Computational Mathematics: Models, Methods, and Analysis with MATLAB and MPI is a unique book covering the concepts and techniques at the core of computational science.
Computational Mathematics: Models, Methods, and Analysis with MATLAB and MPI is a unique book covering the concepts and techniques at the core of computational science.
Machine learning is a dynamic and rapidly expanding field focused on creating algorithms that empower computers to recognize patterns, make predictions and continually enhance performance.
Real-time systems are of importance to a large number of university laboratories and research institutes worldwide, and without the proper integration of real-time into distributed computing, institutions simply could not function.
This is one of the first parallel computing books to focus exclusively on parallel data structures, algorithms, software tools, and applications in data science.
Gain Critical Insight into the Parallel I/O EcosystemParallel I/O is an integral component of modern high performance computing (HPC), especially in storing and processing very large datasets to facilitate scientific discovery.
Visualization and analysis tools, techniques, and algorithms have undergone a rapid evolution in recent decades to accommodate explosive growth in data size and complexity and to exploit emerging multi- and many-core computational platforms.
New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data.
The hybrid/heterogeneous nature of future microprocessors and large high-performance computing systems will result in a reliance on two major types of components: multicore/manycore central processing units and special purpose hardware/massively parallel accelerators.
New sequencing technologies have broken many experimental barriers to genome scale sequencing, leading to the extraction of huge quantities of sequence data.
With multicore processors now in every computer, server, and embedded device, the need for cost-effective, reliable parallel software has never been greater.
A Thorough Overview of the Next Generation in ComputingPoised to follow in the footsteps of the Internet, grid computing is on the verge of becoming more robust and accessible to the public in the near future.
Solutions for Time-Critical Remote Sensing ApplicationsThe recent use of latest-generation sensors in airborne and satellite platforms is producing a nearly continual stream of high-dimensional data, which, in turn, is creating new processing challenges.
Designed for introductory parallel computing courses at the advanced undergraduate or beginning graduate level, Elements of Parallel Computing presents the fundamental concepts of parallel computing not from the point of view of hardware, but from a more abstract view of algorithmic and implementation patterns.
Designed for introductory parallel computing courses at the advanced undergraduate or beginning graduate level, Elements of Parallel Computing presents the fundamental concepts of parallel computing not from the point of view of hardware, but from a more abstract view of algorithmic and implementation patterns.
High-Performance Computing for Big Data: Methodologies and Applications explores 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, life science, neural networks, and neuromorphic engineering.
Multigrid methods are among the most efficient iterative methods for the solution of linear systems which arise in many large scale scientific calculations.
Multigrid methods are among the most efficient iterative methods for the solution of linear systems which arise in many large scale scientific calculations.
In view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems.
In view of the growing presence and popularity of multicore and manycore processors, accelerators, and coprocessors, as well as clusters using such computing devices, the development of efficient parallel applications has become a key challenge to be able to exploit the performance of such systems.
Use the GPU Successfully in Your Radiotherapy PracticeWith its high processing power, cost-effectiveness, and easy deployment, access, and maintenance, the graphics processing unit (GPU) has increasingly been used to tackle problems in the medical physics field, ranging from computed tomography reconstruction to Monte Carlo radiation transport simulation.
Parallel Computing Architectures and APIs: IoT Big Data Stream Processing commences from the point high-performance uniprocessors were becoming increasingly complex, expensive, and power-hungry.
Parallel Computing Architectures and APIs: IoT Big Data Stream Processing commences from the point high-performance uniprocessors were becoming increasingly complex, expensive, and power-hungry.
Addresses innovations in technology relating to the energy efficiency of a wide variety of contemporary computer systems and networks With concerns about global energy consumption at an all-time high, improving computer networks energy efficiency is becoming an increasingly important topic.
Addresses innovations in technology relating to the energy efficiency of a wide variety of contemporary computer systems and networks With concerns about global energy consumption at an all-time high, improving computer networks energy efficiency is becoming an increasingly important topic.
Parallel Scientific Computing Scientific computing has become an indispensable tool in numerous fields, such as physics, mechanics, biology, finance and industry.
This book assumes familiarity with threads (in a language such as Ada, C#, or Java) and introduces the entity-life modeling (ELM) design approach for certain kinds of multithreaded software.
This book will serve as a guide in understanding workflow scheduling techniques on computing systems such as Cluster, Supercomputers, Grid computing, Cloud computing, Edge computing, Fog computing, and the practical realization of such methods.
This book will serve as a guide in understanding workflow scheduling techniques on computing systems such as Cluster, Supercomputers, Grid computing, Cloud computing, Edge computing, Fog computing, and the practical realization of such methods.
Parallel Computing: Methods, Algorithms and Applications presents a collection of original papers presented at the international meeting on parallel processing, methods, algorithms, and applications at Verona, Italy in September 1989.
Parallel Computing: Methods, Algorithms and Applications presents a collection of original papers presented at the international meeting on parallel processing, methods, algorithms, and applications at Verona, Italy in September 1989.
There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools.
