Search Results for "distributed shared memory"

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.

AlgART Java libraries for processing arrays and matrices are open-source product, distributed under MIT license. So, anyone can use them for free without any restrictions. Main features: 63-bit addressing of array elements (64-bit long int indexes), memory model concept (allowing storing data in different schemes from RAM to mapped disk files), wide usage of lazy evaluations, built-in multithreading optimization for multi-core processors, wide set of image processing algorithms over matrices, etc. - please see at the site. ...

The Safe C Library provides bound checking memory and string functions per ISO/IEC TR24731. These functions are alternative functions to the existing standard C library that promote safer, more secure programming. The ISO/IEC Programming languages — C spec, C11, now includes the bounded APIs in Appendix K, "Bounds-checking interfaces". This latest upload supports building static library, a shared library and a linux kernel module.

SNOMP (SNOMP is Not OpenMP) is a library for semi-shared memory parallelization.

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.

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.