Search Results for "shared memory allocator"
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95 projects for "shared memory allocator" with 1 filter applied:
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Train ML Models With SQL You Already KnowBuild and deploy ML models using familiar SQL. Automate data prep with built-in Gemini. Query 1 TB and store 10 GB free monthly.
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Hivemind
Hivemind turns your traces into reusable skills across agents
Hivemind is a shared memory and skill system for AI coding agents. It captures agent sessions as structured traces, including prompts, tool calls, responses, and subagent activity. The system mines those traces for repeated patterns and turns them into reusable skills that can be shared across a team. It supports agents such as Claude Code, OpenClaw, Codex, Cursor, Hermes, and pi. -
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Agent-Native
A framework for building agentic apps
...Each capability is defined once as an action that can be called by both the agent and the user interface. The same actions can also be exposed through HTTP, MCP, A2A, and command-line interfaces. Shared data and application state let agents see relevant UI context and immediately surface their work back to users. The framework includes chat, authentication, permissions, skills, memory, automations, agent teams, and PostgreSQL-backed persistence. It supports PGlite for local development and lets developers bring their own models, databases, tools, and infrastructure. ... -
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EverOS
One portable memory layer for every AI agent
...The system is designed to preserve user context and agent experience across sessions without forcing dependence on a hosted service. EverOS can serve as shared memory infrastructure for coding assistants, personal agents, and custom applications. Its architecture emphasizes user ownership, portability, and self-evolving reuse of accumulated knowledge. -
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Macro
Macro is a unified interface for email, messages, tasks, calls, agents
Macro is an open-source all-in-one workspace that combines email, messages, docs, tasks, calls, agents, pull requests, files, and CRM into one connected interface. It is designed around shared team memory, so information across the workspace can be linked, queried, and used by people or AI agents without losing context. The product emphasizes keyboard-first speed, unified communication, and a single inbox for emails, mentions, tasks, channel updates, and agent responses. Its docs system is collaborative, markdown-native, version-controlled, and built for real-time work. ... -
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Former.skill
AI skill generator designed to reconstruct conversational personality
Ex Skill is an AI skill generator designed to reconstruct the conversational personality and shared memories of a former partner from personal data. It can analyze exported chats, photos, social media records, PDFs, images, and manually entered descriptions. The system builds separate memory and persona layers covering relationship history, habits, emotional patterns, communication style, and behavior. Generated personas can respond in a style modeled after the source material. ... -
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jemalloc
A general purpose malloc(3) implementation
jemalloc is a general purpose malloc(3) implementation that emphasizes fragmentation avoidance and scalable concurrency support. jemalloc first came into use as the FreeBSD libc allocator in 2005, and since then it has found its way into numerous applications that rely on its predictable behavior. In 2010 jemalloc development efforts broadened to include developer support features such as heap profiling and extensive monitoring/tuning hooks. Modern jemalloc releases continue to be integrated... -
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Alook
The collaboration layer for your AI workforce
...Alook also emphasizes memory and traceability, so agents can remember past decisions, learn preferences, and keep a record of instructions and replies. Its main value is turning separate AI coding tools into an organized, always-on operating system for agent-based work. -
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Perfetto
Production-grade client-side tracing, profiling, and analysis
Perfetto is a production-grade tracing platform for Android, Linux, and Chrome that captures extremely detailed information about what a system is doing over time. It’s designed around a low-overhead producer/consumer model: instrumented components (“producers”) write binary events into shared memory buffers and a collector (“service”) reliably streams them to storage. The data model spans kernel and userspace, so you can stitch together CPU scheduling, app lifecycles, binder/IPC hops, GPU work, power and thermal signals, file I/O, heap samples, and more into a single coherent timeline. Perfetto’s ecosystem includes a web-based UI that can load multi-GB traces directly in the browser and an offline “trace processor” that exposes the trace as a queryable SQL-like table schema for deep analysis and automation. ... -
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QM
Multiplayer agent harness for work
QM is an open-source multiplayer agent harness designed for startup teams and company-wide AI work. Each person, channel, and project receives its own scoped memory, files, credentials, permissions, schedules, web apps, and durable sandbox. The same agent identity and configuration can operate through Slack or the web interface. Teams can choose among supported models and harnesses, including Pi, OpenCode, Codex, and Claude Code, without binding the deployment to one vendor. Administrators control organization settings, available models, shared skills, and security posture. ... -
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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TurboFieldfare
Gemma 4 26B-A4B inference in ~2 GB of RAM on any M-series MacBook
TurboFieldfare is a custom Swift and Metal runtime for running the instruction-tuned Gemma 4 26B-A4B model on Apple Silicon Macs with limited memory. Instead of loading the entire model, it keeps the shared core and KV cache in RAM while streaming only the routed experts required for each token from SSD. This approach reduces active memory use to roughly 2 GB while the installed model occupies about 14.3 GB of storage. The project includes a native Mac application, command-line tools, a streaming installer, a Swift library, and an experimental OpenAI-compatible local server. ... -
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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. Additional support... -
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SMUX
A stream multiplexing library for Golang with minimal memory usage
SMUX is a stream multiplexing library for Go that lets multiple logical streams share one reliable underlying connection. It is designed for transports such as TCP or KCP, where ordering and reliability are already provided by the lower layer. The library uses sessions, streams, and frames to manage many independent data flows over a single connection. It focuses on controlled memory usage, smooth receiving behavior, fair traffic shaping, and small protocol overhead. Its design includes a... -
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DSVPN
A dead simple VPN
DSVPN is a Dead Simple VPN, designed to address the most common use case for using a VPN. Runs on TCP. Works pretty much everywhere, including on public WiFi where only TCP/443 is open or reliable. Uses only modern cryptography, with formally verified implementations. Small and constant memory footprint. Doesn't perform any heap memory allocations. Small (~25 KB), with an equally small and readable code base. No external dependencies. Works out of the box. No lousy documentation to read. No... -
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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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cpp-ipc
C++ IPC Library: A high-performance inter-process communication
C++ IPC Library: A high-performance inter-process communication using shared memory on Linux/Windows. -
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Context Hub
Makes coding agents get smarter with every task
Context Hub is a curated documentation system built to help coding agents write more accurate code. It gives agents versioned, language-specific reference material instead of forcing them to rely on noisy web searches or stale model memory. The project includes a CLI called chub that agents can use to search for available docs, fetch specific API guidance, and request only the files they need. It also supports local annotations, allowing an agent to remember project-specific notes, pitfalls, or workarounds across future sessions. Feedback can be sent back to maintainers so shared documentation improves over time. ... -
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BigMac
An open-source toolkit for BigMac-style pipeline-parallel training
BigMac is an open-source toolkit for pipeline-parallel training of multimodal large language models. It preserves optimized language-model pipeline schedules while placing encoder and generator work around them. This design reduces activation memory without bringing back cross-module pipeline bubbles. Its scheduler creates global operator plans, while its executor runs those plans through a shared schedule abstraction. A Megatron-Core reference backend and Qwen3 and Qwen3-VL tutorials help developers connect the approach to real training workflows. The simulator lets researchers visualize schedules, compare pipeline strategies, and model timing imbalances caused by compute cost, input size, or uneven stage partitioning. ... -
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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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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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shmcat
A tool to dump shared memory segments, files and text
This is a simple tool that dumps shared memory segments (System V and POSIX), files and text. It might be useful when you have to debug programs that use shared memory. -
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UAP Common Extensions (UCX)
Utilities Library for C
With this library we provide useful data structures and algorithms for common programming tasks in the C language. -
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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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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...
