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 Q220132014

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-upA7/A15 Optimized bionic

LLVM wrapper

LLVM patches

profile and benchmark LLVM and GCC

NEON MM libraries

Open Crypto librariesOptimize Speech compcompiler-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_lockcd /sys/devices/system/cpu/cpu0/cpufreqecho userspace >scaling_governorecho 1700000 >scaling_max_freqecho 1700000 >scaling_min_freqecho 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) optimizationsTest AOSP

4.4.2Master + 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) optimizationsTest AOSP

4.4.2Master + BIONIC optimizations

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.orgMore about Linaro: http://www.linaro.org/about/

More about Linaro engineering: http://www.linaro.org/engineering/Linaro members: www.linaro.org/members