Post Register Allocation Spill Code Optimization

CODE OPTIMIZATION METHOD FOR QUALCOMM HEXAGON PROCESSOR, SUPPORTING INSTRUCTION LEVEL PARALLELISM AND BUILT WITH VLIW (Very Long Instruction Word) ARCHITECTURE

ITNOU: Information technologies in education, science and management ◽

10.47501/itnou.2021.1.105-115 ◽

2021 ◽

Vol 115 ◽

pp. 105-115

Author(s):

Tatiana Nikolaevna Romanova ◽

◽

Dmitry Igorevich Gorin ◽

Keyword(s):

Optimization Method ◽

Register Allocation ◽

Instruction Level Parallelism ◽

Code Optimization ◽

Very Long Instruction Word ◽

Running Time ◽

Level Parallelism ◽

Packet Density

A method for optimizing the filling of a machine word with independent instructions is proposed, which allows to increase the performance of programs by stacking the maximum number of independent commands in a package. The paper also confirms the hypothesis that with the transition to random register allocation by the compiler, the packet density will increase, which will result in a decrease in the program's running time.

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Breaking Instance-Independent Symmetries In Exact Graph Coloring

Journal of Artificial Intelligence Research ◽

10.1613/jair.1637 ◽

2006 ◽

Vol 26 ◽

pp. 289-322 ◽

Cited By ~ 11

Author(s):

A. Ramani ◽

I. L. Markov ◽

K. A. Sakallah ◽

F. A. Aloul

Keyword(s):

Symmetry Breaking ◽

Graph Coloring ◽

Optimization Problems ◽

Register Allocation ◽

Code Optimization ◽

Dramatic Improvement ◽

Planning Time ◽

Sat Solvers ◽

Reduction Methods ◽

High Level

Code optimization and high level synthesis can be posed as constraint satisfaction and optimization problems, such as graph coloring used in register allocation. Graph coloring is also used to model more traditional CSPs relevant to AI, such as planning, time-tabling and scheduling. Provably optimal solutions may be desirable for commercial and defense applications. Additionally, for applications such as register allocation and code optimization, naturally-occurring instances of graph coloring are often small and can be solved optimally. A recent wave of improvements in algorithms for Boolean satisfiability (SAT) and 0-1 Integer Linear Programming (ILP) suggests generic problem-reduction methods, rather than problem-specific heuristics, because (1) heuristics may be upset by new constraints, (2) heuristics tend to ignore structure, and (3) many relevant problems are provably inapproximable. Problem reductions often lead to highly symmetric SAT instances, and symmetries are known to slow down SAT solvers. In this work, we compare several avenues for symmetry breaking, in particular when certain kinds of symmetry are present in all generated instances. Our focus on reducing CSPs to SAT allows us to leverage recent dramatic improvement in SAT solvers and automatically benefit from future progress. We can use a variety of black-box SAT solvers without modifying their source code because our symmetry-breaking techniques are static, i.e., we detect symmetries and add symmetry breaking predicates (SBPs) during pre-processing. An important result of our work is that among the types of instance-independent SBPs we studied and their combinations, the simplest and least complete constructions are the most effective. Our experiments also clearly indicate that instance-independent symmetries should mostly be processed together with instance-specific symmetries rather than at the specification level, contrary to what has been suggested in the literature.

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