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Why does FUSE on Android suck?

Introduction FUSE (Filesystem in Userspace) is a very useful mechanism in many applications. The thing is, those applications should not be focused on performance in terms of actual data transfers. FUSE has many advantages implied by userspace sandboxing, but for sure performance wasn't the main design consideration. I'm not telling that it is a bad design or something wrong with FUSE itself. It is just focused on other aspects like security, stability and easiness of creating applications. The problem I'd like to discuss here is that Google decided to use FUSE as a frontend to actual data stored on the non-volatile memory. FUSE has been introduced in Android 4.4 to handle "emulated" storage. Before that, "emulated" storage path was mounted as VFAT. Here's how it looked on old ICS (output of mount command):

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grep、sed、awk练习题

文件:datafile Steve Blenheim:238-923-7366:95 Latham Lane, Easton, PA 83755:11/12/56:20300 Betty Boop:245-836-8357:635 Cutesy Lane, Hollywood, CA 91464:6/23/23:14500 Igor Chevsky:385-375-8395:3567 Populus Place, Caldwell, NJ 23875:6/18/68:23400 Norma Corder:397-857-2735:74 Pine Street, Dearborn, MI 23874:3/28/45:245700 Jennifer Cowan:548-834-2348:583 Laurel Ave., Kingsville, TX 83745:10/1/35:58900 Jon DeLoach:408-253-3122:123 Park St., San Jose, CA 04086:7/25/53:85100 Karen Evich:284-758-2857:23 Edgecliff Place, Lincoln, NB 92086:7/25/53:85100 Karen Evich:284-758-2867:23 Edgecliff Place, Lincoln, NB 92743:11/3/35:58200 Karen Evich:284-758-2867:23 Edgecliff Place, Lincoln, NB 92743:11/3/35:58200 Fred Fardbarkle:674-843-1385:20 Parak Lane, DeLuth, MN 23850:4/12/23:780900 Fred Fardbarkle:674-843-1385:20 Parak Lane, DeLuth, MN 23850:4/12/23:780900 Lori Gortz:327-832-5728:3465 Mirlo Street, Peabody, MA 34756:10/2/65:35200 Paco Gutierrez:835-365-1284:454 Easy Street, Decatur, IL 75732:2/28/53:123500 Ephram Hardy:293-259-5395:235 CarltonLane, Joliet, IL 73858:8/12/20:56700 James Ikeda:834-938-8376:23445 Aster Ave., Allentown, NJ 83745:12/1/38:45000 Barbara Kertz:385-573-8326:832 Ponce Drive, Gary, IN 83756:12/1/46:268500 Lesley Kirstin:408-456-1234:4 Harvard Square, Boston, MA 02133:4/22/62:52600 William Kopf:846-836-2837:6937 Ware Road, Milton, PA 93756:9/21/46:43500 Sir Lancelot:837-835-8257:474 Camelot Boulevard, Bath, WY 28356:5/13/69:24500 Jesse Neal:408-233-8971:45 Rose Terrace, San Francisco, CA 92303:2/3/36:25000 Zippy Pinhead:834-823-8319:2356 Bizarro Ave., Farmount, IL 84357:1/1/67:89500 Arthur Putie:923-835-8745:23 Wimp Lane, Kensington, DL 38758:8/31/69:126000 Popeye Sailor:156-454-3322:945 Bluto Street, Anywhere, USA 29358:3/19/35:22350 Jose Santiago:385-898-8357:38 Fife Way, Abilene, TX 39673:1/5/58:95600 Tommy Savage:408-724-0140:1222 Oxbow Court, Sunnyvale, CA 94087:5/19/66:34200 Yukio Takeshida:387-827-1095:13 Uno Lane, Ashville, NC 23556:7/1/29:57000 Vinh Tranh:438-910-7449:8235 Maple Street, Wilmington,

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Mila唐建团队开源大分子机器学习平台TorchProtein:分析蛋白质序列及结构数据,仅需一两行代码

机器之心专栏 机器之心编辑部 继药物研发机器学习平台 TorchDrug 之后,时隔一年,Mila 唐建团队开源了新的蛋白质机器学习平台 TorchProtein,这是目前第一个专门针对蛋白质研究的开源机器学习库。 蛋白质是生物体的重要组成成分。理解蛋白质的结构与生化性质,对于药物研发和人类健康有着不可估量的意义。传统基于生物实验的蛋白质研究不仅周期漫长,而且开销巨大。相比之下,机器学习技术则能大幅降低蛋白质研究的周期和开销,为新药的研发带来革命性的影响。然而,基于机器学习的蛋白质研究,涉及到生物领域知识、

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