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LCA14: LCA14-205: Optimizing SQLite for Android mobile
 

LCA14: LCA14-205: Optimizing SQLite for Android mobile

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Resource: LCA14

Resource: LCA14
Name: LCA14-205: Optimizing SQLite for Android mobile
Date: 04-03-2014
Speaker: Khasim Syed Mohammed
Video: https://www.youtube.com/watch?v=iobAwaEu1oM

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    LCA14: LCA14-205: Optimizing SQLite for Android mobile LCA14: LCA14-205: Optimizing SQLite for Android mobile Presentation Transcript

    • Tue-4-Mar, 11:15am, Khasim Syed Mohammed LCA14-205: Optimizing SQLite for Android mobile
    • www.linaro.org Boot Time Reduction investigation Back ground of this work FutureQ1 Q22013 2014 12-DEC-2013 Android Optimizations Cortex-A7/A15 Investigation Q3 Q4 Power Optimization investigation fdlibm sqlite Migrate AOSP to latest zlib guava LLVM / Clang Android explore libart system start-up A7/A15 Optimized bionic LLVM wrapper LLVM patches profile and benchmark LLVM and GCC NEON MM libraries Open Crypto libraries Optimize Speech comp compiler-rt Q4 Closed Development Drafting Community/ External Upstream Approved Scheduled Ongoing
    • www.linaro.org Agenda Progress update ■ What’s the approach ■ Our findings so far ■ Remaining work NOTE : This is still a work in progress - estimated date of closure end of April 2014
    • www.linaro.org What is SQLite ? ■ SQLite is a software library that implements a self- contained, serverless, zero-configuration,transactional SQL database engine. ■ SQLite is the most widely deployed SQL database engine in the world. ■ The source code for SQLite and more information available on sqlite.org
    • www.linaro.org Do we really need database in Mobile devices ?
    • Do we need database in Mobile device ? Source : http://gigaom.com/2013/05/11/welcome-to-the-new-and-fast-growing-ecosystem-of-mobile-business-apps/ - Mobile apps are transforming the business software market - Business / Enterprise apps are getting built for “mobile first” - Most of these applications need data base management system on mobile -basic requirement: Large/Small amount of data should be stored and important data should be retrieved from a large database in the least possible time.
    • • Explore the folder external/sqlite in Android sources • Finding possible ways of improving the overall performance of SQlite • Ensure that we don’t break any compatibility Expectation
    • • Understand how SQLite operates and find it’s dependencies. Our approach Commands Use CPU to run Queries eMMC access to store or retrieve information • Possible optimizations areas : • Data : Improve data throughput • CPU : Utilize CPU efficiently to run queries faster and reduce CPU utilization by offloading the SQL queries to other cores if possible.
    • • RL Benchmark is an SQLite benchmark that runs thousands of insert, select, update, and delete functions - the same functions Android uses to store data. • The resulting number is the total amount of time (in seconds) that it took for your device to run through all the tests. • The faster it completed it, the faster your device stores and retrieves data; thus, lower is better. Tools / Measurement Also looked at SQL Bench, Andro Bench, but this one was most widely used by app developers.
    • • The following functions from cortex-strings optimizations from Linaro perform better than AOSP • strlen • memchr • memcpy Learnings Test with out optimization with optimization 500000000 * strlen(15*a) 8.563289 7.3658144 1000000 * strlen(15000*a) 4.795874 4.4586328 10000000 * memcpy of 15000 bytes 14.0750624 12.276912 900000000 * memcpy of 15 bytes 3.1883678 3.1854456 https://wiki.linaro. org/Platform/Android/CortexStringsInBionic Thanks to Bero @ Linaro.org NOTE: SQLite source has around a. 240 “memcpy” b. 60 “strlen”
    • • Accelerating SQL Database Operations on a GPU is possible (Example with CUDA) - Thanks to Tom Gall @ Linaro.org for sharing the information • http://pbbakkum.com/db/ • Nexus 10 device can be prevented from suspending or entering lower power modes by echo benchmark >/sys/power/wake_lock cd /sys/devices/system/cpu/cpu0/cpufreq echo userspace >scaling_governor echo 1700000 >scaling_max_freq echo 1700000 >scaling_min_freq echo 1700000 >scaling_setspeed • From 4.3 onwards Android supports FSTRIM, that basically calls DISCARD command - This marks all the unused blocks on the underlying flash device as unused, so the device performs better. Learnings
    • • On Nexus 10 with AOSP master + Linaro patches for BIONIC optimizations • Preventing the device to enter lower power states Performance improved by 15 % Observation
    • BIONIC (memcpy, strlen) optimizations Test AOSP 4.4.2 Master + BIONIC optimizations Master + BIONIC optimization + suspend disabled 1000 INSERTs 8.3 7.328 7.027 25000 INSERTs in a transaction 2.1 2.026 1.997 25000 INSERTs into an indexed table 2.5 2.012 1.957 100 SELECTs without an index 0.042 0.012 0.008 100 SELECTs on a string comparison 0.012 0.008 0.015 Creating an index 0.428 0.305 0.312 5000 SELECTs with an index 0.718 0.556 0.515 1000 UPDATEs without an index 2.38 2.138 2.068
    • BIONIC (memcpy, strlen) optimizations Test AOSP 4.4.2 Master + BIONIC optimizatio ns Master + BIONIC optimization + suspend disabled 25000 UPDATEs with an index 3.144 3.197 2.965 INSERTs from a SELECT 0.58 0.635 0.552 DELETE without an index 0.63 0.509 0.509 DELETE with an index 0.5 0.468 0.48 DROP TABLE 0.29 0.309 0.292 OVER ALL 21.747 19.503 18.697
    • • On Nexus 7 with AOSP master • Enabling ART instead of Dalvik Performance improved by 11 % (surprising ? despite SQLite is a native library, the Java API imposes an significant overhead) HOWEVER, for some reason ART on Nexus 10 failed to give any better performance - maybe ART on Nexus 10 is still not optimized efficiently Observation
    • Lib ART (Nexus 7) Test Dalvik ART 1000 INSERTs 10.594 10.369 25000 INSERTs in a transaction 3.96 3.36 25000 INSERTs into an indexed table 3.93 3.336 100 SELECTs without an index 0.026 0.016 100 SELECTs on a string comparison 0.029 0.016 Creating an index 0.602 0.566 5000 SELECTs with an index 1.222 0.81 1000 UPDATEs without an index 4.357 3.648
    • Lib ART (Nexus 7) Test Dalvik ART 25000 UPDATEs with an index 6.079 5.038 INSERTs from a SELECT 0.935 0.96 DELETE without an index 0.886 0.915 DELETE with an index 0.776 0.809 DROP TABLE 0.462 0.433 OVER ALL 33.867 30.279
    • ● Android uses 3.7.11 and SQLite.org is on 3.8.3.1 ○ Lot of bug fixes and optimizations - trying since yesterday … ○ Will file a AOSP bug once we try it out to migrate SQLite in AOSP to latest. ● libsql depends on following libraries - need to find if we could optimize any of these routines. ○ libdl.so ○ liblog.so ○ libicuuc.so ○ libicui18n.so ○ libutils.so ○ libc.so ○ libstdc++.so ○ libm.so ● Android provides many APIs and FLAGS for APP developers like WRITE_AHEAD (basically buffers multiple I/O access into one and reads/writes in one chunk) ○ Many books, tutorials available to app developers to refer to. Next steps
    • • Accelerating SQL Database Operations on a GPU - Should we explore this ? • The research paper uses CUDA • Linaro GWG team has a card to implement the same with OpenCL • Android supports only renderscript (not compatible with OpenCL or CUDA) • Renderscript is mainly used in JAVA layers to leverage hardware optimizations, but SQL code is already a “C” code, introducing renderscript calls is something we haven’t done before. • Is this worth of an effort ? DEBATE … • May be wait till we get some numbers to compare with OpenCL. Next steps - “Need a new slide for this one”
    • Please feel free to mail us on linaro-android@lists.linaro.org or IRC (freenode) #linaro-android Any questions ?
    • More about Linaro Connect: http://connect.linaro.org More about Linaro: http://www.linaro.org/about/ More about Linaro engineering: http://www.linaro.org/engineering/ Linaro members: www.linaro.org/members