Search Results for "parallel computing"
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Showing 7 open source projects for "parallel computing"
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Chapel
a Productive Parallel Programming Language
Chapel is an emerging parallel programming language whose design and development are being led by HPE in collaboration with academia, computing labs, and industry. Chapel's goal is to improve the productivity of parallel programmers, from laptops to supercomputers. **Please note that Chapel development has moved to GitHub** -
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Tsunami is an open-source high performance computing language. With it you can write streaming data-parallel algorithms that utilize GPGPUs for orders-of-magnitude speed-up with the ease of writing sequential algorithms.
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DKU is an embedded parallel language, or "piggy-back" language that uses function calls to invoke the language's execution model. It tunes task-size to the hardware while hiding hardware details for high performance portability of parallel code.
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LIME (Less-is-More) is parallel/concurrent programming environment based on C. Internally, it uses XML technology to describe tasks and their dependencies. Externally, it offers the ANSI C99 programming as well as a set of visually-oriented interfaces.
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Get full visibility and control over your tasks and projects with Wrike.Wrike offers world-class features that empower cross-functional, distributed, or growing teams take their projects from the initial request stage all the way to tracking work progress and reporting results.
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The CodeTime platform covers every aspect of parallel software from authoring, through distribution, to run-time. Its goals are: high programmer productivity; write once, run high performance anywhere; and wide acceptance.
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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.
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Brook is an ANSI C like general purpose stream programming language and is designed to incorporate the ideas of data parallel computing and arithmetic intensity into a familiar, efficient language. Has OpenMP CPU, OpenGL, DirectX 9 and AMD CTM backends.
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