Search Results for "distributed shared memory" - Page 7
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Showing 385 open source projects for "distributed shared memory"
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Metaseq
Repo for external large-scale work
Metaseq is a flexible, high-performance framework for training and serving large-scale sequence models, such as language models, translation systems, and instruction-tuned LLMs. Built on top of PyTorch, it provides distributed training, model sharding, mixed-precision computation, and memory-efficient checkpointing to support models with hundreds of billions of parameters. The framework was used internally at Meta to train models like OPT (Open Pre-trained Transformer) and serves as a reference implementation for scaling transformer architectures efficiently across GPUs and nodes. ... -
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ParlAI
A framework for training and evaluating AI models
...The library integrates tightly with PyTorch and supports both generative and retrieval-augmented models, along with utilities for multitask training and model selection. A large set of built-in tasks and dataset loaders (with consistent preprocessing and metrics) makes it easy to compare methods under shared conditions. Tools for distributed training, mixed precision, and model zoos help scale experiments from laptops to multi-GPU clusters. -
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GTB: Graphics Toolbox
C++ libraries and apps for computer graphics and data visualization
The Graphics Toolbox (GTB) is a collection of C++ libraries and apps for computer graphics and data visualization. Wagner Correa initially created GTB as part of his Ph.D. research at Princeton University in collaboration with Professor Claudio Silva and Dr. James Klosowski. Several other researchers later contributed to GTB (see the AUTHORS file). -
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Wasmer Python
WebAssembly runtime for Python
...It provides a Pythonic API for loading, compiling, and executing WebAssembly binaries while maintaining strong security guarantees through sandboxing. The library allows interaction with WebAssembly modules via imports, exports, and shared memory, enabling integration between Python code and compiled modules written in other languages. By leveraging the underlying Wasmer runtime, it delivers near-native execution performance while remaining platform-independent. Wasmer Python is particularly useful for embedding plugins, running untrusted code safely, or executing cross-language workloads in a consistent environment. ... -
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ftserver-android
Self-hosted search engine with web service to share discoveries with
Full Text Search Engine for Android Mobile, Windows Desktop, Linux Server. You can use the KeyWord to find relative WebSites, dig in important information, search answers. It has a web server inside, use it to share discoveries with people. App's Source Codes included, can be freely distributed over the internet in an unchanged or changed form. Check the file size after downloaded the Android APK. https://sourceforge.net/projects/ftserver-android/files/ The Code Repository... -
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FeatureBase
A crazy fast analytical database, built on bitmaps
FeatureBase is an Open Source, in-memory, MLAP engine providing SQL support, real-time updates, and analytical processing for your growing data. A binary tree index improves the performance & efficiency of analytical queries by reducing I/O operation. Simple or complex, FeatureBase knocks it out in milliseconds. On-the-fly updates and deletes. Operate instantly on your freshest data without the need for preaggregation. -
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Aurae
Distributed systems runtime daemon written in Rust
Aurae is on a mission to be the most loved and effective way of managing workloads on a node. Our hope is that by bringing a better set of controls to a node, we can unlock brilliant higher-order distributed systems in the future. Aurae deploys a memory-safe 1 runtime daemon, process manager, and PID-1 initialization system to remotely schedule processes, containers, and virtual machines as well as set node configurations (e.g., networking storage). Through system proportioning and enterprise workload isolation techniques, the Aurae open-source project can complement higher-order schedulers and control planes (such as Kubernetes) as Aurae supports the usage of multi-tenant workloads and enterprise identities all the way down to the socket layer. -
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Mars Framework
Mars is a tensor-based unified framework for large-scale data
Mars is a distributed computing framework designed to scale scientific computing and data science workloads across large clusters while preserving the familiar programming interfaces of common Python libraries. The project provides a tensor-based execution model that extends the capabilities of tools such as NumPy, pandas, and scikit-learn so that large datasets can be processed in parallel without rewriting code for distributed environments. -
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SimpleXlsxWriter
C++ library for creating XLSX files for MS Excel 2007 and above.
This library represents XLSX files writer for Microsoft Excel 2007 and above. The main feature of this library is that it uses C++ standard file streams. On the one hand it results in almost unnoticeable memory and CPU resources consumption while processing (that may be very useful at saving a large data arrays), but on the other hand it makes unfeasible to edit data that were written. Hence, if using this library the structure of the future report should be known enough. The library is written in C++ with using STL functionality and based on the ZIP library (included), which has a free license: http://www.codeproject.com/Articles/7530/Zip-Utils-clean-elegant-simple-C-Win32 This library is distributed under the terms of the zlib license: http://www.zlib.net/zlib_license.html -
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FairScale
PyTorch extensions for high performance and large scale training
...It introduced Fully Sharded Data Parallel (FSDP) style techniques that shard model parameters, gradients, and optimizer states across ranks to fit bigger models into the same memory budget. The library also provides pipeline parallelism, activation checkpointing, mixed precision, optimizer state sharding (OSS), and auto-wrapping policies that reduce boilerplate in complex distributed setups. Its components are modular, so teams can adopt just the sharding optimizer or the pipeline engine without rewriting their training loop. ... -
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SnappyData
Memory optimized analytics database, based on Apache Spark
SnappyData (aka TIBCO ComputeDB) is a distributed, in-memory optimized analytics database. SnappyData delivers high throughput, low latency, and high concurrency for a unified analytics workload. By fusing an in-memory hybrid database inside Apache Spark, it provides analytic query processing, mutability/transactions, access to virtually all big data sources and stream processing all in one unified cluster. -
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AWS IoT Over-the-air Update Library
Manage the notification of a newly available update
...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. -
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Rocket Chip
Rocket Chip Generator
...A diplomacy framework (LazyModules) lets designers wire components with negotiated parameters, enabling reuse and rapid exploration of different cache sizes, port counts, and memory hierarchies. The generator supports custom accelerators through the RoCC interface, allowing domain-specific compute units to be plugged into the pipeline with shared cache and memory semantics. Tooling integrates with FIRRTL, Verilator, and commercial EDA flows, and the ecosystem around Rocket Chip (e.g., Chipyard) adds harnesses, peripherals, and verification infrastructure. -
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.NET Boxed
.NET project templates with batteries included
...Use the HTTPS scheme and TLS security across the entire site, redirects HTTP to HTTPS, and adds a Strict Transport Security (HSTS) HTTP header with preloading enabled. Both in-memory and distributed cache are configured. You do need to specify where the distributed cache stores its data. Allow configuring Kestrel security limits such as maximum request size via configuration and set sensible stricter defaults. -
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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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MXNet
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning
Apache MXNet is a scalable, efficient open-source deep learning framework—offering a flexible hybrid programming model (symbolic + imperative) and supporting a wide array of languages—designed for training and deploying neural networks across heterogeneous systems. Apache MXNet is a deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, MXNet contains a dynamic... -
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TensorFlowOnSpark
TensorFlowOnSpark brings TensorFlow programs to Apache Spark clusters
By combining salient features from the TensorFlow deep learning framework with Apache Spark and Apache Hadoop, TensorFlowOnSpark enables distributed deep learning on a cluster of GPU and CPU servers. It enables both distributed TensorFlow training and inferencing on Spark clusters, with a goal to minimize the amount of code changes required to run existing TensorFlow programs on a shared grid. -
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Apache MXNet (incubating)
A flexible and efficient library for deep learning
Apache MXNet is an open source deep learning framework designed for efficient and flexible research prototyping and production. It contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations. On top of this is a graph optimization layer, overall making MXNet highly efficient yet still portable, lightweight and scalable. -
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HipMer
A High performance distributed memory assembler for big genomic data
HipMer is the first end-to-end de novo genome assembler designed for extreme scale analysis via efficient parallelization. The single-genome assembly implementation is a high-performance parallelization and port of the Meraculous assembler (http://jgi.doe.gov/data-and-tools/meraculous/). The MetaHipMer extension is a recent addition to HipMer that is geared to large metagenomes and leverages iterative kmer sizes and a specialized scaffolding algorithm to produce increased contiguity and... -
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FreeRTOS AWS Reference Integrations
IoT operating system for microcontrollers.
...A microcontroller contains a simple, resource-constrained processor that can be found in many devices, including appliances, sensors, fitness trackers, industrial automation, and automobiles. Many of these small devices can benefit from connecting to the cloud or locally to other devices, but have limited compute power and memory capacity. -
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wholeaked
Tool that embeds identifiers in files to trace leak sources
wholeaked is an open source file distribution and tracking tool designed to help identify the source of leaked files. It works by generating unique versions of a file for each recipient and embedding identifying signatures or metadata into each distributed copy. If the file later appears in an unauthorized location, the embedded identifier can be analyzed to determine which recipient originally received that specific version. This approach allows organizations, researchers, or individuals to trace the origin of leaks in sensitive documents, binaries, or other shared resources. wholeaked automates the process of creating personalized file variants and associating them with a list of recipients. ... -
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PJON
Experimental, arduino-compatible, multi-master, multi-media network
PJON® (Padded Jittering Operative Network) is an experimental, Arduino-compatible, multi-master, multi-media, software-defined network protocol that can be easily cross-compiled on many microcontrollers and real-time operative systems like ATtiny, ATmega, SAMD, ESP8266, ESP32, STM32, Teensy, Raspberry Pi, Zephyr, Linux, Windows x86, Apple and Android. PJON operates on a wide range of media, data links and existing protocols like PJDL, PJDLR, PJDLS, Serial, RS485, USB, ASK/FSK, LoRa, UDP,... -
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JAMon API
Monitor Java applications - SQL, HTTP, Methods, Exceptions and more.
JAMon API is a free, simple, high performance, thread safe, Java API that allows developers to easily monitor the performance and scalability of production applications. JAMon tracks hits, execution times (total, avg, min, max, std dev), and more. * JAMon Users Manual: For more on the JAMon, including installing, configuring, and using it, see http://jamonapi.sourceforge.net/. * Support: If you have any questions about usage please post a question on the forum at ... -
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...NESSIE is an electronic structure code that uses a real-space FEM discretization and domain-decomposition (DD) to perform all-electron ground-state DFT and real-time excited-state TDDFT calculations. The code is written to take advantage of multilevel parallelisms of the FEAST eigenvalue solver to target systems containing many distributed-memory compute nodes. The real space mesh is generated using the software tetgen.
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Gitcoin Web
Grow Open Source
...Build resilient projects, better coordination, and positive-sum outcomes. Growing networks with aligned incentives toward the wellbeing of each participant and the system as a whole. Through distributed funding and organizations, we build together toward our shared goals.
