GPGPU 2
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Description
The modern GPU can be used as a general-purpose processor. This field of "GPGPU" (general-purpose programmability of graphics hardware) or "GPU computing" is having an increasing impact on GPU architecture, GPU software and programming environments, and the computing industry. These two lectures discuss the fundamentals of GPGPU: the programming model, the hardware, and some fundamental algorithms. We use NVIDIA's CUDA and G80 architecture as a representative example.
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In our final content lecture, we look at how to parallelize the graphics pipeline. What is challenging about parallelizing the GPU? What are the ways we could parallelize it? We discuss the sorting taxonomy of parallelism strategies, look at different ways to communicate within a multi-node...
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