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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 cove...
Dramatically accelerate the building process of complex models using PyTorch to extract the best performance from any computing environment Key Features Reduce the model-building time by applying optimization techniques and approaches Harness the computing power of multiple devices and machines to boost the training process Focus on model quality by quickly evaluating different model configurations Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThis book, written by an HPC expert with over 25 years of experience, guides you through enhancing model training performance using PyTorch. Here you’ll learn how model complexity impacts training time and discover pe...
This book constitutes the refereed proceedings of the 19th Symposium on High Performance Computing System, WSCAD 2018, held in São Paulo, Brazil, in October 2018. The 12 revised full papers presented were carefully reviewed and selected out of 61 submissions. The papers included in this book are organized according to the following topics: cloud computing; performance; processors and memory architectures; power and energy.
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This book constitutes the proceedings of the 27th International Conference on Parallel and Distributed Computing, Euro-Par 2021, held in Lisbon, Portugal, in August 2021. The conference was held virtually due to the COVID-19 pandemic. The 38 full papers presented in this volume were carefully reviewed and selected from 136 submissions. They deal with parallel and distributed computing in general, focusing on compilers, tools and environments; performance and power modeling, prediction and evaluation; scheduling and load balancing; data management, analytics and machine learning; cluster, cloud and edge computing; theory and algorithms for parallel and distributed processing; parallel and distributed programming, interfaces, and languages; parallel numerical methods and applications; and high performance architecture and accelerators.