Search Results for "shared memory"

...UCX exposes a set of abstract communication primitives which utilize the best of available hardware resources and offloads. These include RDMA (InfiniBand and RoCE), TCP, GPUs, shared Memory, and network atomic operations. UCX facilitates rapid development by providing a high-level API, masking the low-level details, while maintaining high-performance and scalability. UCX implements best practices for transfer of messages of all sizes, based on accumulated experience gained from applications running on the world’s largest datacenters and supercomputers.

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. ...

C++ IPC Library: A high-performance inter-process communication using shared memory on Linux/Windows.

...It contains a series of high-quality base components, such as a go-style coroutine, coroutine-based network programming framework, command line, and config file parser, high-performance log library, unit testing framework, JSON library, etc. co has implemented a go-style coroutine, which has the following features. Multi-thread scheduling, the default number of threads is the number of system CPU cores. Shared stack, coroutines in the same thread share several stacks (the default size is 1MB), and the memory usage is low. Simple test on Linux shows that 10 millions of coroutines only take 2.8G of memory (for reference only). There is a flat relationship between coroutines, and new coroutines can be created from anywhere (including in coroutines). ...

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...

...We provide a sample application where an image function (x,y) -> (R,G,B) is learned. The fully fused MLP component of this framework requires a very large amount of shared memory in its default configuration. It will likely only work on an RTX 3090, an RTX 2080 Ti, or high-end enterprise GPUs. Lower-end cards must reduce the n_neurons parameter or use the CutlassMLP (better compatibility but slower) instead. tiny-cuda-nn comes with a PyTorch extension that allows using the fast MLPs and input encodings from within a Python context. ...

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. ...

The ccgsl provides simple C++ wrappers for the GNU Scientific Library. It uses Java-like shared-pointer classes in place of structs to avoid direct memory allocation/freeing and to work better with the STL. It lets you construct functions for optimisation, root-finding and the like from C++ member functions, making it easier to integrate with existing C++ code. It also provides C++ exceptions.

This is a collection of libraries contained : Shared memory allocation, configuration script processor, containers (trees, lists, queues, stacks), file system abstraction, network library, timers/threads, Image library, Display libraries, and more.

To make the native application to support cloud service, csmake will genarate a client stub and the service application, it's similar with the webservice, COBAR, omniORB, SOAP, gsoap etc.

a shared memory allocator that provides a simple interface for named shared memory segments; shared memory between any processes; provides shared memory queues; does not use the same address between processes; fast structured arena file scales well

The AntHill library implements network fail-over and scaling functionality for any user applications and protocols. Implement different transports such as TCP, UDP & Shared Memory. Contains useful utilities such as DumpSender and etc.

libsharedmem is an easy to use C library for handling shared memory blocks on POSIX compatible systems. It also contains malloc()/realloc()/free() -style shared allocation functionality and synchronization primitives. libshmsg adds optionally zero-co

StlMemTrack is a shared class that helps track the memory usage of the specified particular STL containers in your code.

yshm is a C++ shared memory manager.

SHAllocator is C++ STL allocator in SYSTEM V shared memory based on libmm.

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.

One approach to constructing fast queues is to construct a mechanism for using shared memory appropriate containers in C++ as templates. There are three main components: the shared segment of memory, an allocator of memory chunks and the queue itself.

A data parallel scientific programming model. Compiles efficiently to different platforms like distributed memory (MPI), shared memory multi-processor (pthreads), Cell BE processor, Nvidia Cuda, SIMD vectorization (SSE, Altivec), and sequential C++ code.

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.

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.

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.

STL allocator, implements shared memory allocation (for unix/linux systems). Enables sharing memory between processes, while still using the STL API.

DATTEL means "DATa parallel TEmplate Library". It is a C++ library providing STL-algorithms on shared memory (via pthreads) and/or distributed memory (via MPI). The parallelism is hidden from the programmer. Porting code to DATTEL should be easy.

A Pooled, Shared Memory allocator for the C++ Standard Template Library (STL). Allows processes to share an STL container class to facilitate control and communications between the connected processes.