Search Results for "distributed shared memory" - Page 5
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Showing 447 open source projects for "distributed shared memory"
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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. ... -
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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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super-agent-party
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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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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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CXX
Safe interop between Rust and C++
CXX is a library that offers safe interop between Rust and C++. It provides a safe mechanism for calling C++ code from Rust and vice versa, one that is protected from the many possible things that can go wrong when bindgen or cbindgen is used to generate unsafe C-style bindings. The general idea of CXX is to define the signatures of both sides of the FFI boundary embedded together in one Rust module. CXX gets a complete picture from this of the boundary, and through it is able to perform... -
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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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AWS SigV4 Library
AWS library to sign AWS HTTP requests with Signature Version 4
...This library can optionally be used by applications sending direct HTTP requests to AWS services requiring SigV4 authentication. This library has no dependencies on any additional libraries other than the standard C library. This library is distributed under the MIT Open Source License. This library has gone through code quality checks including verification that no function has a GNU Complexity score over 8, and checks against deviations from mandatory rules in the MISRA coding standard. Deviations from the MISRA C:2012 guidelines are documented under MISRA Deviations. This library has also undergone static code analysis using Coverity static analysis, and validation of memory safety through the CBMC automated reasoning tool. -
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LingBot-World
Advancing Open-source World Models
LingBot-World is an open-source, high-fidelity world simulator designed to advance the state of world models through video generation. Built on top of Wan2.2, it enables realistic, dynamic environment simulation across diverse styles, including real-world, scientific, and stylized domains. LingBot-World supports long-term temporal consistency, maintaining coherent scenes and interactions over minute-level horizons. With real-time interactivity and sub-second latency at 16 FPS, it is... -
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LMCache
Supercharge Your LLM with the Fastest KV Cache Layer
LMCache is an extension layer for LLM serving engines that accelerates inference, especially with long contexts, by storing and reusing key-value (KV) attention caches across requests. Instead of rebuilding KV states for repeated or shared text segments, LMCache persists and retrieves them from multiple tiers—GPU memory, CPU DRAM, and local disk—then injects them into subsequent requests to reduce TTFT and increase throughput. Its design supports reuse beyond strict prefix matching and enables sharing across serving instances, improving efficiency under real multi-tenant traffic. ... -
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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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Consul Template
Template rendering, notifier, and supervisor for @hashicorp Consul
This project provides a convenient way to populate values from Consul into the file system using the consul-template daemon. The daemon consul-template queries a Consul or Vault cluster and updates any number of specified templates on the file system. As an added bonus, it can optionally run arbitrary commands when the update process completes. Please see the examples folder for some scenarios where this functionality might prove useful. While there are multiple ways to run Consul Template,... -
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tigerbeetle
The financial transactions database designed for mission critical safe
TigerBeetle is production-ready on Linux and seamlessly integrated with major programming languages. TigerBeetle is a financial transactions database designed for mission-critical safety and performance to power the next 30 years of OLTP. TigerBeetle redesigns the distributed database storage engine and consensus protocol for the OLTP workload. This solves the problem of OLTP write contention to unlock three orders of magnitude more performance than a general purpose (OLGP) database. The... -
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HUSTOJ
Popular Open Source Online Judge based on PHP/C++/MySQL/Linux
...(Only the original part of the code, which uses components from other open-source projects, please follow the agreement of the original component.) Because the web terminal/database/judgment machine are all packaged in the same image and cannot be extended, it is not recommended to use this image for distributed judgment. In addition, please do not use the SHM file system in Docker, it will be unable to mount due to insufficient memory space The sandbox environment causes inexplicable runtime errors. The default location of script installation is /home/judge, where src is all source code, data is test data, etc directory is the configuration file of the judgment side, and the install directory is various tool scripts. -
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Omnilingual ASR
Omnilingual ASR Open-Source Multilingual SpeechRecognition
Omnilingual-ASR is a research codebase exploring automatic speech recognition that generalizes across a very large number of languages using shared modeling and training recipes. It focuses on leveraging self-supervised audio pretraining and scalable fine-tuning so low-resource languages can benefit from high-resource data. The project provides data preparation pipelines, training scripts, decoding utilities, and evaluation tools so researchers can reproduce results and extend to new... -
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Linera Protocol
Main repository for the Linera protocol
Linera Protocol is a blockchain or distributed ledger architecture designed for scalable and composable execution across shared state shards. It emphasizes linearizability, causal consistency, and determinism by structuring cross-domain interactions through explicit protocols and asynchronous messaging. Each domain (shard) handles its own commands and state transparently; inter-domain operations rely on well-defined messaging layers and proofs to preserve consistency without central coordination. ... -
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NeuralForecast
Scalable and user friendly neural forecasting algorithms.
NeuralForecast offers a large collection of neural forecasting models focusing on their performance, usability, and robustness. The models range from classic networks like RNNs to the latest transformers: MLP, LSTM, GRU, RNN, TCN, TimesNet, BiTCN, DeepAR, NBEATS, NBEATSx, NHITS, TiDE, DeepNPTS, TSMixer, TSMixerx, MLPMultivariate, DLinear, NLinear, TFT, Informer, AutoFormer, FedFormer, PatchTST, iTransformer, StemGNN, and TimeLLM. There is a shared belief in Neural forecasting methods'... -
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Alluxio
Open Source Data Orchestration for the Cloud
Alluxio is the world’s first open source data orchestration technology for analytics and AI for the cloud. It bridges the gap between computation frameworks and storage systems, bringing data from the storage tier closer to the data driven applications. This enables applications to connect to numerous storage systems through a common interface. It makes data local, more accessible and as elastic as compute. -
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.NET for Apache Spark
A free, open-source, and cross-platform big data analytics framework
.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write... -
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MobileLLM
MobileLLM Optimizing Sub-billion Parameter Language Models
MobileLLM is a lightweight large language model (LLM) framework developed by Facebook Research, optimized for on-device deployment where computational and memory efficiency are critical. Introduced in the ICML 2024 paper “MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases”, it focuses on delivering strong reasoning and generalization capabilities in models under one billion parameters. The framework integrates several architectural innovations—SwiGLU... -
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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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Armbian Linux Build Framework
Armbian Linux Build Framework
...BASH shell and lightweight XFCE-based desktop. Standard boot, config, and update methods with minimal user-space footprint. Special config utilities are optional. A distributed image is compressed to its real data size which starts below 1G. Login is possible via serial, HDMI/VGA or SSH. Boot loader and kernel optimizations, memory caching, ZRAM swap, and video acceleration where applicable. Images are made fully automatized from sources. Releases are PGP signed and code is regularly inspected by the community. ... -
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TensorRT LLM
TensorRT LLM provides users with an easy-to-use Python API
...It provides a Python-based API built on top of PyTorch that allows developers to define, customize, and deploy LLMs efficiently across a variety of hardware configurations, from single GPUs to large multi-node clusters. The library focuses on maximizing throughput and minimizing latency through advanced techniques such as quantization, custom attention kernels, and optimized memory management strategies. It includes support for cutting-edge inference methods like speculative decoding and inflight batching, enabling real-time and large-scale AI applications. TensorRT-LLM integrates seamlessly with NVIDIA’s broader inference ecosystem, including Triton Inference Server and distributed deployment frameworks, making it suitable for production environments. -
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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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Ludwig AI
Low-code framework for building custom LLMs, neural networks
...Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. Retain full control of your models down to the activation functions. Support for hyperparameter optimization, explainability, and rich metric visualizations. Experiment with different model architectures, tasks, features, and modalities with just a few parameter changes in the config. ...
