Development tools for parallel computer systems tend to be architecture-specific, difficult to integrate and fairly basic. Parallel application developers often find themselves juggling tools to match ...

In the podcast, Mike Bernhardt from ECP catches up with Sameer Shende to learn how the Performance Research Lab at the University of Oregon is helping to pave the way to Exascale. Developers of ...

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 ...

NVIDIA's CUDA (Compute Unified Device Architecture) makes programming and using thousands of simultaneous threads straightforward. CUDA turns workstations, clusters—and even laptops—into massively ...

The end of dramatic exponential growth in single-processor performance marks the end of the dominance of the single microprocessor in computing. The era of sequential computing must give way to a new ...

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 ...