaying jobs for as long as you like, applying middleware to every job, sharing data and models between jobs and even chunking jobs. Laravel Haystack supports every queue connection/worker out of the box. (Database, Redis/Horizon, SQS). It's great if you need to queue thousands of jobs in a chain or if you are looking for features that the original Bus chain doesn't provide. If you need to... -
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DeepSpeed
Deep learning optimization library: makes distributed training easy
DeepSpeed is an easy-to-use deep learning optimization software suite that enables unprecedented scale and speed for Deep Learning Training and Inference. With DeepSpeed you can: 1. Train/Inference dense or sparse models with billions or trillions of parameters 2. Achieve excellent system throughput and efficiently scale to thousands of GPUs 3. Train/Inference on resource constrained GPU systems 4. Achieve unprecedented low latency and high throughput for inference 5. Achieve extreme... -
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librsb
A shared memory parallel sparse matrix library including Sparse BLAS.
librsb is a library for sparse matrix computations featuring the Recursive Sparse Blocks (RSB) matrix format. This format allows cache efficient and multi-threaded (that is, shared memory parallel) operations on large sparse matrices. The most common operations necessary to iterative solvers are available, e.g.: matrix-vector multiplication, triangular solution, rows/columns scaling, diagonal extraction / setting, blocks extraction, norm computation, formats conversion. The RSB format is especially well suited for symmetric and transposed multiplication variants. ... -
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SAGECAL
GPU/MIC accelerated radio interferometric calibration program
SAGECal is a very fast, memory efficient and GPU accelerated radio interferometric calibration program. It can handle all source models including points, Gaussians and Shapelets. It can calibrate along hundreds of directions without running out of memory in almost real time. Intel Xeon Phi acceleration is also available. Distributed calibration using MPI and consensus optimization is enabled. -
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Simple components for Ada
A software components library
The Simple components for Ada library provides implementations of smart pointers for automatically collected objects (using reference counting), object persistence, unbounded and bounded arrays of smart pointers, generic unbounded arrays of private objects and plain pointers, generic sets, maps, arbitrary precision arithmetic, B-trees, directed graphs, directed weighted graphs, stacks, and storage pools. It also includes table management, string editing, IEEE 754 support, and infix... -
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JDiskCat
Multi-platform disk cataloguing utility written in java.
Easy-to-use multi-platform disk cataloguing program supporting local or removable media - drives and folders. Uses XML files as a data storage. It was originally created in 2010 to catalogue software compilations (also called freeware compilations) and CDs distributed with computer magazines. It was later improved to support any kind of disk and folder. It can be used to catalogue fragile disks like CDs, floppies, external hard drives, usb sticks, memory cards which are easy to damage. Cataloguing enables user to check what they contain without putting them physically into drive and avoid a possibility of a mechanical damage. ... -
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BMDFM
Binary Modular DataFlow Machine (BMDFM)
Binary Modular DataFlow Machine (BMDFM) is a software package that enables running an application in parallel on shared memory symmetric multiprocessing (SMP) computers using the multiple processors to speed up the execution of single applications. BMDFM automatically identifies and exploits parallelism due to the static and mainly dynamic scheduling of the dataflow instruction sequences derived from the formerly sequential program. 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. ... -
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gokv
Simple key-value store abstraction and implementations for Go
Simple key-value store abstraction and implementations for Go. Redis, Consul, etcd, bbolt, BadgerDB, LevelDB, Memcached, DynamoDB, S3, PostgreSQL, MongoDB, CockroachDB, and many more. There are detailed descriptions of the methods in the docs and in the code. You should read them if you plan to write your own gokv.Store implementation or if you create a Go package with a method that takes a gokv.Store as a parameter, so you know exactly what happens in the background. -
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Ring
Simple and flexible programming language for applications development
The Ring is a practical general-purpose multi-paradigm language. The supported programming paradigms are imperative, procedural, object-oriented, declarative using nested structures, functional, meta programming and natural programming. The language is portable (MS-DOS, Windows, Linux, macOS, Android, WebAssembly, Microcontrollers, etc.) and can be used to create Console, GUI, Web, Games and Mobile applications. The language is designed to be simple, small and flexible. Ring is...
