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 ...

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 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 ...

(CS 213 or (CE 205 & 211)) or MS CS/CE or PhDs CS/CE or permission of Instructor. CS 358 serves as an introduction to the field of parallel computing. Topics include common parallel architectures ...

One of the best features of using FPGAs for a design is the inherent parallelism. Sure, you can write software to take advantage of multiple CPUs. But with an FPGA you can enjoy massive parallelism ...

Back in 1965, Intel cofounder Gordon Moore predicted that the semiconductor industry could double the number of transistors on a chip every 12 months (he later amended it to 24 months) for about the ...

In this video, Torsten Hoefler from ETH Zurich presents: Scientific Benchmarking of Parallel Computing Systems. Measuring and reporting performance of parallel computers constitutes the basis for ...

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 ...