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ALP: Efficient Support for All Levels of Parallelism for Complex Media Applications
 

Summary: ALP: Efficient Support for All Levels of
Parallelism for Complex Media Applications
RUCHIRA SASANKA, MAN-LAP LI, and SARITA V. ADVE
University of Illinois at Urbana-Champaign
and
YEN-KUANG CHEN and ERIC DEBES
Intel Corporation
The real-time execution of contemporary complex media applications requires energy-efficient pro-
cessing capabilities beyond those of current superscalar processors. We observe that the complexity
of contemporary media applications requires support for multiple forms of parallelism, including
ILP, TLP, and various forms of DLP, such as subword SIMD, short vectors, and streams. Based
on our observations, we propose an architecture, called ALP, that efficiently integrates all of these
forms of parallelism with evolutionary changes to the programming model and hardware. The novel
part of ALP is a DLP technique called SIMD vectors and streams (SVectors/SStreams), which is
integrated within a conventional superscalar-based CMP/SMT architecture with subword SIMD.
This technique lies between subword SIMD and vectors, providing significant benefits over the
former at a lower cost than the latter. Our evaluations show that each form of parallelism sup-
ported by ALP is important. Specifically, SVectors/SStreams are effective, compared to a system
with the other enhancements in ALP. They give speedups of 1.1 to 3.4X and energy-delay product
improvements of 1.1 to 5.1X for applications with DLP.

  

Source: Adve, Sarita - Department of Computer Science, University of Illinois at Urbana-Champaign

 

Collections: Computer Technologies and Information Sciences