... GPU-based Realtime Deformations using Trilinear Transformations Embedded in a Scene Graph. In: GRAPP 2010, pp. 246–253 (2010) 16. Binotto, A.P.D., Daniel, C., Weber, D., Kuijper, A., Stork, A., Pereira, C., Fellner, D.W.: Iterative SLE ...

... Iterative sle solvers over a cpu-gpu platform. In: 12th IEEE International Conference on High Performance Computing and Communications (HPCC), pp. 305–313. IEEE (2010) 2. Bergou, M., Mathur, S., Wardetzky, M., Grinspun, E.: TRACKS ...

The research conducted in this thesis provides a robust implementation of a preconditioned iterative linear solver on programmable graphic processing units (GPUs).

The tight integration of linear algebra methods with examples from machine learning differentiates this book from generic volumes on linear algebra.

This book examines and explains a variety of scientific programming models (programming models relevant to scientists) with an emphasis on how programming constructs map to different parts of the computer's architecture.

This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation.

This book integrates the core ideas of deep learning and its applications in bio engineering application domains, to be accessible to all scholars and academicians.

Backed by a number of tricks of the trade for training and optimizing deep learning models, this edition of Deep Learning with Python explains the best practices in taking these models to production with PyTorch.

This volume explores the connections between mathematical modeling, computational methods, and high performance computing, and how recent developments in these areas can help to solve complex problems in the natural sciences and engineering ...

This book provides the reader a unified, self-contained treatment, focusing on the practical issues, of how convex optimization can be used in multi-period trading.