Think about making breakfast. You could do one thing at a time - boil water, then toast bread, then fry eggs. This would take forever. But smart people do multiple things at once - while water is ...

As modern .NET applications grow increasingly reliant on concurrency to deliver responsive, scalable experiences, mastering asynchronous and parallel programming has become essential for every serious ...

NVIDIA’s CUDA is a general purpose parallel computing platform and programming model that accelerates deep learning and other compute-intensive apps by taking advantage of the parallel processing ...

Parallel programming lets software run multiple tasks at the same time, speeding up performance for complex jobs. It's best used when the work is intensive and can be divided into independent pieces, ...

A comprehensive collection of CUDA C++ examples demonstrating fundamental to advanced GPU acceleration techniques, focusing on memory management, kernel optimization, and high-performance libraries.

Take advantage of lock-free, thread-safe implementations in C# to maximize the throughput of your .NET or .NET Core applications. Parallelism is the ability to have parallel execution of tasks on ...

├── notes/ # Theoretical concepts and explanations │ ├── 01_introduction/ # Basics of parallel computing │ ├── 02_gpu_architecture/ # GPU hardware fundamentals │ ├── 03_cuda_basics/ # CUDA programming ...

This course focuses on developing and optimizing applications software on massively parallel graphics processing units (GPUs). Such processing units routinely come with hundreds to thousands of cores ...

A hands-on introduction to parallel programming and optimizations for 1000+ core GPU processors, their architecture, the CUDA programming model, and performance analysis. Students implement various ...