- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- List of Contributors
- Preface
- Acknowledgments
- Part 1: Programming and Tools
- Chapter 1: Formal analysis techniques for reliable GPU programming: current solutions and call to action
- Chapter 2: SnuCL: A unified OpenCL framework for heterogeneous clusters
- Chapter 3: Thread communication and synchronization on massively parallel GPUs
- Chapter 4: Software-level task scheduling on GPUs
- Chapter 5: Data placement on GPUs
- Part 2: Algorithms and Applications
- Chapter 6: Biological sequence analysis on GPU
- Chapter 7: Graph algorithms on GPUs
- Chapter 8: GPU alignment of two and three sequences
- Chapter 9: Augmented Block Cimmino Distributed Algorithm for solving tridiagonal systems on GPU
- Chapter 10: GPU computing applied to linear and mixed-integer programming
- Chapter 11: GPU-accelerated shortest paths computations for planar graphs
- Chapter 12: GPU sorting algorithms
- Chapter 13: MPC: An effective floating-point compression algorithm for GPUs
- Chapter 14: Adaptive sparse matrix representation for efficient matrix-vector multiplication
- Part 3: Architecture and Performance
- Chapter 15: A framework for accelerating bottlenecks in GPU execution with assist warps
- Chapter 16: Accelerating GPU accelerators through neural algorithmic transformation
- Chapter 17: The need for heterogeneous network-on-chip architectures with GPGPUs: A case study with photonic interconnects
- Chapter 18: Accurately modeling GPGPU frequency scaling with the CRISP performance model
- Part 4: Power and Reliability
- Chapter 19: Energy and power considerations of GPUs
- Chapter 20: Architecting the last-level cache for GPUs using STT-MRAM nonvolatile memory
- Chapter 21: Power management of mobile GPUs
- Chapter 22: Advances in GPU reliability research
- Chapter 23: Addressing hardware reliability challenges in general-purpose GPUs
- Author Index
- Subject Index
Dedication
To my wife and son for their endless love and support.
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