# 2.7 Module 8: instruction pipelining  (Page 2/3)

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In general, the time delay d is equivalent to a clock pulse and ${T}_{m}$ >>d. Suppose that n instruction are processed with no branched.

• The total time required ${T}_{k}$ to execute all n instruction is:

${T}_{k}$ = [k + (n-1)]

• The speedup factor for the instruction pipeline compared to execution without the pipeline is defined as:

${S}_{K}=\frac{{T}_{1}}{{T}_{K}}=\frac{\text{nk}\tau }{\left[k+\left(n-1\right)\right]\tau }=\frac{\text{nk}}{k+\left(n-1\right)}$

• An ideal pipeline divides a task into k independent sequential subtasks

– Each subtask requires 1 time unit to complete

– The task itself then requires k time units tocomplete. For n iterations of the task, the execution times will be:

– With no pipelining: nk time units

– With pipelining: k + (n-1) time units

Speedup of a k-stage pipeline is thus

S = nk / [k+(n-1)] ==>k (for large n)

## 2.2 pipeline limitations

Several factors serve to limit the pipeline performance. If the six stage are not of equal duration, there will be some waiting involved at various pipeline stage. Another difficulty is the condition branch instruction or the unpredictable event is an interrupt. Other problem arise that the memory conflicts could occur. So the system must contain logic to account for the type of conflict.

• Pipeline depth

- Data dependencies also factor into the effective length of pipelines

- Logic to handle memory and register use and to control the overall pipeline increases significantly with increasing pipeline depth

– If the speedup is based on the number of stages, why not build lots of stages?

– Each stage uses latches at its input (output) to buffer the next set of inputs

+ If the stage granularity is reduced too much, the latches and their control become a significant hardware overhead

+ Also suffer a time overhead in the propagation time through the latches

- Limits the rate at which data can be clocked through the pipeline

• Data dependencies

– Pipelining must insure that computed results are the same as if computation was performed in strict sequential order

– With multiple stages, two instructions “in execution” in the pipeline may have data dependencies. So we must design the pipeline to prevent this.

– Data dependency examples:

A = B + C

D = E + A

C = G x H

A = D / H

Data dependencies limit when an instruction can be input to the pipeline.

• Branching

One of the major problems in designing an instruction pipeline is assuring a steady flow of instructions to initial stages of the pipeline. However, 15-20% of instructions in an assembly-level stream are (conditional) branches. Of these, 60-70% take the branch to a target address. Until the instruction is actually executed, it is impossible to determin whether the branch will be taken or not.

- Impact of the branch is that pipeline never really operates at its full capacity.

– The average time to complete a pipelined instruction becomes

Tave =(1-pb)1 + pb[pt(1+b) + (1-pt)1]

– A number of techniques can be used to minimize the impact of the branch instruction (the branch penalty).

- A several approaches have been taken for dealing with conditional branches:

+ Multiple streams

+ Prefetch branch target

+ Loop buffer

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Almas
are nano particles real
yeah
Joseph
Hello, if I study Physics teacher in bachelor, can I study Nanotechnology in master?
no can't
Lohitha
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William
currently
William
where we get a research paper on Nano chemistry....?
nanopartical of organic/inorganic / physical chemistry , pdf / thesis / review
Ali
what are the products of Nano chemistry?
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learn
Even nanotechnology is pretty much all about chemistry... Its the chemistry on quantum or atomic level
learn
da
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Bhagvanji
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Giriraj
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revolt
da
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narayan
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Damian
yes that's correct
Professor
I think
Professor
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LITNING
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Anam
analytical skills graphene is prepared to kill any type viruses .
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Bob
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brayan
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When we have data register and address registers in user mode (visible registers) then why we need MAR and MBR
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