{ "schema_version": "0.6.0", "paper_id": "efficient-trace-analysis-parallelization", "page_url": "https://naser.github.io/research-publications/papers/efficient-trace-analysis-parallelization/", "title": "Efficient Methods for Trace Analysis Parallelization", "title_variants": [], "authors": [ "Fabien Reumont-Locke", "Naser Ezzati-Jivan", "Michel R. Dagenais" ], "author_details": [ { "name": "Fabien Reumont-Locke", "orcid": null, "profile_url": "https://dblp.org/pid/253/2979.html" }, { "name": "Naser Ezzati-Jivan", "orcid": "https://orcid.org/0000-0003-1435-6297", "profile_url": "https://naser.github.io/" }, { "name": "Michel R. Dagenais", "orcid": null, "profile_url": "https://dblp.org/pid/60/309.html" } ], "publication": { "year": 2019, "venue": "International Journal of Parallel Programming", "type": "journal article", "publication_date": "2019-02-09", "online_date": "2019-02-09", "print_date": "2019-12", "volume": "47", "issue": "5-6", "pages": "951-972", "article_number": null, "publisher": "Springer Science and Business Media LLC", "issn": [ "0885-7458", "1573-7640" ], "isbn": [], "crossref_type": "journal-article" }, "publication_type": "research paper", "status": "published_with_public_full_text", "canonical_source_url": "https://doi.org/10.1007/s10766-019-00631-4", "source_record_id": "efficient-methods-for-trace-analysis-parallelization-d3d00d5f6f", "identifiers": { "doi": "10.1007/s10766-019-00631-4" }, "abstract": null, "abstract_source": "No public abstract captured in the current catalog; summary limited to verified bibliographic metadata and the paper title.", "abstract_available": false, "scholar_eligibility": { "eligible": false, "basis": "not-eligible", "note": "The page is a discovery record; it does not claim Google Scholar article-host eligibility." }, "description": "The paper partitions Common Trace Format streams into balanced workloads, resolves cross-chunk state dependencies, and parallelizes stateful trace analyses with low synchronization cost.", "evidence_level": "full-text-reviewed", "evidence": { "source_basis": "full-text-reviewed", "coverage": "material paper sections", "summary_origin": "AI-assisted catalog editorial summary", "review_status": "catalog-reviewed; paper-author approval pending", "verified_on": "2026-08-09", "sources": [ { "note": "DBLP/DOI bibliographic record for 10.1007/s10766-019-00631-4" }, { "note": "author identity matched to Naser Ezzati-Jivan in the local research catalog" }, { "note": "Efficient parallelization PDF pp. 1-5: CTF/Babeltrace model, partitioning, state dependencies, and proposed map/reduce design" }, { "note": "Efficient parallelization PDF pp. 8-11: storage devices, 44,897,970-event trace, three analyses, speedups, and efficiencies" }, { "note": "Efficient parallelization PDF pp. 11-12: decoding and State History Tree limitations and future work" }, { "note": "local PDF hash verified in pdf-evidence/extraction-manifest.json" } ] }, "summary": { "core_contribution": "The paper partitions Common Trace Format streams into balanced workloads, resolves cross-chunk state dependencies, and parallelizes stateful trace analyses with low synchronization cost.", "problem": "Stateful analysis of LTTng/CTF traces is difficult to scale because stream and state dependencies constrain parallel work, while trace density and storage speed create load imbalance.", "method": "A hybrid packet-index/time partition divides trace streams into approximately balanced chunks. Workers initialize local state, analyze independently, and merge state chronologically; thread migrations are handled as inter-stream dependencies. The implementation uses Babeltrace/CTF decoding, OpenMP/TBB-style parallel execution, and QtConcurrent map/reduce in the real analyses.", "findings": "Three analyses-event count, CPU active time, and I/O-scale substantially on SSD storage. On the 44,897,970-event trace, 32 threads achieved 14.73x, 14.12x, and 18.15x speedup respectively; the corresponding efficiencies were 46.0%, 44.1%, and 56.7%. Storage and decoder overhead limit scaling beyond that point.", "limitations": "The evaluation combines a synthetic simulation with one 8-core trace and a small set of storage devices; the analyses are not a broad workload benchmark. The paper reports non-pipelined memory-operation and decoding bottlenecks, and no distributed or live deployment evaluation.", "future_work": "Improve Babeltrace decoding and copying/locking, parallelize kernel memory operations and State History Tree output, and extend the design to distributed and live trace analysis." }, "tags": [ "trace-analysis", "performance-engineering", "multicore-systems", "performance-optimization" ], "keywords": [ "trace analysis", "parallelization", "analysis scalability", "multicore processing", "CTF", "Babeltrace", "LTTng", "parallel efficiency", "State History Tree" ], "versions": [ { "id": "published-version", "label": "Published version", "relation": "version-of-record", "title": "Efficient Methods for Trace Analysis Parallelization", "url": "https://doi.org/10.1007/s10766-019-00631-4", "pdf_url": null, "status": "published", "canonical_for_citation": true }, { "id": "public-full-text", "label": "Public full text", "relation": "source-record", "title": "Efficient Methods for Trace Analysis Parallelization", "url": "https://publications.polymtl.ca/4212/11/2019_Reumont-Locke_Efficient_methods_trace_analysis_parallelization.pdf", "pdf_url": "https://publications.polymtl.ca/4212/11/2019_Reumont-Locke_Efficient_methods_trace_analysis_parallelization.pdf", "status": "public_full_text", "canonical_for_citation": false } ], "access": { "status": "published_with_public_full_text", "note": "The DOI is the canonical citation target; the public full-text link is an external source and is not redistributed here.", "license": null }, "resources": { "code": null, "data": null, "slides": null, "demo": null }, "citation_guidance": { "when_to_cite": "Cite this paper when your work uses or compares packet-index/time hybrid partitioning of stateful CTF trace analysis.", "points": [ "For packet-index/time hybrid partitioning of stateful CTF trace analysis.", "For local-state plus chronological-merge handling of trace dependencies and thread migrations.", "For the measured 32-thread SSD results: 18.15x I/O speedup and 56.7% I/O efficiency on a 44.9M-event trace.", "For the diagnosis that decoder copying/locks and Linux memory-operation serialization, rather than only raw disk bandwidth, constrain scaling." ], "canonical_version_id": "published-version" }, "provenance": { "metadata_verified_on": "2026-08-09", "metadata_source": [ "DBLP/DOI bibliographic record for 10.1007/s10766-019-00631-4", "author identity matched to Naser Ezzati-Jivan in the local research catalog", "Efficient parallelization PDF pp. 1-5: CTF/Babeltrace model, partitioning, state dependencies, and proposed map/reduce design", "Efficient parallelization PDF pp. 8-11: storage devices, 44,897,970-event trace, three analyses, speedups, and efficiencies", "Efficient parallelization PDF pp. 11-12: decoding and State History Tree limitations and future work", "local PDF hash verified in pdf-evidence/extraction-manifest.json" ], "summary_written_by": "AI-assisted", "summary_verified_by": "full-text-grounded catalog review; author approval pending", "linked_preprint_record": null, "author_order_note": null }, "batch": { "phase": 2, "batch_label": "expanded forty-paper release", "status": "included_in_expanded_catalog", "selected_at": "2026-08-09" } }