concept compute unit in category parallel computing

This is an excerpt from Manning's book Parallel and High Performance Computing MEAP V11 epub. Login to get full access to this book.

In this section, we’ll explore each of the components in our model of a GPU. With each component, we will discuss models for theoretical peak bandwidth. Additionally, we’ll show how to use micro-benchmark tools. 9.2.1   The compute unit is the streaming multiprocessor A GPU compute device has multiple compute units. Compute units (CUs) is the term agreed to by the community for the OpenCL standard. Nvidia calls these streaming multiprocessors (SMs) and Intel refers to them as subslices.

Figure 9.2 A simplified block diagram of a GPU system showing two compute devices, each of them a separate GPU, GPU memory, and multiple Compute Units (CUs) on each compute device. The Nvidia Cuda terminology refers to compute units as Streaming Multiprocessors (SMs).

Figure 10.5 A multi-dimensional work group is linearized onto a 1D strip where it is broken up into subgroups of 32 or 64 work-items. For performance reasons, work groups should be multiples of the subgroup size.