Testing NVIDIA Jetson Nano Developer Kit with and without Fan

Jetson Nano 52Pi-ICE Tower Cooling Fan

A few weeks ago I received NVIDIA Jetson Nano for review together with 52Pi ICE Tower cooling fan which Seeed Studio included in the package, and yesterday I wrote a getting started guide showing how to setup the board, and play with inference samples leveraging the board’s AI capabilities. I’ll now test the board with the stock heatsink in both 5W and 10W modes, and see if thermal throttling does occur, and then I’ll fit the tower cooling fan to find out if we can extract more performance that way and how much lower the CPU temperature is. Jetson Nano Stress Tests with Stock Heatsink Let’s install SBC-Bench testing utility, check it’s properly installed, and run it in 5W mode: The temperature never went over 44.5°C, and no throttling occurred. tegrastats during 7-zip multi-core test: Only two Cortex-A57 cores are used even under load, and power consumption is around 3.3 Watts. Let’s run sbc-bench in 10W mode: The maximum temperature …

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Getting Started with NVIDIA Jetson Nano Devkit: Inference using Images, RTSP Video Stream

Jetson Nano RTSP Stream Inference

Last month I received NVIDIA Jetson Nano developer kit together with 52Pi ICE Tower Cooling Fan, and the main goal was to compare the performance of the board with the stock heatsink or 52Pi heatsink + fan combo. But the stock heatsink does a very good job of cooling the board, and typical CPU stress tests do not make the processor throttle at all. So I had to stress the GPU as well, as it takes some efforts to set it up all, so I’ll report my experience configuring the board, and running AI test programs including running objects detection on an RTSP video stream. Setting up NVIDIA Jetson Nano Board Preparing the board is very much like you’d do with other SBC’s such as the Raspberry Pi, and NVIDIA has a nicely put getting started guide, so I won’t go into too many details here. To summarize: Download the latest firmware image (nv-jetson-nano-sd-card-image-r32.2.3.zip at the time of the review) …

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ROCK PI N10 RK3399Pro SBC Sells for $99 and up

Rock Pi N10 RK3399Pro SBC

Rockchip RK3399Pro processor is based on the popular Rockchip RK3399Pro hexa-core Arm Cortex-A72/A53 processor plus an embedded neural processing unit (NPU) delivering up to 3 TOPS for AI acceleration. So far you had to spend over $200 to get either Toybrick RK3399Pro board or 96Boards RK3399Pro development kit to get started with the processor. Some other companies announced their own RK3399Pro SBC such as Pine64  RockPro64-AI, or Khadas Edge board, but those are not available yet. But there’s now a more affordable Rockchip RK3399Pro SBC courtesy of Radxa’s  Rock Pi N10 available on Seeed Studio in three variants: $99 model A with 4GB RAM (3GB for CPU/GPU + 1GB for NPU), 16GB eMMC flash $129 model B with 6GB RAM (4GB for CPU/GPU + 2GB for NPU), 32GB eMMC flash $169 model C with 8GB RAM (4GB for CPU/GPU + 4GB for NPU), 64GB eMMC flash Rock Pi N10 specifications: SoC – Rochchip RK3399Pro hexa-core big.LITTLE processor with 2x Cortex …

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Think Silicon NEOX|V is the First RISC-V ISA based GPU

RISC-V GPU

We are seeing more and more RISC-V microcontrollers and processors hitting the market, but so far they all lacked a GPU for 3D graphics acceleration. Think Silicon, the make of NEMA GPU for IoT and wearables, has now announced it will demonstrate NEOX|V GPU, the first RISC-V ISA based 3D, at the RISC-V Summit at the San Jose Convention Center, on December 10-12, in San Jose, California. NEOX|V key features: Parallel multi-core and multi-threaded architecture based on the RISC-V64GC ISA instruction set with adaptive NoC (Networks-on-Chip) Configurable from 4 to 64 cores Variety of cache sizes and thread counts organized in 1 to 16 cluster elements Variety of cluster/core configurations with compute power ranging from 12.8 to 409.6 GFLOPS at 800 MHz Support for FP16, FP32, and FP64 plus SIMD instructions Beside 3D graphics, the RISC-V GPU can also be used for machine learning, vision/video processing, and open GPGPU compute framework applications. NEOX|V SDK features System Verilog RTL, Integration Tests, …

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Imagination Unveils IMG A-Series GPU Designed For Everything from IoT to Mobile and Server

IMG A-Series GPU

Imagination Technologies has just launched IMG A-Series GPU which they claim is “The GPU of Everything” and “The fastest GPU IP ever”. IMG A-Series can be customized and scaled for various applications & markets from automotive, AIoT, set-top box, mobile, and server.  Compared to the company’s earlier PowerVR 9Series GPU, IMG A-Series GPU delivers 2.5 times more performance, eight times faster AI processor, and 60% less power while running complex content with the same process node, area, and under similar conditions. IMG A-Series GPU supports the latest API standards including OpenGL ES, Vulkan, OpenCL, and Imagination provides a Unified AI API for use in combination with PowerVR neural network accelerators. It also offers 5x performance density compared to the best current shipping PowerVR devices and supports PVRIC4 lossless or virtually-lossless compression guaranteeing a 50% bandwidth and footprint reduction. The new GPU also leverages HyperLane Technology with up to eight individual, isolated hardware control lanes for multizone hardware virtualization leading to …

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Orange Pi 4/4B Board with RK3399, 4GB RAM Launched for $50 and Up

Orange Pi 4

Orange Pi 4 is yet another Rockchip RK3399 SBC with 4GB RAM, while Orange Pi 4B adds Gyrfalcon Lightspeeur 2801A AI Accelerator. Both models were announced about 10 days but were not for sale just yet. The company has now launched the board on both Aliexpress and their newly opened Amazon store with three options: Orange Pi 4 with no eMMC flash – $49.90 Orange Pi 4 with 16GB eMMC flash – $59.90 Orange Pi 4B with 16GB eMMC flash, Gyrfalcon NPU – $69.90 Quick reminder of Orange Pi 4/4B specifications: SoC – Rockchip K3399 hexa-core big.LITTLE processor with two Arm Cortex A72 cores, four Cortex A53 cores, and an ARM Mali-T860 MP4 GPU with support for OpenGL ES 1.1 to 3.1 support, OpenVG1.1, OpenCL and DX 11 System Memory – 4 GB LPDDR4 Storage – Optional 16 GB eMMC flash, micro SD card NPU (Orange Pi 4B only) – Gyrfalcon Lightspeeur SPR2801S NPU delivering up to 2.8TOPS @ 300mW, 5.6 …

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Hacarus Embedded AI Computing Kit Leverages Sparse Modeling Technology

Hacarus AI Computing Kit Sparse Modeling Technology

AI training often requires thousands of samples to become accurate, and it can be costly and time-consuming, for example, if you want to train a model to detect manufacturing defects you’d need to provide images with both defective samples and good samples. Japanese AI experts at Hacarus have been working on a solution called Sparse Modeling which requires about 50 samples or even less for training, and worked with Congatec to provides an embedded AI computing kit leveraging the technology. Sparse Modeling Technology Hacarus does not go into great detail but explains Sparse Modeling technology is using a data modeling approach that focuses on identifying unique characteristics, in a way that humans recognize friends and family without having to look at everything from feet to head. That means algorithms based on Sparse Modeling do not need as much data as traditional AI solutions, leading to much smaller AI footprint suitable for fanless low-power systems operating 24/7, and/or that may a …

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AAEON BOXER-8220AI Embedded Box PC Features NVIDIA Jetson Nano, 5 Gigabit Ethernet Ports

Jetson Nano Embedded Mini PC

AAEON has launched several AI Boxer-8000 series embedded box PCs based on Intel processors plus AI accelerator, or NVIDIA Jetson TX2. The company has now introduced a new model – BOXER-8220AI – based on NVIDIA Jetson Nano module, and equipped with five Gigabit Ethernet ports. AAEON BOXER-8220AI specifications: SoM (CPU/Memory/Storage) – NVIDIA Jetson Nano with quad-core Arm Cortex-A57 MPCore processor @ 1.43 GHz, 128-core Maxwell GPU. 4GB LPDDR4, 16GB eMMC flash or MicroSD card Video Output – HDMI 2.0 Connectivity – 5x Gigabit Ethernet ports USB – 4x USB 3.0 ports, 1x Micro USB to flash the OS Serial – 2x RS-232 Misc – Power button, recovery button, power LED Power Supply – 10-24V DC via 2-pin terminal block Dimensions – 154 x 101 x 30 mm Weight – 1 kg Temperature Range – Operating: -20°C ~ 60°C, according to IEC60068-2 with 0.5 m/s AirFlow; storage: -45°C ~ 80°C Storage Humidity – 95% @ 40°C, non-condensing Anti-Vibration – 3 Grms/ …

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