Learn IT - Books tags parallel

Practical Haskell: A Real World Guide to Programming

Apress, 2019

Get a practical, hands-on introduction to the Haskell language, its libraries and environment, and to the functional programming paradigm that is fast growing in importance in the software industry. This book contains excellent coverage of the Haskell ecosystem and supporting tools, include Cabal and Stack for managing projects,...

Optimizing Hadoop for MapReduce

Packt Publishing, 2014

This book is the perfect introduction to sophisticated concepts in MapReduce and will ensure you have the knowledge to optimize job performance. This is not an academic treatise; it's an example-driven tutorial for the real world.

Overview

Optimize your MapReduce job performance

Computer Graphics and Geometric Modelling: Implementation & Algorithms

Springer, 2005

Possibly the most comprehensive overview of computer graphics as seen in the context of geometric modelling, this two volume work covers implementation and theory in a thorough and systematic fashion. Computer Graphics and Geometric Modelling: Implementation and Algorithms, covers the computer graphics part of the field of geometric modelling and...

IPython Interactive Computing and Visualization Cookbook

Packt Publishing, 2014

Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science with Python

About This Book

Leverage the new features of the IPython notebook for interactive web-based big data analysis and visualization

Become an expert in high-performance...

Algorithms and Parallel Computing (Wiley Series on Parallel and Distributed Computing)

John Wiley & Sons, 2011

There is a software gap between hardware potential and the performance that can be attained using today ’ s software parallel program development tools. The tools need manual intervention by the programmer to parallelize the code. This book is intended to give the programmer the techniques necessary to explore parallelism in...

Handbook of Parallel Computing: Models, Algorithms and Applications (Chapman & Hall/Crc Computer & Information Science Series)

CRC Press, 2007

We live in an era in which parallel computing has become mainstream and very affordable. This is mainly because hardware costs have come down rapidly. With the advent of the Internet, we also experience the phenomenon of data explosion in every application of interest. Processing voluminous datasets is highly computation intensive. Parallel...

Hands-On Data Science with Anaconda: Utilize the right mix of tools to create high-performance data science applications

Packt Publishing, 2018

Develop, deploy, and streamline your data science projects with the most popular end-to-end platform, Anaconda

Key Features

Use Anaconda to find solutions for clustering, classification, and linear regression

Analyze your data efficiently with the most powerful data...

Learning Spark: Lightning-Fast Big Data Analysis

O'Reilly, 2015

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java,...

JavaScript Concurrency

Packt Publishing, 2015

About This Book

Apply the core principles of concurrency to both browser and server side development

Explore the latest tools and techniques at the forefront of concurrent programming, including JavaScript promises, web workers, and generators

Learn how concurrent and parallel programming...

Parallel Metaheuristics: A New Class of Algorithms

John Wiley & Sons, 2005

Solving complex optimization problems with parallelmetaheuristics

Parallel Metaheuristics brings together an international group ofexperts in parallelism and metaheuristics to provide a much-neededsynthesis of these two fields. Readers discover how metaheuristictechniques can provide useful and practical solutions for a...

Introduction to Parallel Computing, Second Edition

Addison Wesley, 2003

Increasingly, parallel processing is being seen as the only cost-effective method for the fast solution of computationally large and data-intensive problems. The emergence of inexpensive parallel computers such as commodity desktop multiprocessors and clusters of workstations or PCs has made such parallel methods generally...

C++ High Performance: Boost and optimize the performance of your C++17 code

Packt Publishing, 2018

Write code that scales across CPU registers, multi-core, and machine clusters

Key Features

Explore concurrent programming in C++
Identify memory management problems
Use SIMD and STL containers for performance improvement

Book...

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