What is parallel computing?

Parallel computing is the design, study, and process of using algorithms to make multiple computers solve computational problems simultaneously. In parallel computing, problems are split up into several parts for more than two computers to work on at the same time. These parts each have their own set of instructions that are executed on multiple central processing units (CPUs). Parallel computing speeds up problem-solving in computational learning. Previously, most computations were done individually by software written for use on a single computer with one CPU. This meant that only one instruction could be executed at any time.

Why is it important to learn about parallel computing?

It's important to learn about parallel computing because it is the primary system used by programmers today to increase computation power for faster application problem solving and processing power. From multi-core personal computers to supercomputers, parallel computing is what is driving the core processing power. A processor is the computing power that drives your phone, laptop, and tablet. With more power in the processor, applications will run faster and better on your mobile device. Even smartphones are using multicore processing power, with some up to four and eight cores. Parallel computing helps to make this possible. This alone makes parallel computing worth knowing about for its current device applications and also its growing importance into the future.

What career opportunities can arise from learning parallel computing?

Learning parallel computing can bring you into careers as a parallel programming architect, a software engineer, or a high performance computing engineer. Many companies are looking for computing talents who can deliver and innovate in the graphics and parallel computing fields. Companies are continually looking to develop new parallel programming models for their GPU architecture. This is where learning about parallel computing can help you to succeed. By gaining new knowledge for creating new infrastructures and new architectures in parallel computing, you can play a part in advancing the state-of-the-art graphics performance in parallel programming models.

How can taking online courses help me learn about parallel computing?

When you take online courses about parallel computing, you will understand programming, software development, and computational power more clearly. You will study topics like data-parallel programs, how to express the functions of common parallel algorithms, and how to write and use parallel code in programs that use parallel collections to achieve higher computational performance. In these courses, industry experts will teach you not just how parallel computing works in relation to modern GPU architecture, but also how you can use your knowledge base to advance your careers in our increasingly digital world.

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128 results for "parallel computing"

University of Colorado Boulder
Introduction to High-Performance and Parallel Computing
Skills you'll gain: Data Analysis, Computer Programming, Programming Principles, Software Testing, Machine Learning, Computer Programming Tools, Computer Architecture, Theoretical Computer Science, Software Engineering, Software Architecture, Distributed Computing Architecture, Computational Thinking
3.1
(54 reviews)
Beginner · Course
Rice University
Parallel, Concurrent, and Distributed Programming in Java
Skills you'll gain: Algorithms, Computational Thinking, Computer Architecture, Computer Programming, Data Management, Data Structures, Distributed Computing Architecture, Java Programming, Mobile Development, Other Programming Languages, Programming Principles, Software Architecture, Software Engineering, Theoretical Computer Science, Web Development
4.6
(1.5k reviews)
Intermediate · Specialization
Free
Ludwig-Maximilians-Universität München (LMU)
Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python
Skills you'll gain: Strategy and Operations, Computer Programming, Applied Mathematics, Analysis, Operations Research, Mathematical Theory & Analysis, Research and Design, Theoretical Computer Science, Relative Change And Difference, Differential Equations, Mathematics, Computer Graphic Techniques, Calculus, Computer Graphics, Computational Thinking
4.7
(295 reviews)
Intermediate · Course
École Polytechnique Fédérale de Lausanne
Functional Programming in Scala
Skills you'll gain: Algebra, Apache, Apache Spark, Big Data, Computer Graphics, Computer Programming, Computer Programming Tools, Data Analysis, Data Management, Data Structures, Data Visualization, Functional Programming, Mathematics, Other Programming Languages, Programming Principles, Software Engineering, Theoretical Computer Science
4.7
(10.4k reviews)
Intermediate · Specialization
IBM
Advanced Data Science with IBM
Skills you'll gain: Algorithms, Apache, Apache Spark, Applied Machine Learning, Artificial Neural Networks, Basic Descriptive Statistics, Bayesian Statistics, Big Data, Change Management, Cloud Computing, Computer Architecture, Computer Graphic Techniques, Computer Graphics, Computer Programming, Computer Vision, Correlation And Dependence, Data Analysis, Data Management, Data Model, Data Structures, Data Visualization, Deep Learning, Dimensionality Reduction, Distributed Computing Architecture, Econometrics, Estimation, Experiment, General Statistics, IBM Cloud, Leadership and Management, Machine Learning, Machine Learning Algorithms, Mathematics, Natural Language Processing, Probability & Statistics, Probability Distribution, Programming Principles, Python Programming, Regression, Signal Processing, Statistical Machine Learning, Statistical Programming, Statistical Visualization, Strategy and Operations, Theoretical Computer Science
4.3
(2.9k reviews)
Advanced · Specialization
IBM
Fundamentals of Scalable Data Science
Skills you'll gain: Data Analysis, Machine Learning, Probability & Statistics, Basic Descriptive Statistics, Data Visualization, Apache Spark, Computer Programming, Apache, IBM Cloud, Data Management, Big Data, Programming Principles, General Statistics, Cloud Computing, Mathematics, Computer Architecture, Correlation And Dependence, Dimensionality Reduction, Statistical Programming, Distributed Computing Architecture, Probability Distribution, Statistical Visualization
4.3
(2k reviews)
Beginner · Course
University of Pennsylvania
Master of Computer and Information Technology
Skills you'll gain: Computer Programming, Data Structures, Mobile Development, Strategy and Operations, Machine Learning, Theoretical Computer Science, Probability & Statistics, Operating Systems, Mathematics, Mathematical Theory & Analysis, Databases, Computer Vision, Graph Theory, Software Engineering, Data Management, Software Testing, Python Programming, Computer Architecture, Statistical Programming, Linear Algebra, General Statistics, Cryptography, Algorithms, SQL, Database Design
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Degree

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introduction to high-performance and parallel computing

In summary, here are 10 of our most popular parallel computing courses

Introduction to High-Performance and Parallel Computing: University of Colorado Boulder
Parallel, Concurrent, and Distributed Programming in Java: Rice University
Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python: Ludwig-Maximilians-Universität München (LMU)
Master of Computer Science: University of Illinois at Urbana-Champaign
Functional Programming in Scala: École Polytechnique Fédérale de Lausanne
Advanced Data Science with IBM: IBM
Introduction to Big Data with Spark and Hadoop: IBM
Fundamentals of Scalable Data Science: IBM
Scalable Machine Learning on Big Data using Apache Spark: IBM
Big Data Analysis with Scala and Spark: École Polytechnique Fédérale de Lausanne

Skills you can learn in Software Development

Programming Language (34)

Google (25)

Computer Program (21)

Software Testing (21)

Web (19)

Google Cloud Platform (18)

Application Programming Interfaces (17)

Data Structure (16)

Problem Solving (14)

Object-oriented Programming (13)

Kubernetes (10)

List & Label (10)

Frequently Asked Questions about Parallel Computing

Parallel computing is the design, study, and process of using algorithms to make multiple computers solve computational problems simultaneously. In parallel computing, problems are split up into several parts for more than two computers to work on at the same time. These parts each have their own set of instructions that are executed on multiple central processing units (CPUs).
Parallel computing speeds up problem-solving in computational learning. Previously, most computations were done individually by software written for use on a single computer with one CPU. This meant that only one instruction could be executed at any time.‎
It's important to learn about parallel computing because it is the primary system used by programmers today to increase computation power for faster application problem solving and processing power. From multi-core personal computers to supercomputers, parallel computing is what is driving the core processing power.
A processor is the computing power that drives your phone, laptop, and tablet. With more power in the processor, applications will run faster and better on your mobile device. Even smartphones are using multicore processing power, with some up to four and eight cores. Parallel computing helps to make this possible. This alone makes parallel computing worth knowing about for its current device applications and also its growing importance into the future.‎
Learning parallel computing can bring you into careers as a parallel programming architect, a software engineer, or a high performance computing engineer. Many companies are looking for computing talents who can deliver and innovate in the graphics and parallel computing fields.
Companies are continually looking to develop new parallel programming models for their GPU architecture. This is where learning about parallel computing can help you to succeed. By gaining new knowledge for creating new infrastructures and new architectures in parallel computing, you can play a part in advancing the state-of-the-art graphics performance in parallel programming models.‎
When you take online courses about parallel computing, you will understand programming, software development, and computational power more clearly. You will study topics like data-parallel programs, how to express the functions of common parallel algorithms, and how to write and use parallel code in programs that use parallel collections to achieve higher computational performance. In these courses, industry experts will teach you not just how parallel computing works in relation to modern GPU architecture, but also how you can use your knowledge base to advance your careers in our increasingly digital world.‎

This FAQ content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.

Filter by

128 results for "parallel computing"

Introduction to High-Performance and Parallel Computing

Parallel, Concurrent, and Distributed Programming in Java

Computers, Waves, Simulations: A Practical Introduction to Numerical Methods using Python

Master of Computer Science

Functional Programming in Scala

Advanced Data Science with IBM

Introduction to Big Data with Spark and Hadoop

Fundamentals of Scalable Data Science

Scalable Machine Learning on Big Data using Apache Spark

Big Data Analysis with Scala and Spark

Create Your First Multithreaded Application in Java

Master of Computer and Information Technology

Searches related to parallel computing

In summary, here are 10 of our most popular parallel computing courses

Skills you can learn in Software Development

Frequently Asked Questions about Parallel Computing

What is parallel computing?‎

Why is it important to learn about parallel computing?‎

What career opportunities can arise from learning parallel computing?‎

How can taking online courses help me learn about parallel computing?‎

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Filter by

128 results for "parallel computing"

Searches related to parallel computing

In summary, here are 10 of our most popular parallel computing courses

Skills you can learn in Software Development

Frequently Asked Questions about Parallel Computing

What is parallel computing?‎

Why is it important to learn about parallel computing?‎

What career opportunities can arise from learning parallel computing?‎

How can taking online courses help me learn about parallel computing?‎

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