Amazon CTO Werner Vogels takes an in-depth look at the new AWS EC2 Cluster GPU Instances for Cloud HPC:
One trade-off area where our general purpose CPUs were not performing well was that of massive fine grain parallelism. Graphics processing is one such area with huge computational requirements, but where each of the tasks is relatively small and often a set of operations are performed on data in the form of a pipeline. The throughput of this pipeline is more important than the latency of the individual operations. Because of its focus on latency, the generic CPU yielded rather inefficient system for graphics processing. This lead to the birth of the Graphics Processing Unit (GPU) which was focused on providing a very fine grained parallel model, with processing organized in multiple stages, where the data would flow through. The model of a GPU is that of task parallelism describing the different stages in the pipeline, as well as data parallelism within each stage, resulting in a highly efficient, high throughput computation architecture.
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