Search Results for "cuda"

...Supports GCC, Clang, MSVC (Microsoft Visual C++) and other similar compilers. Works on Linux, macOS, other Unix-like operating systems and Windows. Understands C, C++, assembler, CUDA, Objective-C and Objective-C++. Supports secondary storage over HTTP (e.g. using Nginx or Google Cloud Storage), Redis or local filesystem, optionally sharding data onto a server cluster. Supports fast "direct" and "depend" modes that don't rely on using the preprocessor. Supports compression using Zstandard. Checksums cache content using XXH3 to detect data corruption. ...

HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages.

hiCUDA is a directive-based abstraction that simplifies CUDA programming. This project aims to develop a source-to-source compiler, based on Open64, that translates a sequential program with hiCUDA directives into an equivalent CUDA program.

The Open64 Compiler and Tools site is dedicated to the continued development of the former SGI Pro64(TM) compiler for the IA64, x86, CUDA and MIPS architecture.

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.