Sangwhan Moon

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Solid State Drive (SSD) cost-per-bit continues to decrease. Consequently, system architects increasingly consider replacing Hard Disk Drives (HDDs) with SSDs to accelerate Hadoop MapReduce processing. When attempting this, system architects usually realize that SSD characteristics and today's Hadoop framework exhibit mismatches that impede indiscriminate(More)
Solid-state drives (SSDs) have become promising storage components to serve large I/O demands in modern storage systems. Enterprise class (high-end) SSDs are faster and more resilient than client class (low-end) SSDs but they are expensive to be deployed in large scale storage systems. It is an attractive and practical alternative to exploit the high-end(More)
While flash memory is receiving significant attention because of many attractive properties, concerns about write endurance delay the wider deployment of the flash memory. This paper analyzes the effectiveness of protection schemes designed for flash memory, such as ECC and scrubbing. The bit error rate of flash memory is a function of the number of(More)
Solid-state drives (SSDs) are an attractive alternative to hard disk drives (HDDs) to accelerate the Hadoop MapReduce Framework. However, the SSD characteristics and today’s Hadoop framework exhibit mismatches that impede indiscriminate SSD integration. This paper explores how to optimize a Hadoop MapReduce Framework with SSDs in terms of performance, cost,(More)
Feature representation plays a key role to the success of an image retrieval system. In this paper, a comparative study over the effectiveness of several features for content-based image search is presented. This study covers across several conventional features as well as convolutional neural networks (CNN) features, which are introduced recently into(More)
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