← Course contents · Part 1

· Visual lesson · Session 4 of 56


Why does a GPU wait?

A powerful GPU can spend its time waiting. Before buying a faster one, find out where the job actually spends its time.

Picture the idea

Where six seconds go

Read and prepare4 seconds

Largest opportunity in this example

Transfer1 second

Make data available to the GPU

Calculate1 second

Only one sixth of the original time

Invented sequential workload. With overlapping stages, elapsed time follows a different model.

Follow the slowest stage

For a separate GPU, data may travel from storage to CPU preparation, then GPU memory, then calculation. A delay anywhere can hold up the result.

The diagram uses an invented job with no overlap. Four seconds go into preparation, one into transfer, and one into calculation.

Halving calculation time saves only half a second. Reducing preparation from four seconds to two saves two seconds.

Three different measurements

Capacity is how much fits. Bandwidth is how much moves per second. Latency is how long an operation takes.

A large memory capacity does not guarantee a fast data supply. Also watch units: eight bits make one byte.

Try it yourself

Why does doubling calculation speed not halve this six-second job?

Check your answer

Only one second was calculation. The new total is 5.5 seconds. Real applications may overlap stages; then the slowest stage can set the steady pace instead of their times simply adding up.

Sources and further reading

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