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In this paper, we propose an OpenCL framework for heterogeneous CPU/GPU clusters, and show that the framework achieves both high performance and ease of programming. The framework provides an illusion of a single system for the user. It allows the application to utilize multiple heterogeneous compute devices, such as multicore CPUs and GPUs, in a remote node as if they were in a local node. No communication API, such as the MPI library, is required in the application source. We implement the OpenCL framework and evaluate its performance on a heterogeneous CPU/GPU cluster that consists of one host node and nine compute nodes using eleven OpenCL benchmark applications.

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IMPORTANCE Subungual melanoma in situ (SMIS) is a malignant neoplasm that requires early diagnosis and complete surgical excision; however, little is known about the usefulness of the detailed dermoscopic features of longitudinal melanonychia (LM) to predict the diagnosis of SMIS. OBJECTIVES To investigate the characteristic dermoscopic findings of SMIS and to establish a predictive scoring model for the diagnosis of SMIS in patients with adult-onset LM affecting a single digit.