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Title |
Parallel and distributed Data Mining Techniques: GPU Approach |
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Author |
Tagreed Alsulimani |
| Citation |
Vol. 24 No. 12 pp. 213-219 |
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Abstract |
Recent advancements in information technology have led to significant transformations in new processors such as Graphical Processing Units (GPUs) and multicore processors. These innovations are characterized by high-performance capabilities, marked by extensive parallelism and the integration of nonvolatile memory with hybrid storage hierarchies. Today, the task of uncovering relationships among various sets of items within vast and diverse datasets stands as a crucial challenge in information systems. Consequently, leveraging parallel architectures, including emerging processors, has emerged as a promising avenue for enhancing the performance of information systems. In this paper, we present a comprehensive survey of diverse techniques and solutions employed in the parallel and distributed data mining solutions. We delve into the rationale behind and the hurdles associated with the utilization of parallel processors such as multicore CPUs and GPUs, as well as distributed technologies. |
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Keywords |
Information system, distributed; parallel, GPU; data mining |
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