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- W2793048312 abstract "Writing efficient general-purpose programs for Graphics Processing Units (GPU) is a complex task. In order to be able to program these processors efficiently, one has to understand their intricate architecture, memory subsystem as well as the interaction with the Central Processing Unit (CPU). The paper presents the GAP - an automatic parallelizer designed to translate sequential ANSI C code to parallel CUDA C programs. Developed and implemented compiler was tested on the series of ANSI C programs. The generated code performed very well, achieving significant speed-ups for the programs that expose high degree of data-parallelism. Thus, the idea of applying the automatic parallelization for generating the CUDA C code is feasible and realistic." @default.
- W2793048312 created "2018-03-29" @default.
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- W2793048312 date "2018-01-01" @default.
- W2793048312 modified "2023-09-23" @default.
- W2793048312 title "Automatic Parallelization of ANSI C to CUDA C Programs" @default.
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- W2793048312 doi "https://doi.org/10.1007/978-3-319-78024-5_40" @default.
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