Assisting static compiler vectorization with a speculative dynamic vectorizer in an HW/SW codesigned environment

Compiler-based static vectorization is used widely to extract data-level parallelism from computation-intensive applications. Static vectorization is very effective in vectorizing traditional array-based applications. However, compilers' inability to do accurate interprocedural pointer disambig...

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Bibliographic Details
Authors: Kumar, Rakesh, Martínez, Alejandro, González Colás, Antonio María|||0000-0002-0009-0996
Format: article
Publication Date:2016
Country:España
Institution:Universitat Politècnica de Catalunya (UPC)
Repository:UPCommons. Portal del coneixement obert de la UPC
Language:English
OAI Identifier:oai:upcommons.upc.edu:2117/89771
Online Access:https://hdl.handle.net/2117/89771
https://dx.doi.org/10.1145/2807694
Access Level:Open access
Keyword:Compilers (Computer programs)
Dynamic optimizations
Hardware/software codesigned processors
Speculation
Vectorization
Compiladors (Programes d'ordinador)
Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors
Description
Summary:Compiler-based static vectorization is used widely to extract data-level parallelism from computation-intensive applications. Static vectorization is very effective in vectorizing traditional array-based applications. However, compilers' inability to do accurate interprocedural pointer disambiguation and interprocedural array dependence analysis severely limits vectorization opportunities. HW/SW codesigned processors provide an excellent opportunity to optimize the applications at runtime. The availability of dynamic application behavior at runtime helps in capturing vectorization opportunities generally missed by the compilers. This article proposes to complement the static vectorization with a speculative dynamic vectorizer in an HW/SW codesigned processor. We present a speculative dynamic vectorization algorithm that speculatively reorders ambiguous memory references to uncover vectorization opportunities. The speculative reordering of memory instructions avoids the need for accurate interprocedural pointer disambiguation and interprocedural array dependence analysis. The hardware checks for any memory dependence violation due to speculative vectorization and takes corrective action in case of violation. Our experiments show that the combined (static + dynamic) vectorization approach provides a 2× performance benefit compared to the static GCC vectorization alone, for SPECFP2006. Furthermore, the speculative dynamic vectorizer is able to vectorize 48% of the loops that ICC failed to vectorize due to conservative dependence analysis in the TSVC benchmark suite. Moreover, the dynamic vectorization scheme is as effective in vectorization of pointer-based applications as for the array-based ones, whereas compilers lose significant vectorization opportunities in pointer-based applications. Furthermore, we show that speculation is not only a luxury but also a necessity for runtime vectorization.