3 Search Results for "Roland, Perry"

Document
DOI: 10.4230/LIPIcs.ECOOP.2025.19
Profile-Guided Field Externalization in an Ahead-Of-Time Compiler

Authors: Sebastian Kloibhofer, Lukas Makor, Peter Hofer, David Leopoldseder, and Hanspeter Mössenböck

Published in: LIPIcs, Volume 333, 39th European Conference on Object-Oriented Programming (ECOOP 2025)

Abstract
Field externalization is a technique to reduce the footprint of objects by removing fields that most frequently contain zero or null. While researchers have developed ways to bring this optimization into the Java world, these have been limited to research compilers or virtual machines for embedded systems. In this work, we present a novel field externalization technique that uses information from static analysis and profiling to determine externalizable fields. During compilation, we remove those fields and define companion classes. These are used in case of non-default-value writes to the externalized fields. Our approach also correctly handles synchronization to prevent issues in multithreaded environments. We integrated our approach into the modern Java ahead-of-time compiler GraalVM Native Image. We conducted an evaluation on a diverse set of benchmarks that includes standard and microservice-based benchmarks. For standard benchmarks, our approach reduces the total allocated bytes by 2.76% and the maximum resident set size (max-RSS) by 2.55%. For microservice benchmarks, we achieved a reduction of 6.88% for normalized allocated bytes and 2.45% for max-RSS. We computed these improvements via the geometric mean. The median reductions are are 1.46% (alloc. bytes) and 0.22% (max-RSS) in standard benchmarks, as well as 3.63% (alloc. bytes) and 0.20% (max-RSS) in microservice benchmarks.
Cite as

Sebastian Kloibhofer, Lukas Makor, Peter Hofer, David Leopoldseder, and Hanspeter Mössenböck. Profile-Guided Field Externalization in an Ahead-Of-Time Compiler. In 39th European Conference on Object-Oriented Programming (ECOOP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 333, pp. 19:1-19:32, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kloibhofer_et_al:LIPIcs.ECOOP.2025.19,
  author =	{Kloibhofer, Sebastian and Makor, Lukas and Hofer, Peter and Leopoldseder, David and M\"{o}ssenb\"{o}ck, Hanspeter},
  title =	{{Profile-Guided Field Externalization in an Ahead-Of-Time Compiler}},
  booktitle =	{39th European Conference on Object-Oriented Programming (ECOOP 2025)},
  pages =	{19:1--19:32},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-373-7},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{333},
  editor =	{Aldrich, Jonathan and Silva, Alexandra},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECOOP.2025.19},
  URN =		{urn:nbn:de:0030-drops-233121},
  doi =		{10.4230/LIPIcs.ECOOP.2025.19},
  annote =	{Keywords: compilation, instrumentation, profiling, fields, externalization, memory footprint reduction, memory footprint optimization}
}
Document
Resource Paper
DOI: 10.4230/TGDK.2.2.4
FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset

Authors: Sheeba Samuel and Daniel Mietchen

Published in: TGDK, Volume 2, Issue 2 (2024): Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge, Volume 2, Issue 2

Abstract
The way in which data are shared can affect their utility and reusability. Here, we demonstrate how data that we had previously shared in bulk can be mobilized further through a knowledge graph that allows for much more granular exploration and interrogation. The original dataset is about the computational reproducibility of GitHub-hosted Jupyter notebooks associated with biomedical publications. It contains rich metadata about the publications, associated GitHub repositories and Jupyter notebooks, and the notebooks' reproducibility. We took this dataset, converted it into semantic triples and loaded these into a triple store to create a knowledge graph - FAIR Jupyter - that we made accessible via a web service. This enables granular data exploration and analysis through queries that can be tailored to specific use cases. Such queries may provide details about any of the variables from the original dataset, highlight relationships between them or combine some of the graph’s content with materials from corresponding external resources. We provide a collection of example queries addressing a range of use cases in research and education. We also outline how sets of such queries can be used to profile specific content types, either individually or by class. We conclude by discussing how such a semantically enhanced sharing of complex datasets can both enhance their FAIRness - i.e., their findability, accessibility, interoperability, and reusability - and help identify and communicate best practices, particularly with regards to data quality, standardization, automation and reproducibility.
Cite as

Sheeba Samuel and Daniel Mietchen. FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset. In Special Issue on Resources for Graph Data and Knowledge. Transactions on Graph Data and Knowledge (TGDK), Volume 2, Issue 2, pp. 4:1-4:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@Article{samuel_et_al:TGDK.2.2.4,
  author =	{Samuel, Sheeba and Mietchen, Daniel},
  title =	{{FAIR Jupyter: A Knowledge Graph Approach to Semantic Sharing and Granular Exploration of a Computational Notebook Reproducibility Dataset}},
  journal =	{Transactions on Graph Data and Knowledge},
  pages =	{4:1--4:24},
  ISSN =	{2942-7517},
  year =	{2024},
  volume =	{2},
  number =	{2},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/TGDK.2.2.4},
  URN =		{urn:nbn:de:0030-drops-225886},
  doi =		{10.4230/TGDK.2.2.4},
  annote =	{Keywords: Knowledge Graph, Computational reproducibility, Jupyter notebooks, FAIR data, PubMed Central, GitHub, Python, SPARQL}
}
Document
DOI: 10.4230/DagSemProc.09051.6
The Dagstuhl Core

Authors: Theodor Dumitrescu, Johannes Kepper, Andreas Kornstädt, Daniel Röwenstruck, Perry Roland, Craig Sapp, and Eleanor Selfridge-Field

Published in: Dagstuhl Seminar Proceedings, Volume 9051, Knowledge representation for intelligent music processing (2009)

Abstract
A substantial number of workshop attendees were involved in an extensive discussion of musical features for which software support is desirable in the context of scholarly research and applications (printing, analysis, editing of virtual materials, and other activities). Some ability to interchange data among applications is also highly desired. At the present time (early 2009) two XML descriptions for music have been extensively discussed at other meetings and workshops. These are MusicXML (commercial) and the Music Encoding Initiative (MEI; non-commercial). Over continuing discussion in ensuing days, a list of ``core'' features was developed by a group including Ted Dumitrescu, Johannes Kepper, Andreas Kornstaedt, Daniel Roewenstrunk, Perry Roland, and Eleanor Selfridge-Field. Additional input was received from Craig Sapp, who has translated extensively among four of the five data representation schemes (Humdrum Kern, MuseData, SCORE, and MusicXML) compared on the ``core'' feature list. (At the present time, no software to implement MEI is available.) The representation schemes were chosen because of the extensive repositories of music that already exist in them. The list is a work-in-progress. A wiki (restricted access) has been set up at http://muwimedial.de/dagstuhl-core/. After a short phase of refinement, it will be made available more widely. The Dagstuhl Core is a means to facilitate the use of existing and creation of new polyphonic CWN corpora (1650-1935) by educating users about the possibilities and limitations of graphemic, application- independent music data formats and the quality of programs that convert between them. It provides a feature list for each format/converter containing ``Yes''/``No''/``by Extension'' with a concise description how the given feature can (not) be realised in a given format / by a given converter. Serving as a frame of reference for parties interested in using encoded music, as well as creating corpora, formats, and converters, the vast majority of Dagstuhl Core features should carry a ``Yes'' or ``by Extension'' for a music format to be considered a core format for representing music in CWN from 1650 to 1935. The emphasis of the ``core'' is intended to be less on completeness than on ``essential features'' that any representation approach intended for use in scholarly work should be able to handle. It is currently focused on European classical music of the eighteenth and nineteenth centuries.
Cite as

Theodor Dumitrescu, Johannes Kepper, Andreas Kornstädt, Daniel Röwenstruck, Perry Roland, Craig Sapp, and Eleanor Selfridge-Field. The Dagstuhl Core. In Knowledge representation for intelligent music processing. Dagstuhl Seminar Proceedings, Volume 9051, p. 1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{dumitrescu_et_al:DagSemProc.09051.6,
  author =	{Dumitrescu, Theodor and Kepper, Johannes and Kornst\"{a}dt, Andreas and R\"{o}wenstruck, Daniel and Roland, Perry and Sapp, Craig and Selfridge-Field, Eleanor},
  title =	{{The Dagstuhl Core}},
  booktitle =	{Knowledge representation for intelligent music processing},
  pages =	{1--1},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9051},
  editor =	{Eleanor Selfridge-Field and Frans Wiering and Geraint A. Wiggins},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09051.6},
  URN =		{urn:nbn:de:0030-drops-19716},
  doi =		{10.4230/DagSemProc.09051.6},
  annote =	{Keywords: Music encoding, music interchange formats}
}
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