Title :
A Dependency Chain Clustered Microarchitecture
Author :
Narayanasamy, Satish ; Hong Wang ; Wang, Hong ; Shen, John ; Calder, Brad
Author_Institution :
Dept. of Comput. Sci. & Eng., California Univ., San Diego, CA, USA
Abstract :
In this paper we explore a new clustering approach for reducing the complexity of wide issue in-order processors based on EPIC architectures. Complexity effectiveness is achieved by heavily clustering the pipeline from decode to commit stage without the need for any direct bypass between clusters. This is made possible by assuming support for executing compiler-constructed traces. One trace is executed at a time by executing its coarse-grained dependency chains (DCs) in different in-order clusters. Since the DCs of a trace are mutually data independent of each other they can be executed in different clusters without any direct communication between them. To execute DCs in narrower clusters without compromising ILP, a compiler algorithm that splits large DCs by duplicating instructions is proposed. Through cycle accurate simulations we show that a DC processor with one 3-wide, one 2-wide and one 1-wide in-order pipeline, could achieve performance equivalent to a 6-wide inorder superscalar processor. Since a clustered DC microarchitecture is complexity efficient, it is amenable to higher clock frequencies and will also be easier to design and validate than a 6-wide monolithic design.
Keywords :
instruction sets; parallel architectures; parallelising compilers; pipeline processing; 1-wide in-order pipeline; 2-wide in-order pipeline; 3-wide in-order pipeline; 6-wide in-order superscalar processor; 6-wide monolithic design; DC processor; EPIC architectures; clustered DC microarchitecture; coarse-grained dependency chains; compiler algorithm; compiler-constructed traces; dependency chain clustered microarchitecture; Computer architecture; Computer science; Decoding; Delay; Distributed control; Frequency; Microarchitecture; Optimizing compilers; Pipelines; Processor scheduling;
Conference_Titel :
Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International
Print_ISBN :
0-7695-2312-9
DOI :
10.1109/IPDPS.2005.16