deep learning News - Page 2 of 4 - CNX Software

July 20, 2018July 21, 2018 by Jean-Luc Aufranc (CNXSoft) - 5 Comments

Firefly Baidu Face Recognition Kit Comes with Monocular, Binocular, or Structured Light Camera

Firefly AIO-3399J industrial board comprised of a Rockchip RK3399 SoM and a baseboard offering plenty of I/O & connectivity options has been bundled with various other accessories including a 10.1″ touchscreen display, and cameras to create a development platform for Baidu AI offline (aka “at the edge”) face recognition technology. The development kit is available in different variants with either a monocular camera, a binocular camera, or a structured-light camera. There’s also a deluxe kit with WiFi and a stand. Baidu Face Recognition Kit key specifications: SoC – Rockchip RK3399 hexa-core big.LITTLE processor with dual core ARM Cortex A72 up to 2.0 GHz and quad core Cortex A53 processor, ARM Mali-T860 MP4 GPU with OpenGL 1.1 to 3.1 support, OpenVG1.1, OpenCL and DX 11 support System Memory – 2GB DDR3 RAM Storage – 16GB eMMC 5.1 flash, micro SD card slot Display – 10.1″ 1280×800 capacitive touch display Connectivity – […]

July 10, 2018July 10, 2018 by Jean-Luc Aufranc (CNXSoft) - 11 Comments

96-Core NanoPi Fire3 Boards Cluster is a DIY Portable Solution to Teach or Develop Distributed Software

Nick Smith has been messing around with clusters made of Arm boards for several years starting with Raspberry Pi boards, including a 5-node RPI 3 cluster, before moving to other boards like Orange Pi 2E, Pine A64+, or NanoPC-T3. His latest design is based on twelve NanoPi Fire3 boards with 8 cores each, bringing the total number of cores to 96. The platform may not be really useful for actual HPC applications due to limited power and memory, but can still be relied upon for education and development, especially it’s easily portable. Nick also made some interesting points and discoveries. It’s pretty with shiny blinking LEDs, and what looks like proper cooling, and the cluster can deliver 60,000 MFLOPS with Linpack which places it in the top 250 faster computers in the world! That’s provided we travel back in time to year 2000 through 🙂 By today’s standard, it would […]

June 20, 2018June 20, 2018 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Raspberry Pi 3 and Movidius Neural Compute Stick to the Rescue Against Child Pornography

Warning note: While there won’t be any NSFW photos in this post, there will be some photos of ladies in light clothing (e.g. bikini) and “naked” animals for testing purpose… Intel released Movidius Neural Compute Stick allowing low power image recognition at the edge earlier this year, and we’ve seen it work just fine with Raspberry Pi 3 board delivering three times the performance against an inference solution leveraging VideoCore IV GPU. Christian Haschek owns a photo hosting site (PictShare) which happens to run open source code with the same name, and allows user to upload images anonymously. However, he soon found out that at least one user uploaded some child pornography. He contacted the authorities, but then wondered whether there may be others? Since there are simply too many photo on the website to look it up manually, he decided to look for a solution, and went with a […]

June 8, 2018June 8, 2018 by Jean-Luc Aufranc (CNXSoft) - No Comments

Imagination Unveils PowerVR AX2185 and AX2145 Neural Network Accelerators (NNA)

Imagination Technologies introduced PowerVR Series2NX neural network accelerator (NNA) last year. At the time, the company claimed the NNA would deliver twice the performance at half the bandwidth over existing competing solutions, and that it was the first dedicated hardware solution with flexible bit-depth support from 16-bit down to 4-bit. What they did not announce last September were any specific parts. But they’ve just done that today with PowerVR AX2185 and AX2145 NNAs “designed to enable high-performance computation of neural networks at very low power consumption in minimal silicon area”. PowerVR AX2185 PowerVR AX2185 is said to be the highest performing neural network accelerator per mm2 in the market with eight full-width compute engines delivering up to 4.1 TOPS (Tera Operations Per Second), or 2,048 MACs/clock. AX2185 NNA can deliver 3.5 times the performance compared to a desktop GPU. The NNA is best suited for high-end smartphones, smart surveillance and […]

June 4, 2018July 12, 2018 by Jean-Luc Aufranc (CNXSoft) - 5 Comments

NVIDIA Introduces Jetson Xavier Devkit and Isaac Robotics Software

NVIDIA Xavier was first unveiled in September 2016 as an artificial intelligence SoC with eight NVIDIA Custom 64-bit Arm cores, a 512-core Volta GPU, 8K video encoding and decoding, and a computer vision accelerator (CVA) now called NVDLA (NVIDIA Deep Learning Accelerator). Earlier this year, the company announced Xavier was sampling, and DRIVE IX & DRIVE AR SDKs for the automotive market. On the eve of Computer 2018, NVIDIA has introduced Jetson Xavier development kit, as well as Isaac robotics software for autonomous machines. Jetson Xavier key specifications: SoC – NVIDIA Xavier with 8-core ARMv8.2 64-bit CPU, 8MB L2 + 4MB L3 512-core Volta GPU with Tensor Cores 2x NVDLA engines for deep learning 7-way VLIW Processor for vision acceleration VPU with dual 4Kp60 video decoding and encoding System Memory – 16GB 256-bit LPDDR4x | 137 GB/s Storage – 32GB eMMC 5.1 flash Display – 3x eDP/DP/HDMI at 4Kp60 | […]

March 19, 2018March 28, 2019 by Jean-Luc Aufranc (CNXSoft) - 22 Comments

96Boards Unveils Four A.I. Developer Platforms: HiKey 970, Ultra96, ROCK960 PRO & Enterprise Edition

Many new processors include a Neural Processing Unit (NPU) – aka Neural Network Accelerator (NNA) – in order to speed up talks associated with artificial intelligence, such as object or other patterns recognitions. With Linaro Connect Hong Kong 2018, 96Boards has just unveiled four development boards specifically designed for artificial intelligence solution with Hikey 970 powered by Hisilicon Kirin 970 processor, Ultra96 based on Xilinx Zynq UltraScale+ ZU3EG ARM+ FPGA SoC, and ROCK960 PRO & Enterprise Edition featuring the upcoming Rockchip RK3399Pro processor. Hikey 970 Preliminary specifications: SoC – Kirin 970 with 4x Cortex A73 @ 2.36GHz, 4x Cortex A53 @ 1.8GHz, Arm Mali G72-MP12 GPU, NPU with 256MAC/cycle @ 960MHz System Memory – 6GB 1866MHz, 4 Channel LPDDR4x Storage -64GB UFS storage, micro SD card slot Video Output – HDMI 1.4 up to 1080p60 Camera – 4 lanes CSI + 2 lanes CSI Connectivity – Gigabit Ethernet, wireless module, […]

January 8, 2018January 8, 2018 by Jean-Luc Aufranc (CNXSoft) - 17 Comments

Rockchip RK3399Pro SoC Integrates a 2.4 TOPS Neural Network Processing Unit for Artificial Intelligence Applications

Rockchip RK3399 (aka OP1) SoC was launched in 2016 with an hexa core Arm Cortex A72/A53 processor, Mali-T860MP4 GPU, support for 4K video decoding, and high speed interfaces like USB 3.0 and PCIe, as well as Gigabit Ethernet. The processor is found in Chromebooks, TV boxes, development boards, and other devices. The company has unveiled an upgraded “Pro” version of the processor at CES 2018. Rockchip RK3399Pro appears to have most of the same features as its predecessor but adds a neural network processing unit (NPU) delivering up to 2.4 TOPS for artificial intelligence and deep learning applications. The company claims that compared to traditional solution, the computing performance of typical deep neural network Inception V3, ResNet34 and VGG16 models on RK3399Pro is improved by almost one hundred times, and power consumption is less than 1% than A.I. solutions implemented using GPU acceleration. Based on the information provided in the […]

January 3, 2018June 4, 2019 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

Laceli AI Compute Stick is a More Powerful & Efficient Alternative to Intel/Movidius Neural Compute Stick

Intel’s Movidius Neural Compute Stick is a low power deep learning inference kit and “self-contained” artificial intelligence (A.I.) accelerator that connects to the USB port of computers or development boards like Raspberry Pi 3, delivering three times more performance than a solution accelerated with VideoCore IV GPU. So far it was the only A.I USB stick solution that I heard of, but Gyrfalcon Technology , a US startup funded at the beginning of last year, has developed its own “artificial intelligence processor” with Lightspeeur 2801S, as well as a neural USB compute stick featuring the solution: Laceli AI Compute Stick. The company claims Laceli AI Compute Stick runs at 2.8 TOPS (Trillion operation per second) performance within 0.3 Watt of power, which is 90 times more efficient than the Movidius USB Stick that can deliver 100 GFLOPS (0.1 TOPS) within 1 Watt of power. Information about the processor and stick […]