With the increasing computational complexity of cloud auditing and other data-intensive analysis applications, there is a growing need for computing platforms that can handle massive data sets and perform rapid analysis. These needs are met by systems with accelerators, such as Graphics Processing Units (GPUs), that can perform data analysis with a high level of parallelism employing tools like Hadoop MapReduce to handle massively parallel computing jobs. Applying GPUs to general purpose processing is known as GPGPU. This chapter uses an introductory approach to cover the basics of GPUs and GPGPU computing and their application to cloud computing and handling of large data sets. The main aim is to give the reader a broad background on how GPGPUs are used and their contribution to advances in cloud auditing.
CITATION STYLE
Ross, V. W., & Leeser, M. E. (2013). GPGPU computing for cloud auditing. In High Performance Cloud Auditing and Applications (Vol. 9781461432968, pp. 259–282). Springer New York. https://doi.org/10.1007/978-1-4614-3296-8_10
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