JIT Compilation Policy on Single-Core and Multi-core Machines

2011 ◽  
Author(s):  
Prasad A Kulkarni ◽  
Jay Fuller
Keyword(s):  
Jit Compilation

scholarly journals Type stability in Julia: avoiding performance pathologies in JIT compilation

2021 ◽  
Vol 5 (OOPSLA) ◽  
pp. 1-26
Author(s):  
Artem Pelenitsyn ◽  
Julia Belyakova ◽  
Benjamin Chung ◽  
Ross Tate ◽  
Jan Vitek
Keyword(s):  
Programming Language ◽  
Corpus Analysis ◽  
Formal Definition ◽  
Compiler Optimizations ◽  
Definition Of ◽  
High Level ◽  
Jit Compilation

As a scientific programming language, Julia strives for performance but also provides high-level productivity features. To avoid performance pathologies, Julia users are expected to adhere to a coding discipline that enables so-called type stability. Informally, a function is type stable if the type of the output depends only on the types of the inputs, not their values. This paper provides a formal definition of type stability as well as a stronger property of type groundedness, shows that groundedness enables compiler optimizations, and proves the compiler correct. We also perform a corpus analysis to uncover how these type-related properties manifest in practice.

The impact of optional type information on jit compilation of dynamically typed languages

2012 ◽  
Vol 47 (2) ◽  
pp. 13-24 ◽  
Author(s):  
Mason Chang ◽  
Bernd Mathiske ◽  
Edwin Smith ◽  
Avik Chaudhuri ◽  
Andreas Gal ◽  
...  
Keyword(s):  
The Impact ◽  
Type Information ◽  
Jit Compilation ◽  
Typed Languages

scholarly journals Of JavaScript AOT compilation performance

2021 ◽  
Vol 5 (ICFP) ◽  
pp. 1-30
Author(s):  
Manuel Serrano
Keyword(s):  
Performance Analysis ◽  
Just In Time ◽  
Design And Implementation ◽  
Dynamic Languages ◽  
Academic Publications ◽  
Jit Compilation ◽  
A Performance

The fastest JavaScript production implementations use just-in-time (JIT) compilation and the vast majority of academic publications about implementations of dynamic languages published during the last two decades focus on JIT compilation. This does not imply that static compilers (AoT) cannot be competitive; as comparatively little effort has been spent creating fast AoT JavaScript compilers, a scientific comparison is lacking. This paper presents the design and implementation of an AoT JavaScript compiler, focusing on a performance analysis. The paper reports on two experiments, one based on standard JavaScript benchmark suites and one based on new benchmarks chosen for their diversity of styles, authors, sizes, provenance, and coverage of the language. The first experiment shows an advantage to JIT compilers, which is expected after the decades of effort that these compilers have paid to these very tests. The second shows more balanced results, as the AoT compiler generates programs that reach competitive speeds and that consume significantly less memory. The paper presents and evaluates techniques that we have either invented or adapted from other systems, to improve AoT JavaScript compilation.

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