10,354 research outputs found
Lost in translation: Exposing hidden compiler optimization opportunities
Existing iterative compilation and machine-learning-based optimization
techniques have been proven very successful in achieving better optimizations
than the standard optimization levels of a compiler. However, they were not
engineered to support the tuning of a compiler's optimizer as part of the
compiler's daily development cycle. In this paper, we first establish the
required properties which a technique must exhibit to enable such tuning. We
then introduce an enhancement to the classic nightly routine testing of
compilers which exhibits all the required properties, and thus, is capable of
driving the improvement and tuning of the compiler's common optimizer. This is
achieved by leveraging resource usage and compilation information collected
while systematically exploiting prefixes of the transformations applied at
standard optimization levels. Experimental evaluation using the LLVM v6.0.1
compiler demonstrated that the new approach was able to reveal hidden
cross-architecture and architecture-dependent potential optimizations on two
popular processors: the Intel i5-6300U and the Arm Cortex-A53-based Broadcom
BCM2837 used in the Raspberry Pi 3B+. As a case study, we demonstrate how the
insights from our approach enabled us to identify and remove a significant
shortcoming of the CFG simplification pass of the LLVM v6.0.1 compiler.Comment: 31 pages, 7 figures, 2 table. arXiv admin note: text overlap with
arXiv:1802.0984
Model-based dependability analysis : state-of-the-art, challenges and future outlook
Abstract: Over the past two decades, the study of model-based dependability analysis has gathered significant research interest. Different approaches have been developed to automate and address various limitations of classical dependability techniques to contend with the increasing complexity and challenges of modern safety-critical system. Two leading paradigms have emerged, one which constructs predictive system failure models from component failure models compositionally using the topology of the system. The other utilizes design models - typically state automata - to explore system behaviour through fault injection. This paper reviews a number of prominent techniques under these two paradigms, and provides an insight into their working mechanism, applicability, strengths and challenges, as well as recent developments within these fields. We also discuss the emerging trends on integrated approaches and advanced analysis capabilities. Lastly, we outline the future outlook for model-based dependability analysis
- …