ACAS001. Opportunities for Universities: Application Development for Intel Architecture Based Smartphone Platforms

Transcription

1 Opportunities for Universities: Application Development for Intel Architecture Based Smartphone Platforms Nick Bao, Sr. Software, Mobile & Communications Group, Intel ACAS001

2 Agenda Platform Architecture Overview Software Enhancements in Android * for Intel Smartphones Intel Software Development Tools for Android Joint Innovation Projects with Shanghai Jiao Tong University Joint Innovation Projects with Tsinghua University The PDF for this Session presentation is available from our Technical Session Catalog at the end of the day at: intel.com/go/idfsessionsbj URL is on top of Session Agenda Pages in Pocket Guide 2

3 3 Platform Architecture Overview

4 Intel Atom Processor Z2460 System-on-Chip (SoC) Package Size Package-on-Package (PoP) 12 x 12 mm PoP FCMB4 32nm Non PoP SoC < 0.8 mm PoP z height < 1.4mm OEM/ODM can solder up to 2 GB of LPDDR2 memory on top of SOC Memory Peak Bandwidth 800MT/s Dual 32 bit channels Supports 1 or 2 ranks per channel Memory Size and Density Supports total memory size of 128MB, 256MB, 512MB and 1GB per channel Supports 1Gb, 2Gb and 4Gb chip densities Other Features Aggressive power management to reduce power consumption Proactive page closing policies to close unused pages Supports different physical mappings of bank addresses to optimize for performance 4

5 Intel Smartphone Platform, Intel Atom Processor Z2460 with SoC Block Diagram LPDDR2 emultimedia Card Security Engine IO Power Low Power Audio Rails I2S ULPI Power Delivery IC: VRs Audio CODEC USB2 OTG SD/MMC Primary Camera: 8MP, 15fps, 1080p MIPI-CSI I O Storage 2D/3D Graphics CPU w/512kb L2$ Video Enc/Dec (1080p30) IO MIPI-HSI UART SPI Intel XMM 6260 HSPA+ Modem TI Wi-Fi* & Bluetooth Technology CSR GPS Secondary Camera: 1.3MP, 1080p MIPI-CSI Image Signal Processor Display Controller (3 pipes) HDMI 1.3a HDMI Display IO MIPI-DSI Internal Display 5 Intel Atom processor Z2460 SoC with Hi-K 32nm Process Technology)

6 Performance Leadership CPU AND PROCESS HARDWARE ACCELERATORS OPTIMIZED PLATFORM Hi-k 32nmLP SoC Process Intel Hyper- Threading Technology Enhanced Intel SpeedStep Technology 512KB L2$/core ISA: Intel SSE2, SSE3, SSSE3 Optimized Memory Controller 2D/3D Graphics with DVFS High Performance ISP with 240MPPS OTF Low Power Audio DSP 1080p30 Video Encode and Decode Security Engine Optimized platform power management Footprint and costoptimized PMIC Wireless Connectivity Integrated Multi-options for memory, audio codec Rich suite of I/Os for OEM customization 6 Intel Streaming SIMD Extensions (Intel SSE)

7 Smartphone Platform Integration Applications SW Middleware Operating System s, Firmware HW Crypto Storage Audio CPU Intel Form Factor Reference Design Board Design Graphics Video Display Memory System-on-Chip (SoC) Integration Integration across the hardware and software stack 7

8 Technology Evolution Process: Industry-leading multi-oxide process optimized for performance and power CPU: Higher frequencies, multicores, energy optimized Memory: Next Generation technologies UFS, LPDDR3, Fast WideIO Multimedia: High-performance multicore graphics and ISP, multi-stream multi-codec programmable video encode/decode, high-performance ultra-low power audio experience Display: High-resolution interface options Security: Advanced DRM schemes, malware and IDS 8

9 9 Software Enhancements in Android * for Intel Smartphones

10 Apps Optimizing Android * for Intel Atom Processor Based Devices Applications Home Contacts Phone Browser Most Android* applications just run on Intel Atom processor based platforms User Experience Middleware GPU & Activity Video support for canvas operations Package Surface OpenGL * ES SGL Telephony Libraries Media Framework FreeType SSL Application Framework Windows * Resource SQLite WebKit libc Content Providers Optimized web technologies such as HTML 5, WebKit and javascript * Location View System Core Libraries Notification Android * Runtime Dalvik Virtual Machine Operating System Display Keypad Camera WiFi Linux * Kernel Flash Memory Audio s Binder (IPC) Power Management 10 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.

11 Optimizing Android * for Intel Atom Processor Based Devices Apps Applications Home Contacts Phone Browser User Experience Package Activity Telephony Application Framework Windows * Resource Content Providers Location View System Notification Libraries Android * Runtime Middleware Surface OpenGL * ES SGL Media Framework FreeType SSL SQLite WebKit libc Core Libraries Dalvik Virtual Machine Operating System Display Keypad Camera WiFi Linux * Kernel Flash Memory Audio s Binder (IPC) Power Management 11

12 Optimizing Android * for Intel Atom Processor Based Devices Apps User Experience SKIA and OpenGL optimizations Middleware Operating System Applications Home Contacts Phone Browser Package Surface OpenGL * ES SGL Display Keypad Extensive middleware development in imaging, media Application and Framework DRM deliver Windows * Content Providers compelling media experiences Activity Telephony Libraries Media Framework FreeType SSL Camera WiFi Resource SQLite WebKit libc Linux * Kernel Enhanced Debugging and logging Flash Memory Audio s Location Memory Optimizations, AVI, DivX *, and ASF container types, WMV /VC-1 decoder. Live Streaming optimizations, HDMI and WiDi Extended Video Modes, Video Playback DRM View System Core Libraries Notification Android * Runtime Dalvik Virtual Machine Binder (IPC) Intel architecture assembly optimizations Power Management App Compatibility Enhancements Apply extensive experience optimizing Java * to the Dalvik * VM 12

13 Optimizing Android * for Intel Atom Processor Based Devices Apps Applications Home Contacts Phone Browser User Experience Package Activity Telephony Application Framework Windows * Resource Content Providers Location View System Notification Middleware Surface OpenGL * ES Shared Memory SGL Architecture Libraries Media Framework FreeType SSL SQLite WebKit Low Power Audio Offload libc Android * Runtime Core Libraries Dalvik Virtual Machine s validated & optimized for power & memory footprint Operating System Display Keypad Camera WiFi Linux * Kernel Flash Memory Audio s Binder (IPC) Power Management 13

14 Browser Experience SKIA rendering 22.8 FPS GL accelerated rendering 60 FPS Fishtank * HTML5 workload developed by Microsoft * We have customized for internal demonstration Removed randomness Fish position, direction, size Added ability to customize parameters via URL Specify Canvas size vs. full screen Number of fish to draw How long to run We tell Fishtank how many frames to draw The FPS score it reports is the average during the test Routinely develop and integrate optimizations from V8 and Webkit into Android * Platform 14

15 Camera Burst Capture User select burst size up to 10 pictures Burst capture speed: 10 pictures in under a second Full resolution images: 8MP Shoot & select PERFECT IMAGE 15 Note: Pictures captured in burst mode with a Lava * Xolo * X900 Smartphone using the Intel Atom Processor Z

16 16 Intel Software Development Tools for Android *

17 Intel VTune Amplifier Performance Profiler Hardware Collection low overhead Event-based sampling for tuning platform performance Uses Intel Atom microarchitecture events (i.e., cache misses, floating point assists) Performance collector collects CPU and performance management unit counters GUI-based evaluation results - quickly identify cause of performance issues - CPU timeline provides workload context - Powerful filtering Remove the guesswork with fast, accurate performance profiles Compare results quickly, sort by difference - Compare 2 optimizations, what improved - Compare 2 systems what didn t speed up as much 17

18 Intel VTune Amplifier Power Analysis Analyzes behaviors that may cause unnecessary platformwide power consumption Detailed processor WakeUps Analysis Types Sleep State Analysis (C-state, S- State, D-State) Frequency Analysis (P-State) Android * Wakelocks GUI-based results - quickly identify cause of power issues Frequency and sleep state transition timeline CPU timeline provides workload context Powerful filtering 18

19 Intel Graphics Performance Analyzers System Analyzer Real-time system-level performance analysis with CPU and GPU metrics Detailed Analysis for OpenGL-ES * applications OpenGL-ES experiments help narrow down problems 19

20 Intel Hardware Accelerated Execution (Intel HAXM) Accelerates Android * emulation by 5-10x by natively executing x86 CPU commands Leverages Intel Virtualization Technology Available on most Intel Architecture based PCs since 2005 Support for Mac * & Windows * KVM for Linux * Applicable for both Dalvik * and NDK apps Must compile NDK apps for x86 Only works with x86 System Image Available as an Extra in the Android SDK directory OpenGL ES * 2.0 Support 20

21 21 Joint Innovation Projects with Shanghai Jiao Tong University

22 Low Power Speech Engine Development Environment Audio Classifier Surrounding audio detector: speech, crowd, music, mechanical, motion noise, etc. Device personalization based on user s ambient environment Keyword Detection, Speaker Verification Speaker and text dependent, language independent; need one-time enrollment Wake up the phone on your voice My voice is my password, a new way to authenticate Trigger to start natural speech interaction Always listening and continuously tracking capabilities are required without noticeable impact on standby power 22

23 Software Architecture Scene Adaptive Phone Setting User Authentication Voice Based Multi-User App Wake on Voice HMM Audio Classifier Training GMM Speaker Verification HMM Recognition GMM DTW Keyword Detector Model Database Preemphasis De-noise Front End Feature Extraction Spectrogram MFCC Context Trigger Voice Activity Detection Windowing LPE Modular design and Software re-use reduces code size and MIPS consumption in the offload engine 23

24 Environment Audio Classifier Input: PCM 16bits, Mono, 16kHz Feature: Mel-Frequency Cepstral Coefficient (MFCC) Classifier Algorithm: Gaussian Mixture Model Offline Model Training Speech (female/male) Music Crowd Motion Sound Mechanical Sound Quiet Entire Algorithm Offload to LPE PCM Host IA Pre- Processing, Energy Detection etc. Context AWARE Middleware Stack & Apps Audio Classifier Trigger MFCC Android Audio HAL GMM Classifier Speech Music Crowd... Aggregator LPE.mix model 24

25 Key Word Detection PCM VAD Noise reduction Preprocessing Front End Feature Extraction Core Recognition Keyword Base Score Input: PCM 16bits, Mono, 16kHz Feature: Mel-Frequency Cepstral Coefficient (MFCC) Matching Algorithm: Dynamic Time Wrapping (DTW), Template Based Additional Modules PCM Signal Pre-Processing Frame Admission for Keyword Enrollment 25

26 Environment Audio Classifier Performance 100% Environment Audio Classifier 90% 80% 70% 60% Avg. Accuracy = 92% 50% 40% 30% 20% 10% 0% Music Crowd Speech motion Mechanical 26

27 Key Word Detection Performance 12.00% Equal Error Rate: (Smaller is Better) 10.00% 8.00% 6.00% 4.00% 2.00% 0.00% 27

28 Curriculum and Student Projects With Shanghai Jiao Tong University Intel Atom processor Z2460 based Mobility system: Application Analysis & Design Hardware and software architecture Application development Tools 28

29 Some Experiments 1. VoiceOut Speak out what you have typed in 2. Show some information about the battery 3. Show current gravity information 4. Turn on/off the camera flash or vibrator 29

30 Some Experiments 5. Camera demo Camera preview here. Move your finger on the preview to make some interesting effects on the picture (not done). Show the first touch position and touch numbers for further usage Press the save button to save the preview picture into SD card 30

31 Application Development in Progress Color ring resistance recognition by taking a picture Virtual fitting Imaging processing-based face recognition Location based services 31

32 32 Joint Innovation Projects with Tsinghua University

33 Development Process Milestone 1: Android * APK Development Flow Development environments Design documents Milestone 2: Study of OpenCV * for Android Development documents Tutorial in the development group of Tsinghua University Some applications with OpenCV@C/C++ 33

34 34 Project 1: Campus Navigation System Based on Smartphone & Computer Vision

35 Key Technology Mobile phone interactive control Recognition and location based on image matching Virtual reality High-performance software development on smartphone 35

36 Project 2: Navigator for the Blind Based on Smartphone & Brain-Computer Interface Brain Signal Amp Pattern Recognition User EEG Mobile Brain- Computer Bluetooth Technology Earphone Computer Vision Face Recognition 36

37 Key Technology Brain-computer interface Brain signal recognition Image recognition High-performance software development on smartphone 37

38 Summary 2nd Generation of Intel Platforms for Smartphones Full support for standard Android * Development Intel Software Developer tools Opportunities for Universities on Application development on Intel Architecture based smartphone 38

39 Next Steps Download the Android * SDK Download the SDK add-on for the Intel Emulator with Intel Hardware Accelerated Execution (Intel HAXM) acceleration Download the x86 NDK Download Intel Software Developer Tools for Android Start developing/optimizing curriculum/innovation projects today 39

40 Where to Get More Info Intel Software Network (ISN) Real developers sharing knowledge and offering help Dedicated communities and forums focused on your interests Worldwide reach News and insights on cutting edge technology Intel Android Developer Website Great content you won t find anywhere else Technical articles, tools and How-To guides Native app porting tips and case studies Info on x86 emulator and Intel Hardware Accelerated Execution Active forums and blogs written by Intel and community experts 40

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