Android* on Intel platforms
And what it means for you, developers.
Agenda
• And what it means for you, developers.
Powering the next generation of smartphones and feature
phones, tablets, wearables, and connected devices with
leading-edge technologies
Tablet Product Roadmap …
2012
In the game
2013
IA Tablets ramping
Motorola Razr i w/ Medfield
Windows 8 connected standby tablets TTM
Samsung Galaxy Tab 3 on Clover Trail+
Bay Trail-T Accelerating: ~25 wins & counting
2014
14nm Coming Soon
“Across the board Intel manages a huge advantage
…The x86 power myth has been busted.”
--Anandtech* 12/24/12
Intel HD Graphics
22nm, Quad Core
Targeting significant graphics
performance increase over Bay Trail
Intel HD Graphics
“Clover Trail+”
“Clover Trail”
“Bay Trail”
Excellent Android Performance 2X Faster CPU & up to 4.8X 1
Faster Graphics than Z2760
Intel XMM 7160 LTE option
Intel XMM 7160 LTE option
Up to 4k x 2k Display
Rich security, context, and imaging
capability set built-in
Intel XMM 7260 LTE w/CA
“Medfield”
Product timing aligned to year of introduction
1For
performance details, see https://www-ssl.intel.com/content/www/us/en/benchmarks/atom/atom-tablet-z3770-infographic.html
Smartphones with Intel Inside - 2012
Z2460
Orange* San Diego (UK)
Orange* avec Intel Inside (FR)
Lava* Xolo X900
Motorola* RAZR i
ZTE* Grand X IN
Megafon* Mint
Lenovo*
K800
Smartphones with Intel Inside - 2013
Z2420
Z2560
Z2580
Lenovo* K900 – 5.5”
Intel® Yolo
ASUS Fonepad™ Note FHD - 6”
Etisalat E-20*
ZTE* Geek – 5”
Acer* Liquid C1
…
ZTE* Grand X2 In – 4.5”
Tablets with Intel Inside - 2013
ASUS* MeMO Pad FHD 10”
ASUS* Fonepad™ 7”
(Z2560)
(Z2420/Z2460)
Samsung* Galaxy™ Tab 3 10.1”
(Z2560)
Dell Venue 7 and 8
Clover Trail Plus dual-core
Atom chip
Future Android* platforms based on
Intel* Silvermont microarchitecture
New 22nm tri-gate microarchitecture
~3X more peak performance or ~5X lower power than previous Atom microarchitecture
Intel® Atom™ Processor Z3000 Series
(Bay Trail)
Next Generation Tablets
Merrifield
Next Generation Smartphones
Our devices are already fully compatible
with established Android* ecosystem
•
Android*
Dalvik*
apps
• These will directly work, Dalvik has been
optimized for Intel® platforms.
Android Runtime
Dalvik Virtual
Machine
Core Libraries
• Android NDK apps
• Most will run without any recompilation on consumer platforms.
• Android NDK provides an x86 toolchain since 2011
• A simple recompile using the Android NDK yields the best
performance
• If there is specific processor dependent code, porting may be
necessary
Most of the time, it just works !
What we are working on for Android*
Key AOSP and
Kernel
Contributor
Optimized Drivers
& Firmware
Porting and
Optimizing
Browser and Apps
NDK Apps
Bridging
Technology
Highly Tuned
Dalvik Runtime
64
bit
64-Bit
How to target multiple platforms
(incl. x86) from NDK apps ?
INTEL CONFIDENTIAL
Configuring NDK Target ABIs
If you have the source code of your native libraries, you can compile it for several CPU
architectures by setting APP_ABI to all in the Makefile “jni/Application.mk”:
APP_ABI=all
Put APP_ABI=all inside
Application.mk
Run ndk-build…
ARM v7a libs are built
ARM v5 libs are built
x86 libs are built
mips libs are built
The NDK will generate optimized code for all target ABIs
You can also pass APP_ABI variable directly to ndk-build, and specify each ABI:
ndk-build APP_ABI=x86
Packaging APKs for Multiple CPU
Architectures
Two options:
PIDs
PSI
TS
• One package for all (“fat binary”)
• Embed native libraries for each architecture in one APK
• Easiest and preferred way to go
• Multiple APKs
• One APK per architecture
• If you have good reasons to do so (i.e., your fat binary APK
would be larger than 50MB)
Fat Binaries
By default, an APK contains libraries for
every supported ABIs.
libs/armeabi
Use lib/armeabi libraries
libs/armeabi-v7a
libs/x86
…
APK file
Use lib/armeabi-v7a
libraries
Use lib/x86
libraries
The application will be filtered during installation (after download)
Multiple APKs
• Google Play* supports multiple APKs for the
same application.
• What compatible APK will be chosen for a device
entirely depends on the android:VersionCode
• Using this convention, the chosen APK will be the
one that run best on the device:
3rd party libraries x86 support
Game engines/libraries with x86 support:
• Havok Anarchy SDK: android x86 target available
• Unreal Engine 3: android x86 target available
• Marmalade: android x86 target available
• Cocos2Dx: set APP_ABI in Application.mk
• FMOD: x86 lib already included, set ABIs in Application.mk
• AppGameKit: x86 lib already included, set ABIs in Application.mk
• libgdx: x86 lib available from nightly builds
• …
No x86 support but works on consumer devices:
• Corona
• Unity
Software and Services Group
Porting processor specific
code to x86 on Android*
INTEL CONFIDENTIAL
SIMD Instructions
• NEON* instruction set on ARM* platforms
• MMX™, Intel® SSE, SSE2, SSE3, SSSE3 on Intel® Atom™
processor based platforms
• http://intel.ly/10JjuY4 - NEONvsSSE.h : wrap NEON functions
and intrinsics to SSE3 – 100% covered
//******* definition sample *****************
int8x8_t
vadd_s8(int8x8_t a, int8x8_t b); // VADD.I8 d0,d0,d0
#ifdef USE_MMX
#define vadd_s8 _mm_add_pi8
//MMX
#else
#define vadd_s8 _mm_add_epi8
#endif
//…
Supplemental Streaming SIMD Extensions (SSSE)
Intel® Streaming SIMD Extensions (Intel® SSE)
Optimization Notice
Intel's compilers may or may not optimize to the same degree for non-Intel microprocessors for optimizations that are not unique to Intel microprocessors. These
optimizations include SSE2, SSE3, and SSSE3 instruction sets and other optimizations. Intel does not guarantee the availability, functionality, or effectiveness of any
optimization on microprocessors not manufactured by Intel. Microprocessor-dependent optimizations in this product are intended for use with Intel microprocessors. Certain
optimizations not specific to Intel microarchitecture are reserved for Intel microprocessors. Please refer to the applicable product User and Reference Guides for more
information regarding the specific instruction sets covered by this notice.
Notice revision #20110804
Memory Alignment
By default
struct TestStruct {
int mVar1;
long long mVar2;
int mVar3;
};
Easy fix
struct TestStruct {
int mVar1;
long long mVar2 __attribute__ ((aligned(8)));
int mVar3;
};
Intel® Tools for Android*
apps developers
Most of our tools are relevant even if you’re not targeting x86 platforms!
INTEL CONFIDENTIAL
Faster Android* Emulation on
Intel® Architecture Based Host PC
Pre-built Intel® Atom™ Processor
Images
• Android* SDK manager has x86 emulation
images built-in
• To emulate an Intel Atom processor
based Android phone, install the “Intel
Atom x86 System Image” available in the
Android SDK Manager
Much Faster Emulation
• Intel® Hardware Accelerated Execution
Manager (Intel® HAXM) for Mac and
Windows uses Intel® Virtualization
Technology (Intel® VT) to accelerate
Android emulator
• Intel VT is already supported in Linux* by
qemu -kvm
Intel x86 Atom
System Image
Intel x86 Emulator
Accelerator
Software and Services Group
Intel® Threading Building Blocks (TBB)
• Specify tasks instead of manipulating threads
• Intel® Threading Building Blocks (Intel® TBB) maps your logical
tasks onto threads with full support for nested parallelism
• Targets threading for scalable performance
• Uses proven efficient parallel patterns
• Uses work-stealing to support the load balance of unknown
execution time for tasks
• Open source and licensed versions available
on Linux*, Windows*, Mac OS X*, Android*…
Open Source version available on: threadingbuildingblocks.org
Licensed version available on: software.intel.com/en-us/intel-tbb
Intel® TBB - Example
#include <tbb/parallel_reduce.h>
#include <tbb/blocked_range.h>
Lambda function with
Computes
Calculating
Defining
Defining
reduction
a areduction
apart
one-ofover
Pi
range and initial value as
dimensional
within
function
a the
range
range
ranger
parm
double getPi() {
const int num_steps = 10000000;
const double step = 1./num_steps;
double pi = tbb::parallel_reduce(
tbb::blocked_range<int>(0, num_steps), //Range
double(0), //Value
//function
[&](const tbb::blocked_range<int>& r, double current_sum ) ->
double {
for (size_t i=r.begin(); i!=r.end(); ++i) {
double x = (i+0.5)*step;
current_sum += 4.0/(1.0 + x*x);
}
return current_sum; // updated value of the accumulator
},
[]( double s1, double s2 ) { //Reduction
return s1+s2;
}
);
return pi*step;
}
Intel® Graphics Performance Analyzers
• Profiles performance and Power
• Real-time charts of CPU, GPU
and power metrics
• Conduct real-time experiments
with OpenGL-ES* (with state
overrides) to help narrow down
problems
• Triage system-level
performance with CPU, GPU and
Power metrics
Available freely on intel.com/software/gpa
Intel® Graphics Performance
Analyzers
1. Install APK, and
connect to Host PC via
adb
2. Run Intel® GPA System Analyzer
on development machine
3. View Profile
Intel® HTML5 Development
Environment (XDK NEW)
• Great tools for free
• Convenient, cloud-based build tool lets you target all popular
platforms & app stores
• Write once, run anywhere; code once, debug once, publish
everywhere
more on: html5dev-software.intel.com
Software and Services Group
Other tools and libs for Android*
• Intel IPP Preview
• Intel Compiler
Software and Services Group
Call to Action
Software and Services Group
Backup
INTEL CONFIDENTIAL
Apps
GPU & Video support
for canvas operations
Home
Application
Framework
User
Experience
Apps
Optimizing Android for Intel®
Atom™ Processor-Based Devices
Contacts
SKIA
and openGLWindows*
Activity
Manager
Manager
optimizations
Telephony
Manager
Package Manager
Phone
Browser
Extensive middleware
development
in imaging,
…
Content Providers
View System
media and DRM deliver
compelling media
Resource
Location Manager
Notification Manager
experiences
Manager
Operating
System
Middleware
Libraries
Android* Runtime
Surface Manager
Media
Framework
SQLite
OpenGL* ES
FreeType
WebKit
SGL
SSL
libc
Memory Optimizations, AVI,
DivX*, Display
and ASF
container types,
Driver
WMV /VC-1 decoder. Live
Streaming optimizations, HDMI
Driver
andKeypad
WiDI Extended
Video
Modes, Video Playback DRM
…
Core Libraries
Apply our extensive
experience
optimizing Java* to
the Dalvik* VM
Dalvik Virtual Machine
…
Linux* Kernel
Camera Driver
We optimize web
technologies such as
HTML 5, WebKit and
JavaScript†
Flash Memory
Driver
Enhanced debugging
and logging
WiFi Driver
Audio Drivers
Binder (IPC) Driver
IA assembly
optimizations
Drivers validated &
optimized for power
& memory footprint
Power Management
†Based on third party validation and sampling of Android apps using specific computer systems and/or components and reflect the approximate performance of Intel products as measured by those tests.
Any difference in system hardware or software design or configuration may affect actual performance and/or results.
Components of TBB (version 4.2)
Parallel algorithms
Flow Graphs
parallel_for
parallel_for_each
parallel_reduce
parallel_do
parallel_scan
parallel_pipeline & filters
parallel_sort
parallel_invoke
functional nodes
(source, continue, function)
buffering nodes
(buffer, queue, sequencer)
split/join nodes
other nodes
Ranges and
partitioners
Tasks & Task groups
Task scheduler
Synchronization primitives
atomic operations
mutexes : classic, recursive, spin, queuing
rw_mutexes : spin, queuing
Thread Local Storage
combinable
enumerable_thread_specific
flattened2d
Concurrent containers
concurrent_hash_map
concurrent_queue
concurrent_bounded_queue
concurrent_priority_queue
concurrent_vector
concurrent_unordered_map
concurrent_unordered_set
Memory allocators
tbb_allocator, cache_aligned_allocator, scalable_allocator
Intel® TBB – Integration
#for including tbb in your project:
Android.mk
include $(CLEAR_VARS)
LOCAL_MODULE := tbb
LOCAL_SRC_FILES := $(TBB_PATH)/lib/android/libtbb.so
LOCAL_EXPORT_C_INCLUDES := $(TBB_PATH)/include
include $(PREBUILT_SHARED_LIBRARY)
#for calling tbb from your lib:
LOCAL_CPP_FEATURES := rtti exceptions
LOCAL_SHARED_LIBRARIES += tbb
LOCAL_CFLAGS += -DTBB_USE_GCC_BUILTINS -std=c++11
APP_STL := gnustl_shared
System.loadLibrary("gnustl_shared");
System.loadLibrary("tbb");
System.loadLibrary("YourLib");
Application.mk
Java
Intel® TBB - Download
GPLv2 with runtime exception available from
threadingbuildingblocks.org/download :
The commercial version with support is here:
software.intel.com/en-us/intel-tbb
Beacon Mountain Preview v0.5
Downloader and Installer for a common set of Android* tools
from Intel and 3rd parties :
Intel Tools
Third-Party Tools
Intel® Hardware Accelerated Execution
Manager
Intel® Graphics Performance Analyzers System
Analyzer
Intel® Integrated Performance Primitives
Preview
Intel® Threading Building Blocks
Intel® Software Manager
Google Android SDK (ADT Bundle)
Android NDK
Eclipse Integrated Development
Environment
Android Design
Cygwin* (for Windows operating systems)
Free download at
http://intel.com/software/beaconmountain
Software and Services Group
Intel® C++ Compiler for Android*
• Based on Intel® C/C++ Compiler XE 13.0
for Linux*
• Integrates into the Android* NDK as
additional toolchain which can be used
from the command-line
• Supports Intel® Atom™ processor
optimization
• Free for now
Available on http://software.intel.com/c-compiler-android