Intel® 64 and IA-32 Architectures Optimization Reference Manual

MULTICORE AND HYPER-THREADING TECHNOLOGY8.1.1 MultithreadingWhen an application employs multithreading to exploit task-level parallelism in aworkload, the control flow of the multi-threaded software can be divided into twoparts: parallel tasks and sequential tasks.Amdahl’s law describes an application’s performance gain as it relates to the degreeof parallelism in the control flow. It is a useful guide for selecting the code modules,functions, or instruction sequences that are most likely to realize the most gains fromtransforming sequential tasks and control flows into parallel code to take advantagemultithreading hardware support.Figure 8-1 illustrates how performance gains can be realized for any workloadaccording to Amdahl’s law. The bar in Figure 8-1 represents an individual task unit orthe collective workload of an entire application.In general, the speed-up of running multiple threads on an MP systems with N physicalprocessors, over single-threaded execution, can be expressed as:TsequentialPRelativeResponse= ------------------------------- = ⎛1 – P + --- + O⎞Tparallel ⎝ N ⎠where P is the fraction of workload that can be parallelized, and O represents theoverhead of multithreading and may vary between different operating systems. Inthis case, performance gain is the inverse of the relative response.Single ThreadTsequential1-P PTparallelMulti-Thread on MP1-PP/2P/2OverheadFigure 8-1. Amdahl’s Law and MP Speed-upWhen optimizing application performance in a multithreaded environment, controlflow parallelism is likely to have the largest impact on performance scaling withrespect to the number of physical processors and to the number of logical processorsper physical processor.8-2