All processors since about 1985 use pipelining to overlap the execution of instructions and improve performance. This potential overlap among instructions is called instruction-level parallelism (ILP), since the instructions can be evaluated in parallel.
There are two largely separable approaches to exploiting ILP: an approach that relies on hardware to help discover and exploit the parallelism dynamically, and an approach that relies on software technology to find parallelism, statically at compile time. Processors using the dynamic, hardware-based approach, including the Intel Pentium series, dominate in the market; those using the static approach, including the Intel Itanium, have more limited uses in scientific or application-specific environments.
The value of the CPI (cycles per instruction) for a pipelined processor is the sum of the base CPI and all contributions from stalls: Pipeline CPI = Ideal pipeline CPI + Structural stalls + Data hazard stalls + Control stalls
The ideal pipeline CPI is a measure of the maximum performance attainable by the implementation. By reducing each of the terms of the right-hand side to minimize the overall pipeline CPI or, alternatively, increase the IPC (instructions per clock).
The simplest and most common way to increase the ILP is to exploit parallel- ism among iterations of a loop. This type of parallelism is often called loop-level parallelism.There are a number of techniques for converting such loop- level parallelism into instruction-levelparallelism. Basically, such techniques work by unrolling the loop either statically by the compiler or dynamically by the hardware. An important alternative method for exploiting loop-level parallelism is the use of vector instructions . A vector instruction exploits data- level parallelism by operating on data items in parallel.
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