Optimizing Parallel Reduction In Cuda To Reach GPU Peak Performance

Mahardito, Adityo and Suhendra, Adang and Hasta, Deni Tri Optimizing Parallel Reduction In Cuda To Reach GPU Peak Performance. Skripsi Program Studi Sistem Komputer. (Submitted)

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GPUs are massively multi threaded many core chips that have hundreds of cores and thousands of concurrent threads swith high performance and memory bandwidth. Now days, GPUs have already been used to accelerate some numerically intensive high performance computing applications in parallel not only used to graphic processing. This thesis aims primarily to demonstrate the programming model approaches that can be maximize the performance of GPUs. This is accomplished by a proof of maximum reach of bandwidth memory and get speed up from the GPU that used to process parallel computation. The programming environment that used is NVIDIA’s CUDA, it is parallel architecture and model for generalpurpose computing on a GPU.

Item Type: Article
Uncontrolled Keywords: Cuba;GPU Peak;Performance
Subjects: A General Works > AI Indexes (General)
Divisions: Fakultas Ilmu Komputer dan Teknologi Informasi > Program Studi Sistem Komputer
Depositing User: Mr Reza Chandra
Date Deposited: 28 Feb 2014 04:16
Last Modified: 28 Feb 2014 04:16
URI: http://repository.gunadarma.ac.id/id/eprint/722

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