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Super scalar
&
Super Pipeline
approach to processor
Superscalar
• 1st invented in 1987
• Superscalar processor executes multiple independent
instructions in parallel.
• Common instructions (arithmetic, load/store etc) can
be initiated simultaneously and executed
independently.
• Applicable to both RISC & CISC, but usually in RISC
Why Superscalar
• Most operations are on scalar quantities
• Superscalar was designed to improve the
performance of these operations by executing them
concurrently in multiple pipelines
Superscalar Performance
• In superscalar multiple independent instruction pipelines are
used. Each pipeline consists of multiple stages, so that each
pipeline can handle multiple instructions at a time.
• A superscalar processor typically fetches multiple instructions
at a time and then attempts to find nearby instructions that
are independent of one another and can therefore be
executed in parallel.
• If the input to one instruction depends on the output of a
preceding instruction, then the latter instruction cannot
complete execution at the same time or before the former
instruction.
General Superscalar Organization
• The configuration below, supports the parallel
execution of two integer operations, two floating
point operations and one memory operation.
Super Pipeline
• Super-pipeline is an alternative approach to achieve
greater performance
• 1st invented in 1988
• Many pipeline stages need less than half a clock
cycle
Super pipeline cont…
• Super-pipelining is the breaking of stages of a given
pipeline into smaller stages (thus making the
pipeline deeper) in an attempt to shorten the clock
period and thus enhancing the instruction
throughput by keeping more and more instructions
in flight at a time.
Super pipeline Performance
• The performance is shown below in the figure:
Superscalar versus
super-pipeline
• Simple pipeline system
performs only one pipeline
stage per clock cycle
• Super-pipeline system is
capable of performing two
pipeline stages per clock cycle

• Superscalar performs only
one pipeline stage per clock
cycle in each parallel pipeline
Super pipeline benefit & drawback
• Benefits:
The major benefit of super-pipelining is the increase in
the number of instructions which can be in the pipeline at
one time and hence the level of parallelism.
• Drawbacks:
The larger number of instructions "in flight" (i.e., in some
part of the pipeline) at any time, increases the potential
for data dependencies to introduce stalls.
Limitations of superscalar
• The superscalar approach depends on the ability to
execute multiple instructions in parallel. The term
Instruction-level parallelism refers to the degree to
which the instructions of a program can be
executed in parallel.
• A combination of compiler-based optimization and
hardware techniques can be used to maximize
instruction-level parallelism.
Limitations to parallelism
Fundamental limitations to parallelism
– True data dependency
– Procedural dependency
– Resource conflicts
– Output dependency
– Anti-dependency
Data dependency problem
• The major problem of executing multiple
instructions in a scalar program is the handling of
data dependencies. If data dependencies are not
effectively handled, it is difficult to achieve an
execution rate of more than one instruction per
clock cycle.
Any Question

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Superscalar & superpipeline processor

  • 1.
  • 2.
  • 4. Superscalar • 1st invented in 1987 • Superscalar processor executes multiple independent instructions in parallel. • Common instructions (arithmetic, load/store etc) can be initiated simultaneously and executed independently. • Applicable to both RISC & CISC, but usually in RISC
  • 5. Why Superscalar • Most operations are on scalar quantities • Superscalar was designed to improve the performance of these operations by executing them concurrently in multiple pipelines
  • 6. Superscalar Performance • In superscalar multiple independent instruction pipelines are used. Each pipeline consists of multiple stages, so that each pipeline can handle multiple instructions at a time. • A superscalar processor typically fetches multiple instructions at a time and then attempts to find nearby instructions that are independent of one another and can therefore be executed in parallel. • If the input to one instruction depends on the output of a preceding instruction, then the latter instruction cannot complete execution at the same time or before the former instruction.
  • 7. General Superscalar Organization • The configuration below, supports the parallel execution of two integer operations, two floating point operations and one memory operation.
  • 8. Super Pipeline • Super-pipeline is an alternative approach to achieve greater performance • 1st invented in 1988 • Many pipeline stages need less than half a clock cycle
  • 9. Super pipeline cont… • Super-pipelining is the breaking of stages of a given pipeline into smaller stages (thus making the pipeline deeper) in an attempt to shorten the clock period and thus enhancing the instruction throughput by keeping more and more instructions in flight at a time.
  • 10. Super pipeline Performance • The performance is shown below in the figure:
  • 11. Superscalar versus super-pipeline • Simple pipeline system performs only one pipeline stage per clock cycle • Super-pipeline system is capable of performing two pipeline stages per clock cycle • Superscalar performs only one pipeline stage per clock cycle in each parallel pipeline
  • 12. Super pipeline benefit & drawback • Benefits: The major benefit of super-pipelining is the increase in the number of instructions which can be in the pipeline at one time and hence the level of parallelism. • Drawbacks: The larger number of instructions "in flight" (i.e., in some part of the pipeline) at any time, increases the potential for data dependencies to introduce stalls.
  • 13. Limitations of superscalar • The superscalar approach depends on the ability to execute multiple instructions in parallel. The term Instruction-level parallelism refers to the degree to which the instructions of a program can be executed in parallel. • A combination of compiler-based optimization and hardware techniques can be used to maximize instruction-level parallelism.
  • 14. Limitations to parallelism Fundamental limitations to parallelism – True data dependency – Procedural dependency – Resource conflicts – Output dependency – Anti-dependency
  • 15. Data dependency problem • The major problem of executing multiple instructions in a scalar program is the handling of data dependencies. If data dependencies are not effectively handled, it is difficult to achieve an execution rate of more than one instruction per clock cycle.
  • 16.