Search Results for "distributed shared memory" - Page 2
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Showing 46 open source projects for "distributed shared memory"
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OneFlow
OneFlow is a deep learning framework designed to be user-friendly
...An extension for OneFlow to target third-party compiler, such as XLA, TensorRT and OpenVINO etc.CUDA runtime is statically linked into OneFlow. OneFlow will work on a minimum supported driver, and any driver beyond. For more information. Distributed performance (efficiency) is the core technical difficulty of the deep learning framework. OneFlow focuses on performance improvement and heterogeneous distributed expansion. It adheres to the core concept and architecture of static compilation and streaming parallelism and solves the memory wall challenge at the cluster level. world-leading level. ... -
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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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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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Gitcoin Web
Grow Open Source
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PyText
A natural language modeling framework based on PyTorch
...It achieves this by providing simple and extensible interfaces and abstractions for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine. We use PyText at Facebook to iterate quickly on new modeling ideas and then seamlessly ship them at scale. Distributed-training support built on the new C10d backend in PyTorch 1.0. Mixed precision training support through APEX (trains faster with less GPU memory on NVIDIA Tensor Cores). Extensible components that allows easy creation of new models and tasks. -
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Wally
Distributed Stream Processing
...By eliminating infrastructure complexity, going from prototype to production has never been simpler. When we set out to build Wally, we had several high-level goals in mind. Create a dependable and resilient distributed computing framework. Take care of the complexities of distributed computing "plumbing," allowing developers to focus on their business logic. Provide high-performance & low-latency data processing. Be portable and deploy easily (i.e., run on-prem or any cloud). Manage in-memory state for the application. Allow applications to scale as needed, even when they are live and up-and-running. ... -
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JavaCá&Lá
A Java Distributed Shared Memory Middleware
How can we easily develop applications for multicore or multicomputer architectures? We frequently use middlewares for that problem, but they are often complex and less productive. This way, at DECOM-UFOP, we have a middleware, named JavaCa&La or just JCL, to build portable and scalable solutions over many high performance computer architectures. Our middleware APIs is simple, intuitive and designed for young and senior programmers who don’t have high performance programming skills. Using... -
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As of now, you can get Ehcache only from ehcache.org or Maven central. A simple, fast, thread safe, standards based cache for Java, and provides memory and disk stores and distributed operation for clusters. ehcache is widely used in such open source projects as Hibernate and Spring. Terracotta offers enterprise edition
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Tuple Spaces
Tuple space with time outs and transactions.
Java implementation of a Tuplespace. Moved to https://github.com/mike-k-houghton/tuplespace A Tuple is an ordered list of items. A Tuple Space is a form of associative memory where entries, tuples, are stored in the space and are retrieved using search criteria that are based on the intrinsic properties of the tuples. The two key operations are put get And that is it! There are refinements on these operations including, for example, timeouts where the tuple will only exist... -
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RapidDevelop R#
RapidDevelop is an IDE and Compiler for a new programming language!
...Being an extension of C#, you can link, build or compile native C# assemblies or Classes and Libraries so that you can very easily port existing code. The programming language also exists in a managed shared library and can be dropped into any .net project so that you can use the compiler in your own projects, with plans to even provide executing compiled code in memory, effectively creating a RapidLang Scripting Language plugin! -
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The SNOMP Library
SNOMP (SNOMP is Not OpenMP) is a library for semi-shared memory parall
SNOMP (SNOMP is Not OpenMP) is a library for semi-shared memory parallelization. -
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TechMVC 3.2.1
MVC2 based HTML 5 enabled Web Application Framework
TechMVC is a very powerful and highly optimized MVC2 based web application framework, which enables developers to build high performance Website. Current Version: 3.1.1 Features Upgraded: =============== 1. Meta Character set support enabled. Can be specified from Config.php($var->defaultCharacterSet). Default: utf-8 2. Following functions added: a. TechMVC::LoadLibrary($path, $shared = false) -> Include library to TechMVC runtime. b. In Config.php varriable... -
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Shared Substance is a programming framework and middleware for developing distributed interactive application. The environment written in Python, operating on the data-oriented programming model.
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Channel is a C++ framework for distributed message passing and event dispatching, configurable with its components (msg ids,routing algorithms...) as template parameters. As a namespace shared by peer threads, channel supports scope control and filtering
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Library that offers users an easy to use interface to synchronize shared data access following the software transactional memory principle.
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Photon provides very fast access to data containers (queues, maps, etc.) in shared memory - it can retrieve millions of data records per second. It also uses some RDB concepts like transactions and crash recovery. See web site for details.
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STLshm provides an C++ STL Allocator implementation for creating and using STL containers (and any other allocator aware types) in shared memory regions. It supports multiple shared region implementations.
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QuickMP (Quick Multi-Processing) is a simple cross-platform C++ API for generating parallel for loops in shared-memory programs, similar to OpenMP. It provides automatic scalable performance based on the number of available processors.
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Jalin aims to bring Linux's IPC facilities within reach of Java programs. Java programs using Jalin will be able to communicate using a variety of techniques from shared memory segments to message queues.
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Blackboard implements a lightweight, portable tuple space suitable for multi-agent system and distributed component design. Supports implicit invocation via content-filtered asynchronous events, blocking call semantics, and shared memory messaging.
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libqmsg is an implementation of well-known Send/Receive/Reply messaging model using Linux shared memory and POSIX message queues.
