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| GIM>Research>Publication |
| PUBLICATION |
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| Full record |
| Title: | An Efficient Joint Analytical and Simulation-based Design Space
Exploration Flow for Predictable Multi-Core Systems |
| Type: | International Conference |
| Where: | 7th Workshop on Rapid Simulation and Performance Evaluation: Methods and Tools. RAPIDO´15 |
| Date: | 2015-01 |
| Authors: |
Fernando Herrera
Ingo Sander
Kathrin Rosvall
Edoardo Paone
Gianluca Palermo
|
| R&D Lines: |
Design of HW/SW Embedded Systems
|
| Projects: |
FP7 611146 CONTREX
|
| ISBN: | 978-1-60558-6991 |
| PDF File: | see file
|
| Abstract: | Recent work has proposed two phase joint analytical and
simulation-based design space exploration (JAS-DSE) ap-
proaches. In such approaches, a first analytical phase relies
on static performance estimation and either on exhaustive or
heuristic search, to perform a very fast filtering of the design
space. Then, a second phase obtains the Pareto solutions af-
ter an exhaustive simulation of the solutions found as com-
pliant by the analytical phase. However, the capability of
such approaches to find solutions close to the actual Pareto
set at a reasonable time cost is compromised by current sys-
tem complexities. This limitation is due to the fact that such
approaches do not support an heuristic exploration on the
simulation-based phase. It is not straightforward because in
the second phase the heuristic is constrained to consider only
the custom set of solutions found in the first phase. This set
is in general unconnected and irregularly distributed, which
prevents the application of existing heuristics. This paper
provides as a solution a novel search heuristic called ARS
(Adaptive Random Sampling). The ARS strategy enables
the application of heuristic search in the two-phases of the
JAS-DSE flow, by enabling the application of heuristic in
the second phase, regardless the type of performance esti-
mation done at each phase. Moreover, it would enable the
definition of N-phase DSE flows. The paper shows on an
experiment focused on predictable multi-core systems how
this enhanced JAS-DSE is capable to find more efficient so-
lutions and to tune the trade-off between exploration time
and accuracy in finding actual Pareto solutions. |
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