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This book constitutes the proceedings of the Second Latin American Conference on High Performance Computing, CARLA 2015, a joint conference of the High-Performance Computing Latin America Community, HPCLATAM, and the Conferencia Latino Americana de Computación de Alto Rendimiento, CLCAR, held in Petrópolis, Brazil, in August 2015. The 11 papers presented in this volume were carefully reviewed and selected from 17 submissions. They were organized in topical sections named: grid and cloud computing; GPU & MIC Computing: methods, libraries and applications; and scientific computing applications. .

Computer Science --- Electrical Engineering --- Engineering & Applied Sciences --- Electrical & Computer Engineering --- Computer science. --- Computer hardware. --- Computer organization. --- Computer Science. --- Computer Hardware. --- Computer Systems Organization and Communication Networks. --- Organization, Computer --- Electronic digital computers --- Informatics --- Science --- Computer network architectures. --- Architectures, Computer network --- Network architectures, Computer --- Computer architecture --- High performance computing

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This book brings a thorough explanation on the path needed to use cloud computing technologies to run High-Performance Computing (HPC) applications. Besides presenting the motivation behind moving HPC applications to the cloud, it covers both essential and advanced issues on this topic such as deploying HPC applications and infrastructures, designing cloud-friendly HPC applications, and optimizing a provisioned cloud infrastructure to run this family of applications. Additionally, this book also describes the best practices to maintain and keep running HPC applications in the cloud by employing fault tolerance techniques and avoiding resource wastage. To give practical meaning to topics covered in this book, it brings some case studies where HPC applications, used in relevant scientific areas like Bioinformatics and Oil and Gas industry were moved to the cloud. Moreover, it also discusses how to train deep learning models in the cloud elucidating the key components and aspects necessary to train these models via different types of services offered by cloud providers. Despite the vast bibliography about cloud computing and HPC, to the best of our knowledge, no existing manuscript has comprehensively covered these topics and discussed the steps, methods and strategies to execute HPC applications in clouds. Therefore, we believe this title is useful for IT professionals and students and researchers interested in cutting-edge technologies, concepts, and insights focusing on the use of cloud technologies to run HPC applications.

Cloud Computing. --- Big data. --- Machine learning. --- Big Data. --- Machine Learning. --- Learning, Machine --- Artificial intelligence --- Machine theory --- Data sets, Large --- Large data sets --- Data sets --- Electronic data processing --- Web services --- Distributed processing