Search engine for discovering works of Art, research articles, and books related to Art and Culture
ShareThis
Javascript must be enabled to continue!

Optimization based on LLVM global instruction selection

View through CrossRef
Abstract Instruction selection is a key component of code generation. High-quality instruction selection has a great impact on the size and quality of the generated code. The existing instruction selection technology is mostly limited to a single statement or a single basic block, and the global instruction selection based on LLVM degrades the entire function in the form of SSA. Global instruction selection optimization based on LLVM is implemented on Shenwei platform, including global instruction merge optimization based on cost model, register bank selection optimization and instruction locality optimization. Through the test of SPEC CPU2006, Experimental results show that the average speed-up ratio before and after the optimization of global instruction selection based on LLVM is 1.08, and the maximum speed-up ratio is 1.36. In addition, when the quality of the generated code is equivalent, the global instruction selection is compared with the default instruction selection, the LLC compilation speed is increased by an average of 20%, and the entire compilation cycle is increased by an average of 6%-8%.
Title: Optimization based on LLVM global instruction selection
Description:
Abstract Instruction selection is a key component of code generation.
High-quality instruction selection has a great impact on the size and quality of the generated code.
The existing instruction selection technology is mostly limited to a single statement or a single basic block, and the global instruction selection based on LLVM degrades the entire function in the form of SSA.
Global instruction selection optimization based on LLVM is implemented on Shenwei platform, including global instruction merge optimization based on cost model, register bank selection optimization and instruction locality optimization.
Through the test of SPEC CPU2006, Experimental results show that the average speed-up ratio before and after the optimization of global instruction selection based on LLVM is 1.
08, and the maximum speed-up ratio is 1.
36.
In addition, when the quality of the generated code is equivalent, the global instruction selection is compared with the default instruction selection, the LLC compilation speed is increased by an average of 20%, and the entire compilation cycle is increased by an average of 6%-8%.

Related Results

Selection Gradients
Selection Gradients
Natural selection and sexual selection are important evolutionary processes that can shape the phenotypic distributions of natural populations and, consequently, a primary goal of ...
Poems
Poems
poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poems selection poem...
Instruction Tuning on Large Language Models to Improve Reasoning Performance
Instruction Tuning on Large Language Models to Improve Reasoning Performance
The growing demand for natural language processing models capable of understanding and executing complex instructions has driven significant advancements in model fine-tuning tech...
Hedging against Uncertain Future Development Plans in Closed-loop Field Development Optimization
Hedging against Uncertain Future Development Plans in Closed-loop Field Development Optimization
Abstract Optimization has received considerable attention in oilfield development studies. A major difficulty is related to handling the uncertainty that can be intr...
Pengaruh Pemikiran Raymond C Davis tentang Bibliography Instruction terhadap Konsep Literasi Informasi
Pengaruh Pemikiran Raymond C Davis tentang Bibliography Instruction terhadap Konsep Literasi Informasi
Bibliography instruction pertama kali digagas oleh Raymond C. Davis pada tahun 1881. Sejak dilaksanakan pada tahun 1881 bibliography instruction masih tetap dilakukan, meskipun kem...
A new type bionic global optimization: Construction and application of modified fruit fly optimization algorithm
A new type bionic global optimization: Construction and application of modified fruit fly optimization algorithm
Fruit fly optimization algorithm, which is put forward through research on the act of foraging and observing groups of fruit flies, has some merits such as simplified operation, st...
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
Modeling Hybrid Metaheuristic Optimization Algorithm for Convergence Prediction
The project aims at the design and development of six hybrid nature inspired algorithms based on Grey Wolf Optimization algorithm with Artificial Bee Colony Optimization algorithm ...

Back to Top