Government-funded academic research on parallel computing, stream processing, real-time shading languages, and programmable ...

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 ...

Programming languages are evolving to bring the software closer to hardware. As hardware architectures become more parallel (with the advent of multicore processors and FPGAs, for example), sequential ...

Graphics processing units (GPUs) are traditionally designed to handle graphics computational tasks, such as image and video processing and rendering, 2D and 3D graphics, vectoring, and more.

A technical paper titled “Scalable Automatic Differentiation of Multiple Parallel Paradigms through Compiler Augmentation” was published by researchers at MIT (CSAIL), Argonne National Lab, and TU ...

CUDA is a parallel computing programming model for Nvidia GPUs. With the proliferation over the past decade of GPU usage for speeding up applications across HPC, AI and beyond, the ready availability ...

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 ...

Students will be able to analyze the computing and memory architecture of a super computing node and use OpenMP directives to improve vectorization of their programs. This module focuses on the key ...

The enormous growth in artificial intelligence (AI) and Internet of Things (IoT) is fueling a growing demand for high-efficiency computing to perform real-time analysis on massive amounts of data. In ...