The SOM family

Haupt, Michael; Hirschfeld, Robert; Pape, Tobias; Gabrysiak, Gregor; Marr, Stefan; Bergmann, Arne; Heise, Arvid; Kleine, Matthias; Krahn, Robert

doi:10.1145/1822090.1822098

Cited by 14 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [24], Marr and Ducasse stated that a significant difference between RPython and Truffle is the number of optimizations a language implementer needs to apply in order to reach the same level of performance. In their experiments, SOM [19] built with RPython achieves excellent performance without adding many optimizations. On the other hand, SOM built with Truffle without any additional optimizations performs one order of magnitude worse than the meta-tracing.…”

Section: Meta-tracing Jit Compilation Techniquementioning

confidence: 99%

Amalgamating different JIT compilations in a meta-tracing JIT compiler framework

Izawa

Masuhara

2020

Proceedings of the 16th ACM SIGPLAN International Symposium on Dynamic Languages

View full text Add to dashboard Cite

Most virtual machines employ just-in-time (JIT) compilers to achieve high-performance. Trace-based compilation and method-based compilation are two major compilation strategies in JIT compilers. In general, the former excels in compiling programs with more in-depth method calls and more dynamic branches, while the latter is suitable for a wide range of programs. Some previous studies have suggested that each strategy has its advantages and disadvantages,and there is no clear winner. In this paper, we present a new approach, namely, the meta-hybrid JIT compilation strategy, mixing the two strategies in a meta-tracing JIT compiler. As a prototype, we implemented a simple meta-tracing JIT compiler framework called BacCaml based on the MinCaml compiler by following RPython's architecture. We also report that some programs ran faster by the hybrid compilation in our experiments. CCS Concepts: • Software and its engineering → Justin-time compilers.

show abstract

Section: Meta-tracing Jit Compilation Techniquementioning

confidence: 99%

Amalgamating different JIT compilations in a meta-tracing JIT compiler framework

Izawa

Masuhara

2020

Proceedings of the 16th ACM SIGPLAN International Symposium on Dynamic Languages

View full text Add to dashboard Cite

show abstract

Test Quality Feedback Improving Effectivity and Efficiency of Unit Testing

Perscheid

Cassou

Hirschfeld

2012

2012 10th International Conference on Creating, Connecting and Collaborating Through Computing

View full text Add to dashboard Cite

International audienceWriting unit tests for a software system enhances the confidence that a system works as expected. Since time pressure often prevents a complete testing of all application details developers need to know which new tests the system requires. Developers also need to know which existing tests take the most time and slow down the whole development process. Missing feedback about less tested functionality and reasons for long running test cases make it, however, harder to create a test suite that covers all important parts of a software system in a minimum of time. As a result a software system may be inadequately tested and developers may test less frequently. Our approach provides test quality feedback to guide developers in identifying missing tests and correcting low-quality tests. We provide developers with a tool that analyzes test suites with respect to their effectivity (e.g., missing tests) and efficiency (e.g., time and memory consumption). We implement our approach, named PathMap, as an extended test runner within the Squeak Smalltalk IDE and demonstrate its benefits by improving the test quality of representative software systems

show abstract

Are We There Yet?: Simple Language Implementation Techniques for the 21st Century

2014

Self Cite

View full text Add to dashboard Cite

Abstract-With the rise of domain-specific languages (DSLs), research in language implementation techniques regains importance. While DSLs can help to manage the domain's complexity, it is rarely affordable to build highly optimizing compilers or virtual machines, and thus, performance remains an issue. Ideally, one would implement a simple interpreter and still reach acceptable performance levels. RPython and Truffle are two approaches that promise to facilitate language implementation based on simple interpreters, while reaching performance of the same order of magnitude as highly optimizing virtual machines. In this case study, we compare the two approaches to identify commonalities, weaknesses, and areas for further research to improve their utility for language implementations.

show abstract

The SOM family

Cited by 14 publications

References 7 publications

Amalgamating different JIT compilations in a meta-tracing JIT compiler framework

Amalgamating different JIT compilations in a meta-tracing JIT compiler framework

Test Quality Feedback Improving Effectivity and Efficiency of Unit Testing

Are We There Yet?: Simple Language Implementation Techniques for the 21st Century

Contact Info

Product

Resources

About