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An architecture for high instruction level parallelism

Authors: S. Arya; H. Sachs; S. Duvvuru;

An architecture for high instruction level parallelism

Abstract

High instruction level parallelism (ILP) can only be achieved when data flow and control flow constraints have been removed or reduced. Data flow constraints, not inherent in the original code, arise from lack of sufficient resources for initiation and execution of multiple instructions concurrently. Control flow, problems are caused by branches which force unpredictable changes in the sequential order of code execution. Removing these obstacles allows for the formation of larger basic blocks, resulting in higher ILP. The dataflow problems are reduced by increasing the number of functional units, registers, condition bits, by pipelining the functional units, and using nonblocking caches. The control flow problem is reduced by using techniques such as conditional execution, speculative execution, and software pipelining, leveraging hardware support. Thus, for high ILP, the processor architecture should include a very closely tied hardware and compiler architectures. An architecture that supports the above features, Software Scheduled SuperScalar, is presented in this paper. >

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    citations
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    6
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
6
Average
Top 10%
Top 10%
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