Posts Tagged ‘gpu’

Some Projects on Nvidia Jetson TK1 Development Board: Nintendo Emulator, USB3 Webcam, and Robotics

August 4th, 2014 4 comments

Nvidia Jetson TK1 is a development board powered by the company’s Tegra K1 quado core Cortex A15 processor, and especially a Kepler GPU that allows for OpenGL 4.4. It has shipped to developers around April/May, and some of them have showcased their projects, or tested some hardware.

Dolphin Emulator on Nvidia Jetson TK1

Dolphin is an emulator for Nintendo GameCube and Wii console that supports full HD (1080p) rendering, and run on Android, Linux and Mac OS,  and there’s also an Alpha version for Android. Ryan Houdek (Sonicadvance1), one of Dolphin’s developers, has leveraged Kepler’s OpenGL support via Nvidia’s GPU drivers, to port the emulator to the platform running on Ubuntu, but it should work as well on Tegra K1 hardware running Android such as XiaoMi MiiPad tablet.  You can watch Mario Kart: Double Dash demo running at full speed on the Nvidia board below. According to the developer, such framerate would be not achievable on Qualcomm 800 because “Adreno Graphics Drivers are grossly inefficient compared to the TK1″.

The latest version of Dolphin for Android (Beta) dates December 7, 2013, so I’d assume the optimizations shown above are not available right now. You can find more demos on Ryan Houdek’s YouTube Channel.

USB3.0 Webcam @ 1080p30

Another developer, Korneliusz Jarzębski, has tested e-con Systems USB3 See3CAM_80 HD camera connected to the board’s USB 3.0 port, and using the camera’s “See3CAM” application. I understand that all that needed to be done was to enable hidraw for USB devices in the Linux kernel, and it just worked out of the box. The application can perform real-time video processing, applying videos filters (invert, particles, etc..), as well as changing image characteristics such as brightness, contrast and so on.

You can find a little more on his blog (Polish).

“Super-Computer-On-Legs” Robot

The last demo I’ll show today is a robot powered by Jetson TK1 board that can walk to the nearest person it can see. The robot detects person via a camera and GPU accelerated face detection (about 5 times faster than CPU-only face detection). Beside better performance, the robot is pretty power-efficient as it only draws about 7 watts, and last about 45 minutes powered by a small LiPo battery. The robot was showcased at the Robotics Science and Systems Conference last month, and while attendees were impressed by the performance and power consumption, they still noticed the board was a bit too big for most robots, especially quad copters. But the platform clearly has potential, and Shervin Emami, the person behind the project who happens to work for… Nvidia, mentioned work is being done on smaller Tegra K1 computer on modules that be installed in a custom motherboard of a robot without unnecessary ports.

If you are interested in seeing more projects running on Jetson TK1 development board, you can consider following “Embedded Tegra & Jetson TK1 Blog” on Google+.

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ARM TechCon 2014 Schedule – 64-Bit, IoT, Optimization & Debugging, Security and More

July 23rd, 2014 No comments

ARM Technology Conference (TechCon) 2014 will take place on October 1 – 3, 2014, in Santa Clara, and as every year, there will be a conference with various sessions for suitable engineers and managers, as well as an exposition where companies showcase their latest ARM based products and solutions. The detailed schedule for the conference has just been made available. Last year,  there were 90 sessions organized into 15 tracks, but this year, despite received 300 applications,  the organizers decided to scale it down a bit, and there will be 75 session in the following 11 tracks:ARM_TechCon_2014

  • Chip Implementation
  • Debugging
  • Graphics
  • Heterogeneous Compute
  • New Frontiers
  • Power Efficiency
  • Safety and Security
  • Software Development and Optimization
  • Software Optimization for Infrastructure and Cloud
  • System Design
  • Verification

There are also some paid workshops that take all day with topics such as “Android (NDK) and ARM overview”, “ARM and the Internet of Things”, or “ARM Accredited Engineer Programs”.

As usual, I’ve gone through the schedule builder, and come up with some interesting sessions with my virtual schedule during the 3-day event:

Wednesday – 1st of October

In this session, Dr. Saied Tehrani will discuss how Spansion’s approach to utilize the ARM Cortex-R line of processors to deliver energy efficient solutions for the automotive MCU market has led the company to become a vital part of the movement toward connectivity in cars. Beginning with an overview of the auto industry’s innovation and growth in connected car features, he will explain how these systems require high performance processing to give drivers the fluid experience they expect. Highlights in security and reliability with ARM Cortex-R, including Spansion’s Traveo Family of MCU’s will also be presented.

HEVC and VP9 are the latest video compression standards that significantly improves compression ratio compared to its widely used predecessors H.264 and VP8 standard. In this session the following will be discussed:

  • The market need for GPU accelerated HEVC and VP9 decoders
  • Challenges involved in offloading video decoding algorithms to a GPU, and how Mali GPU is well suited to tackle them
  • Improvement in power consumption and performance of Mali GPU accelerated decoder
  • big.LITTLE architecture and CCI/CCN’s complementing roles in improving the GPU accelerated video decoder’s power consumption

ARM’s Cortex-M family of embedded processors are delivering energy-efficient, highly responsive solutions in a wide variety of application areas right from the lowest-power, general-purpose microcontrollers to specialised devices in advanced SoC designs. This talk will examine how ARM plans to grow the ARM Cortex-M processor family to provide high performance together with flexible memory systems, whilst still maintaining the low-power, low-latency characteristics of ARM’s architecture v7M.

IoT devices as embedded systems cover a large range of devices from low-power, low-performance sensors to high-end gateways. This presentation will highlight the elements an embedded engineer needs to analyse before selecting the MCU for his design. Software is fundamental in IoT: from networking to power management, from vertical market protocols to IoT Cloud protocols and services, from programming languages to remote firmware update, these are all design criteria influencing an IoT device design. Several challenges specific to IoT design will be addressed:

  • Code size and RAM requirements for the major networking stacks
  • Optimizing TCP/IP resources versus performance
  • Using Java from Oracle or from other vendors versus C
  • WiFi (radio only or integrated module)
  • Bluetooth (Classis versus LE) IoT protocols

Thursday – 2nd of October

Amongst ARM’s IP portfolio we have CPUs, GPUs, video engines and display processors, together with fabric interconnect and POP IP, all co-designed, co-verified and co-optimized to produce energy-efficient implementations. In this talk, we will present some of the innovations ARM has introduced to reduce memory bandwidth and system power, both in the IP blocks themselves and the interactions between them, and how this strategy now extends to the new ARM Mali display processors.

Designing a system that has to run on coin cells? There’s little accurate information available about how these batteries behave in systems that spend most of their time sleeping. This class will give design guidance on the batteries, plus examine the many other places power leakages occur, and offer some mitigation strategies.

64-bit is the “new black” across the electronics industry, from server to mobile devices. So if you are building or considering building an ARMv8-A SoC, you shall attend this talk to either check that you know everything or find out what you shall know! Using the ARMv8 Juno ARM Development Platform (ADP) as reference, this session will cover:

  • The ARMv8-A hardware compute subsystem architecture for Cortex-A57, Cortex-A53 & Mali based SoC
  • The associated ARMv8-A software stack
  • The resources available to 64-bit software developers
  • Demonstration of the Android Open Source Project for ARMv8 running on Juno.

Rapid prototyping platforms have become a standard path to develop initial design concepts. They provide an easy-to-use interface with a minimal learning curve and allow ideas to flourish and quickly become reality. Transitioning from a simple, easy-to-use rapid prototyping system can be daunting, but shouldn’t be. This session presents options for starting with mbed as a prototyping environment and moving to full production with the use of development hardware, the open-source mbed SDK and HDK, and the rich ARM ecosystem of hardware and software tools.Attendees will learn how to move from the mbed online prototyping environment to full production software, including:

  • Exporting from mbed to a professional IDE
  • Full run-time control with debugging capabilities
  • Leveraging an expanded SDK with a wider range of integration points
  • Portability of applications from an mbed-enabled HDK to your custom hardware

Statistics is often perceived as scary and dull… but not when you apply it to optimizing your code! You can learn so much about your system and your application by using relatively simple techniques that there’s no excuse not to know them.This presentation will use no slides but will step through a fun and engaging demo of progressively optimizing OpenCL applications on a ARM-powered Chromebook using IPython. Highlights will include analyzing performance counters using radar diagrams, reducing performance variability by optimizing for caches and predicting which program transformations will make a real difference before actually implementing them.

Friday – 3rd of October

The proliferation of mobile devices has led to the need of squeezing every last micro-amp-hour out of batteries. Minimizing the energy profile of a micro-controller is not always straight forward. A combination of sleep modes, peripheral control and other techniques can be used to maximize battery life. In this session, strategies for optimizing micro-controller energy profiles will be examined which will extend battery life while maintaining the integrity of the system. The techniques will be demonstrated on an ARM Cortex-M processor, and include a combination of power modes, software architecture design techniques and various tips and tricks that reduce the energy profile.

One of the obstacles to IoT market growth is guaranteeing interoperability between devices and services . Today, most solutions address applications requirements for specific verticals in isolation from others. Overcoming this shortcoming requires adoption of open standards for data communication, security and device management. Economics, scalability and usability demand a platform that can be used across multiple applications and verticals. This talk covers some of the key standards like constrained application protocol (CoAP), OMA Lightweight M2M and 6LoWPAN. The key features of these standards like Caching Proxy, Eventing, Grouping, Security and Web Resource Model for creating efficient, secure, and open standards based IoT systems will also be discussed.

Virtual Prototypes are gaining widespread acceptance as a strategy for developing and debugging software removing the dependence on the availability of hardware. In this session we will explore how a virtual prototype can be used productively for software debug. We will explain the interfaces that exist for debugging and tracing activity in the virtual prototype, how these are used to attach debug and analysis tools and how these differ from (and improve upon) equivalent hardware capabilities. We will look in depth at strategies for debug and trace and how to leverage the advantages that the virtual environment offers. The presentation will further explore how the virtual prototype connects to hardware simulators to provide cross-domain (hardware and software) debug. The techniques will be illustrated through case studies garnered from experiences working with partners on projects over the last few years.

Attendees will learn:

  • How to set up a Virtual Prototype for debug and trace
  • Connecting debuggers and other analysis tools.
  • Strategies for productive debug of software in a virtual prototype.
  • How to setup trace on a virtual platform, and analysing the results.
  • Hardware in the loop: cross domain debug.
  • Use of Python to control the simulation and trace interfaces for a virtual platform.
  • 14:30 – 15:20 – GPGPU on ARM Systems by Michael Anderson, Chief Scientist, The PTR Group, Inc.

ARM platforms are increasingly coupled with high-performance Graphics Processor Units (GPUs). However the GPU can do more than just render graphics, Today’s GPUs are highly-integrated multi-core processors in their own right and are capable of much more than updating the display. In this session, we will discuss the rationale for harnessing GPUs as compute engines and their implementations. We’ll examine Nvidia’s CUDA, OpenCL and RenderScript as a means to incorporate high-performance computing into low power draw platforms. This session will include some demonstrations of various applications that can leverage the general-purpose GPU compute approach.

Abstract currently not available.

That’s 14 sessions out of the 75 available, and you can make your own schedule depending on your interests with the schedule builder.

In order to attend ARM TechCon 2014, you can register online, although you could always show up and pay the regular on-site, but it will cost you, or your company, extra.

Super Early Bird Rare
Ended June 27
Early Bird Rate
Ends August 8
Advanced Rate
Ends September 19
Regular Rate
VIP $999 $1,299 $1,499 $1,699
All-Access $799 $999 $1,199 $1,399
General Admission $699 $899 $1,099 $1,299
AAE Training $249 $299 $349 $399
Software Developers Workshop $99 $149 $199 $249
Expo FREE FREE $29 $59

There are more types of pass this year, but the 2-day and 1-day pass have gone out of the window. The expo pass used to be free at any time, but this year, you need to register before August 8. VIP and All-access provides access to all events, General Admission excludes AAE workshops and software developer workshops, AAE Training and Software Developers Workshop passes give access to the expo plus specific workshops. Further discounts are available for groups, up to 30% discount.

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Imagination Technologies Unveils Low Power Low Footprint PowerVR GX5300 GPU for Wearables

July 22nd, 2014 No comments

Up to now most wearables are based on MCU solutions or derived from mobile platforms, which may either not provide the advanced features required by users, or consume too much power and take more space than needed. With Ineda Dhanush and Mediatek Aster, we’ve already seen silicon vendors design wearables SoCs, and now Imagination Technologies has just announced PowerVR GX5300 GPU targeting wearables with support for OpenGL ES 2.0, 480p to 720p resolution, and using 0.55mm2 silicon area based on 28nm process.

PowerVR GX5300 Block Diagram

PowerVR GX5300 Block Diagram

PowerVR GX5300 GPU will be support Android, Android Wear, and Linux based operation systems, and according to the company has the following key features:

  • Unified shaders – The TBDR graphics architecture offers unified shaders where vertex, pixel and GPU compute resources are scaled simultaneously.
  • Low power and high precision graphics – All PowerVR GPUs offer a mix of low (FP16) and high precision (FP32) rendering and implement the full OpenGL ES 2.0 specification.
  • Reduced memory footprint - PowerVR GX5300 supports PVRTC, a texture compression format which reduces memory bandwidth and decreases power consumption. It can help silicon vendors reduce memory costs.

Typical applications will be embedded Linux or Android-based connected home systems that require graphics rendering such as smart washing machines, and wearables running Android Wear such as smartwatches.

PowerVR GX5300 is available for licensing now, but it has not been announced in any wearable SoCs just yet, so it’s probably something we’ll see in products in 2015.

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Hardkernel Unveils $179 ODROID-XU3 Development Board Powered by Samsung Exynos 5422 SoC

July 8th, 2014 9 comments

Remember ODROID-XU2 development board based on Exynos 5420? The bad news is that it apparently got scrapped, but the good news is that it gave birth to ODROID-XU3 development board powered by the latest Samsung Exynos 5422 octa core big.LITTLE SoC with support for Ubuntu 14.04 and Android 4.4, including GPU 3D acceleration with the company promising a full desktop experience in Ubuntu.

ODROID-XU3ODROID-XU3 specifications:

  • SoC – Samsung Exynos 5422 quad core ARM Cortex-A15 @ 2.0GHz+ quad core ARM Cortex-A7 @ 1.4GHz with Mali-T628 MP6 GPU supporting OpenGL ES 3.0 / 2.0 / 1.1 and OpenCL 1.1 Full profile
  • System Memory – 2GB LPDDR3 RAM PoP (933Mhz, 14.9GB/s memory bandwidth, 2x32bit bus)
  • Storage – Micro SD slot (up to 64GB) + eMMC 5.0 module socket (16, 32, or 64GB module available)
  • Video Output – micro HDMI (Up to 1080p) and DisplayPort (up to 2160p)
  • Audio Output – micro HDMI and 3.5mm headphone jack
  • Network Connectivity – 10/100Mbps Ethernet (Via LAN95144 USB + Ethernet controller)
  • USB – 1x USB 3.0 host port, 1x USB 3.0 micro USB OTG port, 4x USB 2.0 ports
  • Expansion – 30-pin header for access to GPIO, IRQ, SPI and ADC signals
  • Debugging – Serial console header
  • Misc – Accurate current sensors and voltage sensors for energy measurement, Power and RGB LEDs, cooling fan header
  • Power Supply – 5V/4A power adapter using 5.5/2.1mm barrel.
  • Dimensions – PCBA: 94x70x18mm; Enclosure: 98x74x29mm
ODROID-XU3 Block Diagram (Click to Enlarge)

ODROID-XU3 Block Diagram (Click to Enlarge)

The company can also provide USB modules / dongles for optical S/PDIF output, Gigabit Ethernet (USB 3.0 to Ethernet adapter), Wi-Fi 802.11n/g/n 1T1R with antenna, and 2.5″/3.5″ SATA drives (USB 3.0 to SATA III adapter).  Hardkernel will provide Ubuntu 14.04 support with OpenGL ES + OpenCL support, and Android 4.4.2 both based on Linux kernel 3.10 LTS, and the source code will soon be available on their github account. This is also the first ODROID board that supports Heterogeneous Multi-Processing / Global Task Scheduling implementation of big.LITTLE processing. You can get an overview of the board and see Ubuntu 14.04 running OpenGL ES 3.0 demo, and playing a windowed YouTube video – which makes me think hardware video decoding may not be implemented yet – in the video below.

ODROID-XU3 comes with a plastic case, an active cooler and a 5V/4A power adapter, and you get pre-order it for $179 + shipping on Hardkernel website with delivery schedule for the 18th of August 2014. There’s no internal storage with the board so you’ll need a micro SD card (Class 10 strongly recommended), or even better purchased one of the eMMC module with the board. The 16GB eMMC sells for $39 and includes an adapter to connect it to your PC. You can get more information, and/or purchase the board and a few of its 23 accessories on Hardkernel’s ODROID-XU3 product page.

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Google Releases Android L (Lollipop?) Developer Preview

June 26th, 2014 2 comments

Google I/O is taking place right now in San Francisco, and the company made several announcements. Although they have not announced the full codename of Android 5.0, referring to the next version as “Android L” (Lollipop would be nice though), but they’ve already documented the key changes made to Android L, and a developer preview will be released later today (26 June), together with binary images for Google Nexus 5 and Nexus 7.


Beside the smartphone and tablet developer preview, there will be 3 other SDKs for Android L:

  • Android Wear SDK – Android for wearables with sync notifications, wearable apps, data transfer APIs, and voice actions, e.g. “Ok Google, call mum”.
  • Android TV Preview SDK – Android for TVs with pre-built fragments for browsing and interacting with media catalogs, in-app search, and recommendations.
  • Android Auto SDK – Android for the car with apps featuring consistent user experience between vehicles, and minimizing distractions.

I’ll go through various software and hardware announcements for Android Wear and TV in separate blog posts, and probably skip Android Auto for now.

So what’s new in Android L Developer Preview?

Material Design

Material Design is is a new design language that will let developer create app which look similar to Google Now. Google chose the name “Material” as it is apparently inspired from real materials such as paper and ink. Android L user interface will be entirely designed with Material Design. The best is to look at an example.

Gmail Now vs Gmail "L"

Gmail Now vs Gmail “L”

On the left, we’ve got the current Gmail app, and on the right the newly designed app for Android L. Lots of it looks like cosmetic changes, but you’ll have noticed the three dot and new mail icons are gone, and all menu will be accessible via the top left icon. There are also some light and shadow effects that will make users feel like they’re touching real elements.

More details can be found in this Material Design presentation (PDF).

Improved Notifications

Notifications have also changed with a new design based on Material, and the ability to display notifications on the lock screen.


I understand lockscreen notifications are optional, and if you don’t like to show them in the lock screen using visibility controls. As you can see from the screenshot above it works very similar to Google Now which cards that you can discard once you’re done. Notifications will also be able to pop-up in games or other full screen apps, and you’ll be able o take action within the notification, for example by declining or accepting a video call request.


The list of recent apps will become the list of recent everything, simply called “Recents”, as it will include both apps, web pages, and documents.

Better Tools for Improving Battery Life

As devices become more powerful, they also become more power hungry despite efforts by SoC designers to reduce energy usage. Badly programmed apps are however the main culprit of short battery life, so Google has introduced Project Volta to help user and developers optimize power consumption. Developers can use “Battery Historian” tool to monitor power consumption of different processes, and which hardware block (e.g. Cellular radio) is currently being used.

Battery_HistorianUsers will also have their own app / feature dubbed “Battery Saver” to improve battery life, and Google claims their Nexus 5 should be able to last an extra 90 minutes on a charge with Battery Saver enabled. This is achieved by reducing the performance of the device once the battery has dropped below 20% charge. At that time, a notification would pop-up to let the user select he wants to enable Battery Saver mode.

Under the hood improvements

As as been widely reported, Google recently killed Dalvik in a recent commit in AOSP, and ART will become the default JAVA runtime using ahead-of-time compilation for speedier application loading time, and memory usage improvements. Google also claims it provides true cross platform support for ARM, MIPS and x86.

Android L will support 64-bit instructions including ARMv8, x86-64 and MIPS64. This will provide a larger number of registers, and increased addressable memory space. Java developers won’t needto change their apps for 64-bit support. One the first Android64 devices is likely to be the Nexus 9 tablet powered by Nvidia Tegra K1 Denver as previously reported.

On the graphics side, Android L adds support for OpenGL ES 3.1, and includes Android Extension Pack for developers with tesselation and geometry shaders and other features that should bring PC and console class graphics to Android games according to Google.

Via Anandtech and Liliputing

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ARM Cortex A15/A17 SoCs Comparison – Nvidia Tegra K1 vs Samsung Exynos 5422 vs Rockchip RK3288 vs AllWinner A80

May 21st, 2014 10 comments

We’re now starting to get quite a few players with ARM Cortex A15 cores on the market, as well as some with ARM Cortex A17. So a comparison table of different quad and octa SoCs might be a useful thing to do. I’ve put aside SoCs such as HiSilicon K3V3, and OMAP5, and focused on the four latest processors: Nvidia Tegra K1 (32-bit), Samsung Exynos 5422, Rockchip RK3288 and AllWinner A80. I haven’t included Mediatek MT6595 and Qualcomm SnapDragon 805, because the two companies mainly focus on smartphones and tablets (although it appears to be slowly changing for Qualcomm), documentation is usually difficult or impossible to find, and in the case of Qualcomm they use their own ARMv7 Krait cores.

rk3288_a80_tegra_k1_exynos_5_octaI’ve highlighted some features in green, in case a particular SoC appears to have an edge.

Rockchip RK3288 AllWinner A80 Nvidia Tegra K1 Samsung Exynos 5422
CPU 4x ARM Cortex-A17 @ 1.8 GHZ 4x ARM Cortex-A15 r4 @ 2.0?? GHz +
4x ARM Cortex-A7 @ ?? GHz
big.LITTLE Processing
Quad Core ARM Cortex-A15 r3 @ 2.3GHz + Cortex A15 r3 companion core 4x ARM Cortex-A15 @ 2.1 GHz +
4x ARM Cortex-A7 @ 1.5 GHz
big.LITTLE Processing
L1 Icache/Dcache 32KB/32KB 32KB/32KB 32KB/32KB 32KB/32KB
L2 Cache 1MB 2MB + 512KB 2MB + 512 KB 2MB + 512 KB
GPU ARM Mali-T764 PowerVR G6230 (64-cores) Kepler GK20a (192-cores) ARM Mali-T628 MP6
GPU API OpenGL ES 1.1/2.0/3.0, OpenVG 1.1, OpenCL 1.1 and Renderscript, Directx11 OpenGL ES 2.0/3.0, OpenCL 1.x, Directx 9.3 OpenGL ES 2.0/3.0/3.1, OpenGL 4.4, OpenCL 1.2, CUDA 6.0, Directx 12 OpenGL ES 1.1/2.0/3.0, OpenCL 1.1,OpenVG 1.0.1, DirectX 11, and Google Renderscript
Video Decoder 4K2K@60fps: HEVC
4K2K@24fps: H.264, MPEG-2, VP6/VP8, MVC
1080p: MPEG-4, Sorenson Spark, VC-1, RV8/RV9/RV10, and AVS
4K2K@30fps: H.264 and VP8
1080p60: MPEG 1/2/4. H.263, H.264, WMV9/VC1, etc…
1080p30: H.265/VP9
3D decoding @ 3840×1080@30fps
1440p – H.264 BP/MP/HP/MVC, VC-1, VP8, MPEG-2 and MPEG-4 1920×1080@120fps – MPEG-4/MPEG-2/H.263/H.264/VP8//VC1
8192×8192 – H.264 and VP8
Video Encoder 1080p30: H.264, MVC, and VP8 4K2K@30fps: H.264 and VP8 H.264
1920×1080@120fps – MPEG-4//H.263/H.264/VP8
8192×8192 – H.264 and VP8
Memory (On-chip) 20KB BootRom, 100KB internal SRAM No data 64KB Boot ROM (IROM) No data
Memory Interfaces DDR3-1333/DDR3L-1333, LPDDR2-1066, LPDDR3-1066, up to 4GB
Dual channel async NAND flash, 8-bit, 60-bit ECC
Single channel async NAND flash, 16-bit, 60-bit ECC
eMMC v4.5
SD/MMC Interface (SD 3.0, MMC ver 4.5)
Raw NAND with 72-bit ECC
eMMC v4.5
DDR3L, and LPDDR3, up to 8GB
LPDDR2 might work but not tested by Nvidia
eMMC version 4.5
LPDDR3/DDR3 – 2-ports 32-bit up to 933 MHz
LPDDR2 – 2-ports 32-bit up to 533 MHz
2x eMMC 5.0, 1x eMMC 4.5
8-bit SDIO 3.0,
4-bit SD 3.0
Display Interfaces Dual channel LVDS
2x Parallel and serial RGB interfaces: Up to 3840×2160 or 2560×1600
MCU LCD interface (optional)
4-lane MIPI up to 1080p60
4-lane eDP up to 4K2K@30fps
HDMI 1.4 and 2.0
Dual channel LVDS up to 1920×1080@60fps
RGB LCD up to 2048×1536@60fps
4-lane MIPI DSI up to 1920×1200@60fps
4-lane eDP up to 2560×1600@60fps
HDMI 1.4
LVDS up to 1920×1200@60fps
2x 4-lane MIPI DSI (Dual link: up to 3840×1920@60fps, single link: 2560×1440@60fps)
4-lane eDP up to 3840×2160@60fps
HDMI 1.4b up to 4096×2160@30fps
4-lane MIPI DSI up to WUXGA (1920×1200) @ 60 fps
1-port (4 lanes) eDisplayPort (eDP) up to WQXGA (2560×1600) @ 60 fps
HDMI 1.4a interfaces with on-chip PHY
Camera Interfaces 12-bit CCIR/Camera I/F up to 5MP
MIPI CSI2 I/F up to 14MP
8/10/12-bit raw data interface
Parallel and MIPI I/F sensor
5M/8M/12M/16M CMOS sensor
8/10/12-bit YUV/Bayer sensor
Up to 16MP @ 37 fps
2x 4x YUV / RAW / CSI
2-ports (4/4 lanes) MIPI CSI2 interfaces
Up to 16MP @ 30fps
14-bit Bayer sensor
USB 2x USB 2.0 Host
1x USB 2.0 OTG
2x USB host
1x USB3.0/2.0 host / device
2x USB 3.0
3x USB 2.0
2x USB 3.0
1x USB 2.0
Ethernet 1x GMAC (RMII/RGMII) 1x Ethernet MAC N/A N/A
TS Interface 2x IN, 1x IN No data 1x TS 1x TSI
PCIe N/A N/A 5-lane PCIe with Gen1 (2.5GT/s) and Gen 2 (5.0 GT/s) speeds N/A
Other I/Os 3x SPI, 6x I2C, 5x UART, 4x PWM, 2x DMAC, 160 GPIO 4x SPI, 7x TWI, 7x UART 3x I2C, 2x SPI, UART, Up to 64 MPIO (Multi Purpose IO) 4x I2C, 7x HS-I2C, 3x SPI, 5x UART, GPIOs, 24-channel DMA controller
Antutu 4.x 35225
Hardware: Pipo P8 (res: 2048×1536)
Hardware: AllWinner OptimusBoard?
Hardware: Tegra K1 Reference Tablet?
Hardware: Samsung Galaxy S5 (SMG900H)
Low Cost Development Board Currently not available, none officially announced. Announced: OptimusBoard, PcDuino8, Cubieboard A80. No price available. Nvidia Jetson TK1 for $192 None with Exynos 5422, but two with the similar Exynos 5420:
Arndale Octa for $179
Announced: ODROID XU-2 (Price not available)

First some general comments:

  1. As details are not always available, and I had to go through thousands of pages of documentation, it’s possible some information is incorrect or missing. So I’d be grateful if anybody points out mistakes in the table.
  2. In L2 Cache = xx MB + xx KB refers to the cache for the bit processors (A15) + the cache for the LITTLE processors (A7) or the companion core.
  3. The “Other I/Os” section is mainly for reference, as I’m sure parts are missing here.
  4. I haven’t addressed power consumption of the different SoC, since I don’t believe numbers provided by the SoC vendors are directly comparable.
  5. Antutu scores are interesting to get an idea of the performance, but we should bear in mind AllWinner A80 and Tegra K1 scores appear to have been achieved with development hardware, which may not have the same thermal constraints as the tablet and smartphone used with Rockchip RK3288 and Exynos 5422.

Based on this comparison table, Nvidia Tegra K1 really seems to have the best package in terms of performance, 3D and GPGPU APIs, and peripheral interfaces such as SATA and PCIe which are missing on all other SoCs. The downsides are video encoding is only supported up to 1440p, and there’s no Ethernet MAC. That means no 4K hardware video decoding, although an article from Anandtech mentioned the company demos 4K 30 fps using the Kepler GPU. The way to add Ethernet with Tegra K1 is to use an external Ethernet Control chip and connect it to the PCI Express port, as they did for Jetson TK1 development board. It’s also likely Tegra K1 is more expensive than all other three, but it’s very versatile and could be found in various type of products: tablets, mini PCs, laptops and so on. Linux and Android are supported, and since the company seem inclined to go open source, it’s likely any Linux based OS can be supported by the platform.

Rockchip RK3288 should be one of the more cost effective platform in the table, but trade offs includes 1MB L2 cache (vs 2MB for others), an 4GB RAM limitation, the lack of USB 3.0 interfaces, and lower overall performance. However it’s the only SoC that 100% 4K ready here with HDMI 2.0, HEVC decode at up to 4K @ 60fps, as well as Gigabit Ethernet. ARM Cortex A17 should also have lower consumption compared to ARM Cortex A15, but it’s unclear how it will compare against big.LITTLE solution. This will probably remain a gray area because power efficiency will highly depend on the payload. RK3288 has already been demoed on hardware running Android and Chromium OS.

AllWinner A80 has performance very close to Tegra K1, apparently supports VP9 (N.B: However, I had been asked to remove VP9 from an AllWinner A80 graphics once), supports 4K30 video decoding, USB 3.0. Apart from the lack of SATA and PCIe interfaces, and OpenGL 4.4 support, AllWinner SoC appears to have few drawbacks compared to Tegra K1, so we’ll have to see how it compares in terms of price versus Rockchip RK3288. The company has also announced support for 5 operating systems for A80: Android, Chrome OS, Ubuntu, Windows 8, and Firefox OS. So they must have worked with Imagination Technology to support the PowerVR GPU on these OS.

Samsung Exynos 5422 appears to be just short of AllWinner A80 and Tegra K1 performance, and the company has dropped some interfaces such as SATA, PCIe, LVDS, Ethernet MAC,  that makes it a little less versatile than other SoCs, and more targeted at tablets and smartphones. It’s the only SoC that supports both 8K encode and decode (H.264 and VP8 only), but lacks HEVC/H.265 hardware support. It’s also the only SoC to support eMMC 5.0, instead of just eMMC 4.5, which can potentially double the IO performance (400MB/s max instead of 200 MB/s).


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AMD Unveils Low Power Mobile “Mullins” APUs for Tablets and Hybrid Laptops

April 30th, 2014 1 comment

AMD has announced its 3rd-generation Mainstream and Low Power Mobile Accelerated Processing Units (APUs), codenamed codenamed “Beema” and “Mullins,” respectively, featuring four x86 Puma+ CPU, AMD Radeon graphics, and a platform security processor (PSP) with an ARM Cortex-A5 core for ARM TrustZone  security. Beema APUs have a TDP between 9W and 15W, whereas Mullins APUs all have less than 5W TDP (2.8W SDP). So I’ll only cover cover Mullins processors in this post, as they may offer an alternative to Intel Bay Trail-T processors.

AMD_Mullins_Block_DiagramThere are now 3 more APUs part of AMD’s tablets and 2-in-1 solutions: A10 Micro-6700T, A4 Micro-6400T, and E1 Micro-6200T. They are highlighted in green in  the table below, and compared to previous generations:

Model​​ Radeon Brand CPU Clock Speed (Max/Base) CPU Cores on Die TDP Total L2 Cache GPU Clock Speed (Max/Base) DDR SDRMA Max Memory Speed
​A10 Micro–​​6700T ​Radeon R6 ​2.2 GHz ​4 ​4.5W ​2MB ​500MHz ​DDR3L-1333
​A4 Micro–​6400T ​Radeon R3 ​1.6 GHz ​4 ​4.5W ​2MB ​350MHz ​DDR3L-1333
A6–1450 Radeon HD 8250 1.4GHz / 1.0GHz 4 8W 2MB 400MHz / 300MHz DDR3L-1066
A4-1350 Radeon HD 8210 1.0GHz 4 8W 2MB 300MHz DDR3L-1066
A4-1250 Radeon HD 8210 1.0GHz 2 8W 1MB 300MHz DDR3L-1333
A4-1200 Radeon HD 8180 1.0GHz 2 3.9W 1MB 225MHz DDR3L-1066
​E1 ​​Micro-6200T ​Radeon R2 ​1.4GHz ​2 ​3.95W ​1MB ​300MHz ​DDR3L-1066

Beside the new Puma+ CPU cores, and AMD R Series GPU, performance and power consumption have been achieved thanks to:

  • AMD Enduro technology for a longer battery life;
  • AMD Start Now technology for quick boot-up and resume from sleep mode
  • AMD Turbo Core technology adding turbo mode when more performance is required.

The company is apparently focusing their efforts ion Windows, and end-users would have to use BlueStacks running on top of Windows for Android support.

Anantech got hold of an 11.6″ tablet reference design (Discovery Tablet) powered by A10 Micro-6700T, and running Windows 8.1. Benchmarks showed most individual tests easily outperforming Intel Atom “Bay Trail” Z3770 quad core processor in terms of CPU performance.

CPU Benchmark

CPU Benchmark – Cinebench R11.50

Multi-threaded performance was however similar to Z3770 in Cinebench multi-threaded benchmark.  The A10 Micro-6700T powered tablet  was also clearly ahead in JavaScript/Web Browser test against platform such as Asus Transformer Book T100 (Intel Atom Z3740) and Apple iPad Air. One oddity was the lower performance of the reference tablet with PCMark7 which tests the overall system performance. Anandtech assumed the disappointing score may be due to other components of the tablet or thermal limits of the tablet.

GPU Benchmark

GPU Benchmark – Futuremark 3DMark

They could not compare GPU performance against competing platforms, but the latest AMD processor appears to have a decent GPU performance considering the 4.5W TDP Mullins processor can match, and even slightly outperform, AMD’s Kabini AMD-5000 with 15W TDP.

More benchmark results are also available via Hot hardware.

Anandtech did not have to test the power consumption of the device. But using numbers provided by AMD, Anandtech compared the idle power consumption between AMD Mulins (620 mW) and Qualcomm Snapdragon (320mW), and it’s clear although AMD has made tremendous improvement in terms of power consumption, they can’t quite match ARM, at least when it comes to idle power consumption, at this point. Later processors will implement an integrated voltage regulator, per part adaptive voltage, and more to lower further power consumption.

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