DocumentCode :
2193365
Title :
Selective eager execution on the PolyPath architecture
Author :
Klauser, Artur ; Paithankar, Abhijit ; Grunwald, Dirk
Author_Institution :
Dept. of Comput. Sci., Colorado Univ., Boulder, CO, USA
fYear :
1998
fDate :
27 Jun-1 Jul 1998
Firstpage :
250
Lastpage :
259
Abstract :
Control-flow misprediction penalties are a major impediment to high performance in wide-issue superscalar processors. In this paper we present Selective Eager Execution (SEE), an execution model to overcome mis-speculation penalties by executing both paths after diffident branches. We present the micro-architecture of the PolyPath processor which is an extension of an aggressive superscalar out-of-order architecture. The PolyPath architecture uses a novel instruction tagging and register renaming mechanism to execute instructions from multiple paths simultaneously in the same processor pipeline, while retaining maximum resource availability for single-path code sequences. Results of our execution-driven, pipeline-level simulations show that SEE can improve performance by as much as 36% for the go benchmark, and an average of 14% on SPECint95, when compared to a normal superscalar, out-of-order speculative execution, monopath processor. Moreover our architectural model is both elegant and practical to implement, using a small amount of additional state and control logic
Keywords :
digital simulation; parallel architectures; performance evaluation; PolyPath architecture; SPECint95; control logic; control-flow misprediction penalties; go benchmark; instruction tagging; pipeline-level simulations; register renaming mechanism; selective eager execution; superscalar out-of-order architecture; superscalar processors; Bandwidth; Computer architecture; Computer science; Contracts; Delay; Out of order; Performance loss; Pipelines; Registers; Tagging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Architecture, 1998. Proceedings. The 25th Annual International Symposium on
Conference_Location :
Barcelona
ISSN :
1063-6897
Print_ISBN :
0-8186-8491-7
Type :
conf
DOI :
10.1109/ISCA.1998.694785
Filename :
694785
Link To Document :
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