{ "authors": [ { "name": "0728a400aa1c86fe" } ], "bib_ref": "cm:29db2248aba45e59:1943b3f46fabaee4", "document_urls": [ "http://arxiv.org/abs/1308.2410", "http://hal.inria.fr/hal-00850880" ], "local_bib": "doc.bib", "local_doc": "doc.pdf", "notes": [ { "bold": "yes", "italic": "yes", "note": "Extended journal version: [$#cm_29db2248aba45e59_6f40bc99c4f7df58#$]" }, { "italic": "yes", "note": "This work summarizes my long-term vision on collaborative, systematic and reproducible benchmarking, optimization and co-design of computer systems across all software and hardware layers using public Collective Mind repository of knowledge, common plugin-based autotuning framework, big data, predictive analytics (machine learning, data mining, statistical analysis, feature detection), crowdsourcing and collective intelligence" }, { "bold": "yes", "italic": "yes", "note": "This work extends my previous article [$#cm_29db2248aba45e59_0c44d9a2db3de3c9#$]" }, { "italic": "yes", "note": "Should be publicly available at some point in autumn, 2014" }, { "italic": "yes", "note": "Related Collective Mind infrastructure and repository [$#cm_d76ac3bb9a3f744c_bd5c924415bae775#$]" }, { "bold": "yes", "italic": "yes", "note": "This work supports my initiative on open research and publication model where all experimental results and related material is continuously shared, validated and improved by the community [$#cm_29db2248aba45e59_40a4b58adfb594a8#$]. To set up an example, I continue sharing all benchmarks, datasets, tools, models and experimental results in Collective Mind repository (c-mind.org/repo)" } ], "place": "France", "publish_iso_date": "2013-06-01", "reproducible": "yes", "title": "Collective Mind: cleaning up the research and experimentation mess in computer engineering using crowdsourcing, big data and machine learning", "type": { "name": "tech_report", "peer_reviewed": "no", "scope": "international" }, "when": "2013", "where": "INRIA technical report HAL-00850880" }