Translating the ARM Neon and VFP instructions in a binary translator

Summary Binary translation attempts to emulate one instruction set with another on the same or different platforms. The important technique is widely used in modern software. Vector and floating‐point instructions are widely used in many applications, including multimedia, graphics, and gaming. Alth...

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Bibliographic Details
Published in:Software, practice & experience practice & experience, 2016-12, Vol.46 (12), p.1591-1615
Main Authors: Guo, Yu-Chuan, Yang, Wuu, Chen, Jiunn-Yeu, Lee, Jenq-Kuen
Format: Article
Language:English
Subjects:
binary translation
cloud computing
Computer programs
Floating point arithmetic
floating-point instruction
Hardware
LLVM
Multimedia
Neon
Software
Translations
Translators
vector instruction
VFP
virtualization
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Summary:Summary Binary translation attempts to emulate one instruction set with another on the same or different platforms. The important technique is widely used in modern software. Vector and floating‐point instructions are widely used in many applications, including multimedia, graphics, and gaming. Although these instructions are usually simulated with software in a binary translator, it is important to support them such that the host single‐instruction, multiple‐data (SIMD) and floating‐point hardware are efficiently used during emulation. We report our design and implementation of the emulation of ARM Neon and vector floating point (VFP) instructions in the machine‐code‐to‐low‐level‐virtual‐machine (MC2LLVM) binary translator. The Neon and VFP instructions are first translated into carefully chosen sequences of LLVM intermediate representation (IR), and later, the IR sequences are optimized and translated into the host native binary by the existing LLVM backend. Because MC2LLVM makes use of the vector and floating‐point types in LLVM IR, the generated host native binary can take full advantage of the vector and floating‐point functional units, if present, of the host machine. To be fully compliant with Neon and VFP instruction sets, all the features are supported, including the flush‐to‐zero mode, default not a number mode, and floating‐point exceptions. The experimental results show that code generated by MC2LLVM with the Neon and VFP extensions achieves an average speedup of 1.174× in SPEC 2006 benchmark suites and exhibits a floating‐point throughput of 12.05× in LINPACK, compared with code generated by MC2LLVM without the Neon and VFP extensions. Furthermore, MC2LLVM is 3.36× faster than QEMU for processing Neon/VFP instructions. Copyright © 2016 John Wiley & Sons, Ltd.
ISSN:0038-0644
1097-024X
DOI:10.1002/spe.2394