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However, none support persistence or instant recovery, and existing PM-based indexes typically evolve B+-trees without considering learned indexes.<\/jats:p>\n          <jats:p>This paper proposes APEX, a new PM-optimized learned index that offers high performance, persistence, concurrency, and instant recovery. APEX is based on ALEX, a state-of-the-art updatable learned index, to combine and adapt the best of past PM optimizations and learned indexes, allowing it to reduce PM accesses while still exploiting machine learning. Our evaluation on Intel DCPMM shows that APEX can perform up to ~15\u00d7 better than existing PM indexes and can recover from failures in ~42ms.<\/jats:p>","DOI":"10.14778\/3494124.3494141","type":"journal-article","created":{"date-parts":[[2022,2,5]],"date-time":"2022-02-05T00:31:46Z","timestamp":1644021106000},"page":"597-610","source":"Crossref","is-referenced-by-count":54,"title":["APEX"],"prefix":"10.14778","volume":"15","author":[{"given":"Baotong","family":"Lu","sequence":"first","affiliation":[{"name":"The Chinese University of Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jialin","family":"Ding","sequence":"additional","affiliation":[{"name":"Massachusetts Institute of Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric","family":"Lo","sequence":"additional","affiliation":[{"name":"The Chinese University of Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Umar Farooq","family":"Minhas","sequence":"additional","affiliation":[{"name":"Microsoft Research"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianzheng","family":"Wang","sequence":"additional","affiliation":[{"name":"Simon Fraser University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2022,2,4]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Paul Alcorn. 2019. 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