About the Book:
The book presents state-of-the-art research, methodologies, and applications of high performance computing for big data applications. It covers fundamental issues in Big Data research, including emerging high performance architectures for data-intensive applications, novel efficient analytical strategies to boost data processing, and cutting-edge applications in diverse fields, such as machine learning, finance, life sciences, and neuromorphic engineering.
Table of Contents
Chapter 1 ◾ Dataflow Model for Cloud Computing Frameworks in Big DataChapter 2 ◾ Design of a Processor Core Customized for Stencil ComputationChapter 3 ◾ Electromigration Alleviation Techniques for 3D Integrated CircuitsChapter 4 ◾ A 3D Hybrid Cache Design for CMP Architecture for Data-Intensive ApplicationsChapter 5 ◾ Matrix Factorization for Drug–Target Interaction PredictionChapter 6 ◾ Overview of Neural Network AcceleratorsChapter 7 ◾ Acceleration for Recommendation Algorithms in Data Mining
Chapter 8 ◾ Deep Learning Accelerators
Chapter 9 ◾ Recent Advances for Neural Networks Accelerators and OptimizationsChapter 10 ◾ Accelerators for Clustering Applications in Machine Learning
Chapter 11 ◾ Accelerators for Classification Algorithms in Machine Learning
Chapter 12 ◾ Accelerators for Big Data Genome Sequencing
