{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-10534590","patent":{"patent_number":"US-10534590","title":"Dynamic recompilation techniques for machine learning programs","assignee":null,"inventors":[],"filing_date":"2017-04-28T00:00:00.000Z","publication_date":"2020-01-14T00:00:00.000Z","cpc_codes":["G06F","G06F","G06N"],"num_claims":20,"abstract":"The embodiments described herein relate to recompiling an execution plan of a machine-learning program during runtime. An execution plan of a machine-learning program is compiled. In response to identifying a directed acyclic graph of high-level operations (HOP DAG) for recompilation during runtime, the execution plan is dynamically recompiled. The dynamic recompilation includes updating statistics and dynamically rewriting one or more operators of the identified HOP DAG, recomputing memory estimates of operators of the rewritten HOP DAG based on the updated statistics and rewritten operators, constructing a directed acyclic graph of low-level operations (LOP DAG) corresponding to the rewritten HOP DAG based in part on the recomputed memory estimates, and generating runtime instructions based on the LOP DAG."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Dynamic recompilation techniques for machine learning programs","description":"The embodiments described herein relate to recompiling an execution plan of a machine-learning program during runtime. An execution plan of a machine-learning program is compiled. In response to ident","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-10534590","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-10534590","citation_suggestion":"Patentable. \"Dynamic recompilation techniques for machine learning programs\" (US-10534590). https://patentable.app/patents/US-10534590","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-10534590","json":"https://patentable.app/api/llm-context/US-10534590","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T20:11:38.370Z"}