Data parallelism

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Related lectures (31)

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Introduction to Concurrency

Covers the basics of concurrency, its importance, and how to write concurrent programs.

Memory Models: Visibility and Semantics

Explains the Java Memory Model and thread start semantics for concurrent programs.

Dynamic Scheduling: Extending Pipelining for Parallelism

Delves into dynamic scheduling to enhance pipelining and enable out-of-order execution for improved performance.

Concurrency and Parallelism: Queue

Explores thread safety, synchronization, and concurrent collections in Scala, focusing on a lock-free concurrent queue implementation.

Pipelining: Enhancing Computer Architecture Performance

Covers pipelining in computer architecture, focusing on its role in enhancing performance through instruction-level parallelism and addressing associated challenges.

Dining Philosophers Problem

Discusses algorithms to prevent starvation and maximize philosophers eating simultaneously.

GPUs: Introduction to CUDA

Introduces the basics of GPUs, CUDA programming, and thread synchronization for parallel computing applications.

GPU Introduction: Performance and Programming

Explores the motivation and advantages of using GPUs for computation, focusing on their performance and programming through CUDA.

Task Parallelism and Explicit Communication

Explores task parallelism, explicit communication, and synchronization primitives for efficient parallel programming.

Data-Parallel Operations: Part 1

Explores data-parallel operations in Scala, converting collections, implementing sum, and examining fold operations.