sdk News - Page 14 of 52 - CNX Software

May 9, 2019 by Jean-Luc Aufranc (CNXSoft) - No Comments

Espressif Rolls out ESP32 Boards for Microsoft Azure IoT & Google Cloud IoT Core Services

Espressif ESP32 WiFi & Bluetooth processor is pretty versatile, and you could connect any ESP32 board to any cloud services with some efforts. But to make things even easier Espressif Systems worked with Microsoft and Google to release versions of ESP32 boards specifically designed to connect to Microsoft Azure IoT or Google Cloud IoT core. Meet ESP32-Azure IoT Kit and ESP32-DevKitC Google Cloud IoT. ESP32-Azure IoT Kit Hardware specifications: Wireless Module – ESP32-WROVER-B WiFi and Bluetooth module Storage – MicroSD card socket Display – 0.96” blue and yellow OLED display driven by SSD1306 I2C driver chip Sensors InvenSense MPU6050 motion sensor NXP MAG3110 magnetometer FBM320 barometer STMicro HTS221 humidity & temperature sensor ROHM BH1750FVI light sensor Expansion – 16-pin header Debugging – USB to UART bridge for serial debugging & programming Misc – Reset button, user button, 2x charge LED’s, 2x user LED’s, 1x passive buzzer Power Supply – 5V […]

May 5, 2019May 5, 2019 by Jean-Luc Aufranc (CNXSoft) - 1 Comment

Grove AI HAT Helps Raspberry Pi Run Edge Computing Workloads

Last year we wrote about Kendryte K210 dual core RISC-V processor specifically designed for for machine vision and machine hearing as well as the corresponding Kendryte KD233 which enables inference at the edge, e.g. tasks such as face recognition or object detection. Latter on we found the processor in Sipeed M1 module which went for as low as $5 in a crowdfunding campaign, and was fitted to some low cost boards now selling for $12.90 on Seeed Studio. The latter company has now designed Grove AI HAT that aims to assist Raspberry Pi in running the edge computing workloads previously described, as exposes 6 Grove interfaces to extend functionality with some of the Grove add-on modules. Grove AI HAT specifications: AI Module – Sipeed “MAIX” M1 with Kendryte K210 dual core RISC-V processor @ 600 MHz, KPU Convolutional Neural Network (CNN) hardware accelerator, APU audio hardware accelerator, 8 MB general […]

April 30, 2019April 30, 2019 by Jean-Luc Aufranc (CNXSoft) - 15 Comments

Rockchip RK1808 Datasheet, TRM, Schematics and Linux SDK Released

Rockchip RK1808 is the first chip from the company fully dedicated to artificial intelligence applications. The Neural Processing Unit (NPU) features an accelerator delivering up to 3.0 TOPS and is coupled with two low power Arm Cortex-A35 cores allowing it to run Linux. We’ve had the specifications for RK1808 for a while, but the company has recently posted hardware and software resources on their open source website. On the hardware side we’ve got: RK1808 Technical Reference Manual (TRM) RK1808 datasheet PDF Schematics for the company’s official RK1808-EVB On the software side we can get the Linux SDK from Github as explained in the Wiki:

git clone https://github.com/rockchip-linux/repo
mkdir linux
cd linux
../repo/repo init --repo-url=https://github.com/rockchip-linux/repo -u https://github.com/rockchip-linux/manifests -b master -m rk1808_linux_release.xml
../repo/repo sync

git clone https://github.com/rockchip-linux/repo

mkdir linux

cd linux

../repo/repo init --repo-url=https://github.com/rockchip-linux/repo -u https://github.com/rockchip-linux/manifests -b master -m rk1808_linux_release.xml

../repo/repo sync

Finally configure the build and start the build process:

sudo apt install liblz4-tool build-essential
source envsetup.sh rockchip_rk1808
./build.sh

sudo apt install liblz4-tool build-essential

source envsetup.sh rockchip_rk1808

./build.sh

After a while, or more accurately close to two hours on a Laptop with Ryzen 7 2700U processor, 8GB RAM, and hard drive, we’ll get U-boot, Linux, buildroot based rootfs, and firmware files and in […]

April 18, 2019 by Jean-Luc Aufranc (CNXSoft) - No Comments

MIPS Based TritonAI 64 AI IP Platform to Enable Inferencing & Training at the Edge

After announcing their first MIPS Open release a few weeks ago, Wave Computing is back in the news with the announcement of TritonAI 64, an artificial intelligence IP platform combining MIPS 64-bit + SIMD open instruction set architecture with the company’s WaveTensor subsystem for the execution of convolutional neural network (CNN) algorithms, and WaveFlow flexible, scalable fabric for more complex AI algorithms. TritonAI 64 can scale up to 8 TOPS/Watt, over 10 TOPS/mm2 using a standard 7nm process node, and eventually would allow both inference and training at the edge. The platform supports 1 to 6 cores with MIPS64r6 ISA boasting the following features: 128-bit SIMD/FPU 8/16/32/int, 32/64 FP datatype support Virtualization extensions Superscalar 9-stage pipeline w/SMT Caches (32KB-64KB), DSPRAM (0-64KB) Advanced branch predict and MMU Integrated L2 cache (0-8MB, opt ECC) Power management (F/V gating, per CPU) Interrupt control with virtualization 256b native AXI4 or ACE interface Here’s the […]

April 15, 2019 by Jean-Luc Aufranc (CNXSoft) - 8 Comments

Novasom M7 SBC aims to be a Drop-In Replacement for Raspberry Pi 3 in Industrial Projects

Raspberry Pi boards are great for education and hobbyist projects, and while they are also found in industrial projects, they may not be the ideal solution for such commercial projects because of potential availability issues, stability issues in demanding environments, lack of certifications, and lack of commercial support. Novasom RASPMOOD family of SBCs aims to provide a drop-in replacement for Raspberry Pi based designs by providing mechanically and electrically compatible boards, as well as a software layer that allows the RASPMOOD boards to leverage the software you’ve already developed for your Raspberry Pi 3 design. Today we’ll specifically look at Novasom M7 “RASPMOOD” board – aka SBC-M7 – powered by a Rockchip RK3328 processor. Specifications: SoC – Rockchip RK3328 quad core Cortex-A53 processor with Mali-450MP4 GPU System Memory – Up to 4 GB DDR3 RAM Storage – Up to 256 GB eMMC Flash + uSD slot Video Output – HDMI […]

March 14, 2019 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Android Q Beta and Preview SDK Released

Google has just announced the first public release of Android Q dubbed “Beta 1”- for Pixel devices only – as well as the corresponding preview SDK for developers. Android Q is said to bring additional privacy and security features for users, enhancements for foldables, new APIs for connectivity, new media codecs and camera capabilities, NNAPI extensions, Vulkan 1.1 support, faster app startup, and more. What’s new in Android Q Privacy protections improvements More control over location with multiple options to “allow all the time”, “allow only while the app is in use” (e.g. not while running in the background), and “deny” Users will be able to control apps’ access to the Photos and Videos or the Audio collections via new runtime permissions Android Q will prevent apps from launching an Activity while in the background, relying on high-priority notifications instead Access to non-resettable device identifiers, including device IMEI, serial number, […]

March 11, 2019 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

HiSilicon Hi3559A Board Enables Smart 8K Camera Development

HiSilicon Hi3559A 5-core Arm Cortex A73/A53 camera processor was announced in 2017 with support for 8K 30fps or 4K 120fps video recording, as well as an integrated dual core neural network accelerator (NNA). It should not be confused with the earlier Hi3559 4K 30 fps processor, or the newer Hi3559C that looks to be the same as Hi3559A without the NNA. Nevertheless, today I was lead to check about Hi3559A processor once again, and I could not find any camera that you can just buy and use today. I still found some upcoming Hi3559A products with OBSBOT Tail AI camera offered for as low as $509 on Kickstarter (delivery scheduled for April 2019), one 4K 120fps OEM? camera from GKuvision, as well as an HiSilicon Hi3559A development board for 8K camera applications, which I’ll look into more details in this blog post. HI3559AV100DMEB specifications: SoC – Hisilicon Hi3559A V100 with […]

November 22, 2018June 4, 2019 by Jean-Luc Aufranc (CNXSoft) - 10 Comments

Orange Pi AI Stick 2801 Neural Compute Stick SDK & Documentation Released

We covered the launch of Orange Pi AI Stick 2801 neural compute stick a few days ago, the first easily available Gyralcon Lightspeeur based USB stick, and noted that while the hardware was there, we had no details about software development kit and documentation at the time. I’ve got some more information now. First, the company release an English presentation about the neural stick, and while it’s not technical documentation, it provides insights into what it is capable of, and an overview about the workflow. More importantly, Shenzhen Xunlong Software also released Orange Pi AI Stick SDK and user manual for x86 PC, as well as cat/dog data and pre-trained models to get started. However, if you want to perform training with your own data, you’ll need to purchase the stick plus PLAI model transformation and training tools sold on Aliexpress for $218 plus shipping, that’s $69 for the hardware, […]