Parallel Programming I

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Related lectures (32)

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Parallel Computing: Principles and OpenMP

Covers the principles of parallel computing and introduces OpenMP for creating concurrent code from serial code.

Parallelism: Programming and Performance

Explores parallelism in programming, emphasizing trade-offs between programmability and performance, and introduces shared memory parallel programming using OpenMP.

Principles of Parallel Computing: OpenMP

Explores the principles of parallel computing, focusing on OpenMP as a tool for creating concurrent code from serial code.

Principles of Parallelism

Covers the basics of parallelism, including physical examples, historical context, multicore era, and parallel collections in Scala.

Parallel Programming: Fundamentals

Covers the basics of parallel programming, including exploiting parallelism in algorithms and the importance of avoiding race conditions.

Task Parallelism and Explicit Communication

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

Threads: Concurrency and Parallelism in Computer Systems

Covers the thread abstraction in computer systems, focusing on concurrency, parallelism, and the management of threads using the POSIX API.

Concurrency and Parallelism: Visibility

Explores visibility in concurrency, memory models, shared memory, and hardware optimizations.

Synchronization: Hardware Implementation

Explores hardware synchronization methods, including locks, barriers, and critical sections in parallel computing.

Memory Consistency Models: Performance Impact and Parallel Computing

Covers memory consistency models, parallel computing, atomic subroutines, GPU architecture, and multithreading.