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dc.contributor.advisorUddin, Dr. Jia
dc.contributor.authorAhmed, Rafid
dc.contributor.authorIslam, Md. Sazzadul
dc.date.accessioned2017-01-16T05:21:18Z
dc.date.available2017-01-16T05:21:18Z
dc.date.copyright2016
dc.date.issued2016-12-14
dc.identifier.otherID 13101209
dc.identifier.otherID 13201081
dc.identifier.urihttp://hdl.handle.net/10361/7599
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016.en_US
dc.descriptionCataloged from PDF version of thesis report.
dc.descriptionIncludes bibliographical references (page 29-31).
dc.description.abstractAs majority of the compression algorithms are implementations for CPU architecture, the primary focus of our work is to exploit the opportunities of GPU parallelism in audio compression. We present an implementation of Apples Lossless Audio Codec (ALAC) algorithm by using NVIDIA GPUs Compute Unified Device Architecture (CUDA) Framework. The core idea is to identify the areas where data parallelism can be applied and parallel programming model CUDA is used to execute the identified parallel components on Single Instruction Multiple Thread (SIMT) model of CUDA. The dataset is retrieved from European Broadcasting Union, Sound Quality Assessment Material (SQAM). Faster execution of the algorithm leads to execution time reduction when applied to audio coding for large audios. This paper also presents the reduction of power usage due to running the parallel components on GPU. Experimental results reveal that we achieve about 80-90% speedup through CUDA on the identified components over its CPU implementation while saving CPU power consumption.en_US
dc.description.statementofresponsibilityRafid Ahmed
dc.description.statementofresponsibilityMd. Sazzadul Islam
dc.format.extent31 pages
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.rightsBRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subjectApples Lossless Audio Codec (ALAC)en_US
dc.subjectNVIDIA GPUen_US
dc.subjectCompute Unified Device Architecture (CUDA)en_US
dc.subjectSound Quality Assessment Material (SQAM)en_US
dc.titleOptimizing apples lossless audio codec algorithm using NVIDIA CUDAen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, BRAC University
dc.description.degreeB. Computer Science and Engineering


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