This textbook is a concise introduction to the basic toolbox of structures that allow efficient organization and retrieval of data, key algorithms for problems on graphs, and generic techniques for modeling, understanding, and solving algorithmic problems.

Aug 29, 2021 · Serial algorithms are algorithms that are not parallel algorithms (i.e. it doesn't allow parallel processing) For example if you want to find maximum element of an array, you can do it as follow: a = [2, 4, 3, 2] ans = -Infinity For i From 0 To Len(a) - 1 ans = Max(ans, a[i]) Return ans

Data-Parallel Algorithms • Efficient algorithms require efficient building blocks • Five data-parallel building blocks • Map • Gather & Scatter • Reduce • Scan • Sort • Advanced data structures: • Sparse matrices • Hash tables • Task queues

principles for parallel algorithms that can be applied in essentially all parallel systems, from the data center to the multicore chips on mobile phones. We will learn to think about parallelism at a high-level, learning general techniques for designing parallel algorithms and data structures, and learning how to approximately analyze their costs.

In this article we describe a series of algorithms ap- propriate for fine-grained parallel computers with general communications. We call these algorithms data parallel algorithms because their parallelism comes from simultaneous operations across large sets of data, rather than from multiple threads of control.

– Understand the data structures and their trade- offs – Rigorously analyze the algorithms that use them (math!) – Learn how to pick “the right thing for the job”

We cover techniques that play a key role in the design of most algorithms and data structures, including: collections (sets, sequences, priority queues, ...), divide-and-conquer, contraction, the greedy method, balanced trees, hashing, sparse matrices, and dynamic programming.

Learn about the essential structure of parallel algorithms, including key components and their significance in enhancing performance and efficiency. Discover the key elements of parallel algorithm structures and how they contribute to better performance in computing.

Directed graphs are weakly connected if there is a path between any two vertices, ignoring direction. A complete directed graph has a directed edge between every pair of vertices. (Again, complete = fully connected.)

We have made sure that we present algorithms in a modern way, including explicitly formulated invariants. We also discuss important further aspects, such as algorithm engineering, memory hierarchies, algorithm libraries, and certifying algorithms.