Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Genetic Improvement in the Shackleton Framework for Optimizing LLVM Pass
  Sequences   Genetic improvement is a search technique that aims to improve a given
acceptable solution to a problem. In this paper, we present the novel use of
genetic improvement to find problem-specific optimized LLVM pass sequences. We
develop a pass-level patch representation in the linear genetic programming
framework, Shackleton, to evolve the modifications to be applied to the default
optimization pass sequences. Our GI-evolved solution has a mean of 3.7% runtime
improvement compared to the -O3 optimization level in the default code
generation options which optimizes on runtime. The proposed GI method provides
an automatic way to find a problem-specific optimization sequence that improves
upon a general solution without any expert domain knowledge. In this paper, we
discuss the advantages and limitations of the GI feature in the Shackleton
Framework and present our results.

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The categories of this paper are: plasm-ph
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
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The categories of this paper are: dg-ga
17
The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
13
The categories of this paper are: quant-ph
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The categories of this paper are: nlin
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The categories of this paper are: hep-ex
18
The categories of this paper are: econ
15
The categories of this paper are: nucl-ex
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
20
The categories of this paper are: acc-phys
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The categories of this paper are: adap-org