I/O-efficient algorithms from Coursera

I/O-efficient algorithms, also known as external memory algorithms or cache-oblivious algorithms, are a class of algorithms designed to efficiently process data that is too large to fit entirely in the main memory (RAM) of a computer. These algorithms are particularly useful when dealing with massive datasets, such as those found in large-scale data processing, database management, and file systems.

Operations on data become more expensive when the data item is located higher in the memory hierarchy. An operation on data in CPU registers is roughly a million times faster than an operation on a data item that is located in external memory that needs to be fetched first. These data fetches are also called I/O operations and need to be taken into account during the design of an algorithm. The goal of this course is to become familiar with important algorithmic concepts and techniques needed to effectively deal with such problems. We will work with a simplified memory hierarchy, but the notions extend naturally to more realistic models.

Prerequisites:

In order to successfully take this course, you should already have a basic knowledge of algorithms and mathematics. Here's a short list of what you are supposed to know:

- O-notation, Ω-notation, Θ-notation; how to analyze algorithms

- Basic calculus: manipulating summations, solving recurrences, working with logarithms, etc.

- Basic probability theory: events, probability distributions, random variables, expected values etc.

- Basic data structures: linked lists, stacks, queues, heaps

- (Balanced) binary search trees

- Basic sorting algorithms, for example MergeSort, InsertionSort, QuickSort

- Graph terminology, representations of graphs (adjacency lists and adjacency matrix), basic graph algorithms (BFS, DFS, topological sort, shortest paths)

The material for this course is based on the course notes that can be found under the resources tab. We will not cover everything from the course notes. The course notes are there both for students who did not fully understand the lectures as well as for students who would like to dive deeper into the topics.

The video lectures contain a few very minor mistakes. A list of these mistakes can be found under resources. If you think you found an error, report a problem by clicking the square flag at the bottom of the lecture or quiz where you found the error.

What's inside

Syllabus

Introduction

In this module we give an introduction to the course I/O-efficient algorithms. We discuss the so-called I/O-model, which consists of an internal memory of limited size, an external memory of unlimited size and where data transfer between these two happens in blocks of a given size. We give a simple example showing that the actual running time of an algorithm working on data in external memory is greatly influenced by its I/O-behavior. Finally, we discuss the basics of analyzing algorithms in the I/O-model.

Designing cache-aware and cache-oblivious algorithms

In this module we discuss two techniques to design I/O-efficient algorithms, using the matrix-transposition problem as a running example. The first technique is a "tile-based" approach and leads to a cache-aware algorithm. The second technique uses a recursive approach and leads to a cache-oblivious algorithm.

Replacement Policies

When we want to read something from external memory while the internal memory is full we need to make room by evicting a block from internal memory. The block which should be evicted is decided by the replacement policy. In this module we introduce LRU and some other some well-known replacement policies, and investigate the I/O-efficiency of LRU compared to an optimal replacement policy.

I/O-efficient sorting

In this module we analyze the I/O-efficiency of MergeSort and discuss how to adapt it to make it more I/O-efficient.

I/O-efficient data structures

In this module we introduce some I/O-efficient data structures: B-trees and buffer trees, and an I/O-efficient priority queue based on buffer trees.

Time-Forward Processing

In this module we discuss time-forward processing, a technique that can be used to evaluate so-called local functions on a directed acyclic graph.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers techniques and algorithms to process large datasets that don't fit in memory, widely usable for those handling big data

Provides a simplified memory hierarchy concept which naturally extends to more realistic models for better understanding and implementation

Teaches both cache-aware and cache-oblivious algorithm design techniques, using the matrix-transposition problem as a running example for better comprehension

Introduces and investigates replacement policies such as LRU and explores their impact on the I/O-efficiency of algorithms

Examines various I/O-efficient data structures such as B-trees, buffer trees, and an I/O-efficient priority queue for practical utilization of the concepts

Prerequisites are essential for understanding the course material effectively

Reviews summary

Well-received i/o-efficient algorithms course

Learners say that I/O-efficient algorithms is a well-received and engaging course that provides a solid introduction to the subject. The lectures are clear and the problem sets are challenging. However, some learners found that the resource notes lacked depth and clarity, and that the quizzes were confusing at times.

Course has clear lectures.

"The lectures are clear."

Course has challenging problem sets.

"The problem-sets [are] challenging."

Course has confusing quizzes.

"The quizzes were a bit confusing at times."

Course has lacking resource notes.

"Resource notes lacked depth and clarity."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in I/O-efficient algorithms with these activities:

Review basic data structures and algorithms

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Reviewing basic data structures and algorithms will strengthen your foundational understanding of computer science, which is essential for success in this course.

Browse courses on Data Structures

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Review the concepts of arrays, linked lists, stacks, queues, and heaps.
Practice implementing these data structures in a programming language of your choice.
Review basic algorithms such as sorting algorithms and search algorithms.

Review calculus concepts

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Reviewing calculus concepts will strengthen your foundational understanding of mathematics, which is essential for success in this course.

Browse courses on Limits

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Review the definition of a limit and practice finding limits of functions.
Review the rules of differentiation and practice differentiating functions.
Review the rules of integration and practice integrating functions.

Watch video tutorials on I/O-efficient algorithms

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Watching video tutorials on I/O-efficient algorithms will help you understand the concepts and techniques presented in this course.

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Find video tutorials on I/O-efficient algorithms on platforms such as YouTube, Coursera, or edX.
Watch the tutorials and take notes on the key concepts.

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Attend a study group

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Attending a study group will provide you with the opportunity to discuss the course material with your peers and clarify any concepts that you may be struggling with.

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Find a study group or organize one with your classmates.
Meet regularly to discuss the course material, work on problems together, and quiz each other.

Start a project on I/O-efficient algorithms

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Starting a project on I/O-efficient algorithms will allow you to apply the concepts learned in this course to a practical problem.

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Identify a project idea that involves the implementation of I/O-efficient algorithms.
Create a project plan and timeline.
Start working on the project.

Practice applying I/O-efficient algorithms to solve problems

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Practicing applying I/O-efficient algorithms will help you develop the skills necessary to design and implement efficient algorithms for large datasets.

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Implement the matrix transposition algorithm and test its performance on different datasets.
Implement a merge sort algorithm and modify it to make it I/O-efficient.
Implement a binary search tree and modify it to make it I/O-efficient.

Create a compilation of resources on I/O-efficient algorithms

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Creating a compilation of resources on I/O-efficient algorithms will help you organize and easily access the materials you need to succeed in this course.

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Gather resources on I/O-efficient algorithms from various sources, such as textbooks, research papers, and online tutorials.
Organize the resources into a structured format, such as a document or website.
Make the compilation available to your classmates and other students.

Design and implement an I/O-efficient algorithm for a real-world problem

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Designing and implementing an I/O-efficient algorithm for a real-world problem will allow you to apply the concepts learned in this course to solve a practical problem.

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Identify a real-world problem that can be solved using I/O-efficient algorithms.
Design an I/O-efficient algorithm to solve the problem.
Implement the algorithm in a programming language of your choice.
Test the performance of the algorithm on a large dataset.
Write a report describing the problem, the algorithm, the implementation, and the results of the performance tests.

Career center

Learners who complete I/O-efficient algorithms will develop knowledge and skills that may be useful to these careers:

Algorithm Engineer

Algorithm Engineers are responsible for designing and implementing efficient algorithms for a variety of applications, such as data processing, optimization, and machine learning. This course may be useful to an Algorithm Engineer because it covers important concepts and techniques for designing and implementing cache-aware and cache-oblivious algorithms.

See salaries and explore the career path for Algorithm Engineer

Computer Scientist

Computer Scientists are involved in all aspects of computing, from theoretical research to the design and implementation of computer systems. This course may be useful to a Computer Scientist because it covers important concepts and techniques for designing and implementing efficient algorithms for processing large amounts of data.

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Professor

Professors are responsible for teaching and conducting research in their field of expertise. This course may be useful to a Professor because it provides a solid foundation in the design and analysis of I/O-efficient algorithms, which are important for teaching and conducting research in computer science.

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Researcher

Researchers are involved in a wide range of activities, from basic research to applied research and development. This course may be useful to a Researcher because it covers important concepts and techniques for designing and implementing efficient algorithms for processing large amounts of data, which is a common task in many research disciplines.

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Quantitative Analyst

Quantitative Analysts are responsible for developing and implementing mathematical and statistical models to analyze financial data. This course may be useful to a Quantitative Analyst because it provides a solid foundation in the design and analysis of I/O-efficient algorithms, which is important for developing and implementing efficient models for financial data analysis.

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Computer Architect

Computer Architects are responsible for designing the overall architecture of computer systems, including the hardware and software components. This course may be useful to a Computer Architect because it covers topics such as I/O-efficient algorithms and I/O-efficient data structures, which can help to improve the performance of computer systems.

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Risk Manager

Risk Managers are responsible for identifying, assessing, and managing risks within an organization. This course may be useful to a Risk Manager because it provides a solid foundation in the design and analysis of I/O-efficient algorithms, which is important for developing and implementing efficient models for risk assessment and management.

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Technical Writer

Technical Writers are responsible for writing documentation for a variety of technical products and services. This course may be useful to a Technical Writer because it provides a solid foundation in the design and analysis of I/O-efficient algorithms, which is important for writing clear and concise documentation for technical products and services.

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Hardware Engineer

Hardware Engineers are responsible for the design, development, and testing of computer hardware, including processors, memory, and storage devices. This course may be useful to a Hardware Engineer because it covers how to efficiently process data in external memory, which is important for designing high-performance computer systems.

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Systems Engineer

Systems Engineers are responsible for designing, implementing, and maintaining computer systems, including hardware and software. This course may be useful to a Systems Engineer because it covers topics such as I/O-efficient algorithms and I/O-efficient data structures, which can help to improve the performance of computer systems.

See salaries and explore the career path for Systems Engineer

Software Engineer

A Software Engineer is responsible for designing, developing, testing, and maintaining software systems. This course may be useful to a Software Engineer because it covers cache-aware and cache-oblivious algorithms, which can help to improve the performance of software applications. Additionally, the course covers I/O-efficient data structures, which can be useful for storing and managing data in a software system.

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Database Administrator

Database Administrators are responsible for the maintenance and performance of databases, ensuring that data is stored, organized, and retrievable. This course may be useful to a Database Administrator because it covers topics such as B-trees and buffer trees, which are used to organize and store data in a database.

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Data Scientist

A Data Scientist is responsible for collecting, cleaning, and analyzing data to help businesses make decisions. This can involve using statistical modeling, machine learning, and other techniques to find patterns and trends in data. This course may be useful for a Data Scientist because it provides a foundation in cache-aware and cache-oblivious algorithms, which can help to improve the efficiency of data processing.

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Data Engineer

A Data Engineer is responsible for building, testing, and maintaining big data pipelines. Data Engineers ensure that the data is processed, transformed, and accessible in a timely manner for Data Scientists and Analysts to use. This course may be useful for a Data Engineer because it discusses how to efficiently process data in external memory. Understanding how to approach and solve these problems can help a Data Engineer be more efficient in their work.

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Data Analyst

A Data Analyst takes large sets of data and uses various tools to clean the data, organize it, and interpret the results to provide insights to a company. This course may be useful to a Data Analyst because while this course primarily focuses on efficiently processing data in external memory, the techniques discussed here can be adapted to fit many other scenarios that a Data Analyst may encounter.

See salaries and explore the career path for Data Analyst