Yoonsung Nam

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In this paper, we propose a fully automatic dynamic scratch-pad memory (SPM) management technique for instructions. Our technique loads required code segments into the SPM on demand at runtime. Our approach is based on postpass analysis and optimization techniques, and it handles the whole program, including libraries. The code mapping is determined by(More)
With the proliferation of cloud computing and virtual machine technologies, MapReduce applications are increasingly deployed in clouds to leverage the full potential of cloud computing environments. However, the MapReduce, which is generally used for processing large amount of data, suffers from the I/O virtualization overheads and resource competitions(More)
With advance of cloud computing technologies, there have been more diverse and heterogeneous workloads running on cloud datacenters. As more and more workloads run on the datacenters, the contention for the limited shared resources may increase, which can make the management of the resources difficult, often leading to low resource utilization. For(More)
With the advances of cloud computing and virtualization technologies, running MapReduce applications over clouds has been attracting more and more attention in recent years. However, as a fundamental problem, the performance of MapReduce applications can sometimes be severely degraded due to the overheads from I/O virtualization and resource competitions(More)
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