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 ...
Parallel programming exploits the capabilities of multicore systems by dividing computational tasks into concurrently executed subtasks. This approach is fundamental to maximising performance and ...
Dr. Guy Blelloch of Carnegie Mellon University has written an article for the folks at CilkArts analyzing why parallel programming seems to be more difficult than sequential programming. He quickly ...
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 ...
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