It evolved from an earlier concept known as the Parallel Random-Access Machine/model (PRAM), which was an early attempt at parallel programming. The PRAM attempt was considered as having a great ...

High Performance Computing (HPC) and parallel programming techniques underpin many of today’s most demanding computational tasks, from complex scientific simulations to data-intensive analytics. This ...

Parallel programming exploits the capabilities of multicore systems by dividing computational tasks into concurrently executed subtasks. This approach is fundamental to maximising performance and ...

In this slidecast, Torsten Hoefler from ETH Zurich presents: Data-Centric Parallel Programming. The ubiquity of accelerators in high-performance computing has driven programming complexity beyond the ...

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 ...

In January we gave NVIDIA’s CUDA (Compute Unified Device Architecture) software tools that allows C programmers to use multiple high-performance GPU cards to perform massively parallel computations ...

The widespread adoption of multi-core hardware is in many cases actually slowing down computing. A typical scenario: A company has a data-intensive software application and wants to make this software ...

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 ...