Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: goSLP: Globally Optimized Superword Level Parallelism Framework   Modern microprocessors are equipped with single instruction multiple data
(SIMD) or vector instruction sets which allow compilers to exploit superword
level parallelism (SLP), a type of fine-grained parallelism. Current SLP
auto-vectorization techniques use heuristics to discover vectorization
opportunities in high-level language code. These heuristics are fragile, local
and typically only present one vectorization strategy that is either accepted
or rejected by a cost model. We present goSLP, a novel SLP auto-vectorization
framework which solves the statement packing problem in a pairwise optimal
manner. Using an integer linear programming (ILP) solver, goSLP searches the
entire space of statement packing opportunities for a whole function at a time,
while limiting total compilation time to a few minutes. Furthermore, goSLP
optimally solves the vector permutation selection problem using dynamic
programming. We implemented goSLP in the LLVM compiler infrastructure,
achieving a geometric mean speedup of 7.58% on SPEC2017fp, 2.42% on SPEC2006fp
and 4.07% on NAS benchmarks compared to LLVM's existing SLP auto-vectorizer.

31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
37
The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat
32
The categories of this paper are: atom-ph
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
34
The categories of this paper are: chem-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: q-bio
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The categories of this paper are: q-fin
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The categories of this paper are: funct-an