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January 17, 2020 by Jean-Luc Aufranc (CNXSoft) - 8 Comments

NVIDIA Jetson Nano Developer Kit-B01 Gets an Extra Camera Connector

Launched in March 2019, NVIDIA Jetson Nano developer kit offered an AI development platform for an affordable $99. The kit is comprised of Jetson Nano module and a carrier board, and the version I received last November ended with “A02”. Jetson Nano developer kit is now getting updated with B01 carrier board that adds an extra MIPI CSI connector and other few changes, including compatibility with NVIDIA Jetson Nano production module (with eMMC flash instead of MicroSD card). Jetson Nano developer kit-B01 specifications: B01 Jetson Nano CPU Module 128-core Maxwell GPU Quad-core Arm A57 processor @ 1.43 GHz System Memory – 4GB 64-bit LPDDR4 @ 25.6 GB/s Storage – microSD card slot Video Encode – 4K @ 30 | 4x 1080p @ 30 | 9x 720p @ 30 (H.264/H.265) Video Decode – 4K @ 60 | 2x 4K @ 30 | 8x 1080p @ 30 | 18x 720p @ 30 […]

December 9, 2019December 10, 2019 by Jean-Luc Aufranc (CNXSoft) - 4 Comments

Testing NVIDIA Jetson Nano Developer Kit with and without 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,

wget https://raw.githubusercontent.com/ThomasKaiser/sbc-bench/master/sbc-bench.sh
chmod +x sbc-bench.sh

1 2	wget https://raw.githubusercontent.com/ThomasKaiser/sbc-bench/master/sbc-bench.sh chmod +x sbc-bench.sh

check it’s properly installed,

sudo ./sbc-bench.sh -m
Time        CPU    load %cpu %sys %usr %nice %io %irq   Temp
15:05:06:  922MHz  0.05   5%   1%   2%   0%   0%   0%  35.0°C
15:05:11:  922MHz  0.13   3%   1%   1%   0%   0%   0%  35.0°C
15:05:16:  922MHz  0.12   3%   1%   1%   0%   0%   0%  34.8°C

sudo ./sbc-bench.sh -m

Time CPU load %cpu %sys %usr %nice %io %irq Temp

15:05:06: 922MHz 0.05 5% 1% 2% 0% 0% 0% 35.0°C

15:05:11: 922MHz 0.13 3% 1% 1% 0% 0% 0% 35.0°C

15:05:16: 922MHz 0.12 3% 1% 1% 0% 0% 0% 34.8°C

and run it in 5W mode:

sudo nvpmodel -m 1

sudo ./sbc-bench

sbc-bench v0.6.9

Memory performance:
memcpy: 3685.3 MB/s 
memset: 8555.4 MB/s 

7-zip total scores (3 consecutive runs): 2877,2885,2854

OpenSSL results:
type             16 bytes     64 bytes    256 bytes   1024 bytes   8192 bytes  16384 bytes
aes-128-cbc     284837.64k   525113.11k   639412.05k   706251.09k   728449.02k   729841.66k
aes-128-cbc     284316.13k   525028.93k   634287.70k   704675.84k   728088.58k   728973.31k
aes-192-cbc     262002.90k   458230.17k   544725.93k   588999.68k   604075.35k   604607.83k
aes-192-cbc     261583.66k   458583.96k   538986.92k   588138.84k   602303.15k   604067.16k
aes-256-cbc     247370.60k   405101.35k   466444.29k   501432.32k   512816.47k   513370.79k
aes-256-cbc     247650.51k   405270.40k   469783.72k   502266.54k   513187.84k   512977.58k

Full results uploaded to http://ix.io/23rg. Please check the log for anomalies (e.g. swapping
or throttling happenend) and otherwise share this URL.

sudo nvpmodel -m 1

sudo ./sbc-bench

sbc-bench v0.6.9

Memory performance:

memcpy: 3685.3 MB/s

memset: 8555.4 MB/s

7-zip total scores (3 consecutive runs): 2877,2885,2854

OpenSSL results:

type 16 bytes 64 bytes 256 bytes 1024 bytes 8192 bytes 16384 bytes

aes-128-cbc 284837.64k 525113.11k 639412.05k 706251.09k 728449.02k 729841.66k

aes-128-cbc 284316.13k 525028.93k 634287.70k 704675.84k 728088.58k 728973.31k

aes-192-cbc 262002.90k 458230.17k 544725.93k 588999.68k 604075.35k 604607.83k

aes-192-cbc 261583.66k 458583.96k 538986.92k 588138.84k 602303.15k 604067.16k

aes-256-cbc 247370.60k 405101.35k 466444.29k 501432.32k 512816.47k 513370.79k

aes-256-cbc 247650.51k 405270.40k 469783.72k 502266.54k 513187.84k 512977.58k

Full results uploaded to http://ix.io/23rg. Please check the log for anomalies (e.g. swapping

or throttling happenend) and otherwise share this URL.

The temperature never went over 44.5°C, and no throttling occurred. tegrastats during 7-zip multi-core test:

CPU [100%@1428,100%@1428,off,off] EMC_FREQ 3%@1600 GR3D_FREQ 0%@76 APE 25 PLL@41.5C CPU@43.5C PMIC@100C GPU@43.5C AO@52.5C thermal@43.5C POM_5V_IN 3348/2567 POM_5V_GPU 0/0 POM_5V_CPU 1549/912
RAM 1211/3956MB (lfb 515x4MB) SWAP 0/1978MB (cached 0MB) IRAM 0/252kB(lfb 252kB) CPU [100%@1428,100%@1428,off,off] EMC_FREQ 3%@1600 GR3D_FREQ 0%@76 APE 25 PLL@41.5C CPU@44C PMIC@100C GPU@43.5C AO@52C thermal@43.5C POM_5V_IN 3348/2568 POM_5V_GPU 0/0 POM_5V_CPU 1549/912
RAM 1239/3956MB (lfb 508x4MB) SWAP 0/1978MB (cached 0MB) IRAM 0/252kB(lfb 252kB) CPU [100%@1428,100%@1428,off,off] EMC_FREQ 3%@1600 GR3D_FREQ 0%@76 APE 25 PLL@41.5C CPU@44C PMIC@100C GPU@43.5C AO@52.5C thermal@43.5C POM_5V_IN 3348/2569 POM_5V_GPU 0/0 POM_5V_CPU 1549/913
RAM 1265/3956MB (lfb 502x4MB) SWAP 0/1978MB (cached 0MB) IRAM 0/252kB(lfb 252kB) CPU [100%@1428,100%@1428,off,off] EMC_FREQ 3%@1600 GR3D_FREQ 0%@76 APE 25 PLL@41.5C CPU@43.5C PMIC@100C GPU@43.5C AO@52.5C thermal@43.5C POM_5V_IN 3348/2571 POM_5V_GPU 0/0 POM_5V_CPU 1510/914

CPU [100%@1428,100%@1428,off,off] EMC_FREQ 3%@1600 GR3D_FREQ 0%@76 APE 25 PLL@41.5C CPU@43.5C PMIC@100C GPU@43.5C AO@52.5C thermal@43.5C POM_5V_IN 3348/2567 POM_5V_GPU 0/0 POM_5V_CPU 1549/912

RAM 1211/3956MB (lfb 515x4MB) SWAP 0/1978MB (cached 0MB) IRAM 0/252kB(lfb 252kB) CPU [100%@1428,100%@1428,off,off] EMC_FREQ 3%@1600 GR3D_FREQ 0%@76 APE 25 PLL@41.5C CPU@44C PMIC@100C GPU@43.5C AO@52C thermal@43.5C POM_5V_IN 3348/2568 POM_5V_GPU 0/0 POM_5V_CPU 1549/912

RAM 1239/3956MB (lfb 508x4MB) SWAP 0/1978MB (cached 0MB) IRAM 0/252kB(lfb 252kB) CPU [100%@1428,100%@1428,off,off] EMC_FREQ 3%@1600 GR3D_FREQ 0%@76 APE 25 PLL@41.5C CPU@44C PMIC@100C GPU@43.5C AO@52.5C thermal@43.5C POM_5V_IN 3348/2569 POM_5V_GPU 0/0 POM_5V_CPU 1549/913

RAM 1265/3956MB (lfb 502x4MB) SWAP 0/1978MB (cached 0MB) IRAM 0/252kB(lfb 252kB) CPU [100%@1428,100%@1428,off,off] EMC_FREQ 3%@1600 GR3D_FREQ 0%@76 APE 25 PLL@41.5C CPU@43.5C PMIC@100C GPU@43.5C AO@52.5C thermal@43.5C POM_5V_IN 3348/2571 POM_5V_GPU 0/0 POM_5V_CPU 1510/914

Only two Cortex-A57 cores are used even under load, and power […]

December 7, 2019June 25, 2021 by Jean-Luc Aufranc (CNXSoft) - 3 Comments

AI inference using Images, RTSP Video Stream on NVIDIA Jetson Nano Devkit

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 […]

November 11, 2019May 16, 2020 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

NVIDIA Jetson Nano Review with 52Pi ICE Tower Cooling Fan – Part 1: Unboxing

Jetson Nano Review with ICE Tower Cooling Fan

If you remember soon after Raspberry Pi 4 launch, there were talks about the SBC overheating under load, and depending on room temperature and workload a heatsink may be needed for the board to perform optimally at all times. This gave birth to “interesting” solutions such as 52Pi ICE Tower Cooling Fan, an oversized cooling solution for Raspberry Pi 4. It does the job however, and it allows me to overclock Raspberry Pi 4 to 2.0 GHz while keeping the CPU temperature under 55°C in a room at 28°C. But the latest Raspberry Pi Foundation board is not the only SBC to suffer from overheating, as at least one user noticed the board would just shutdown under load. The solution was to switch from 10W mode to 5W mode, not an ideal solution since it’s also lowering performance. But 52Pi is coming to the rescue again, as they adapted their […]

November 7, 2019November 7, 2019 by Jean-Luc Aufranc (CNXSoft) - 6 Comments

NVIDIA Jetson Xavier NX SoM Delivers up to 21 TOPS for AI Workloads at the Edge

NVIDIA has just announced Jetson Xavier NX system-on-module, with the company claiming it is the “world’s smallest, most powerful AI supercomputer for robotic and embedded computing devices at the edge” with a 70x45mm “Jetson Nano” form factor, and delivering either up to 14 TOPS at 10 Watts or 21 TOPS at 15 Watts. The company expects the module to be used in small commercial robots, drones, intelligent high-resolution sensors for factory logistics and production lines, optical inspection, network video recorders, portable medical devices, and other industrial IoT systems. Jetson Xavier NX specifications: SoC – NVIDIA Xavier with 6-core NVIDIA Carmel ARM v8.2 64-bit CPU, 6MB L2 + 4MB L3 caches, and a 384-core NVIDIA Volta GPU with 48 Tensor Cores, 2x NVDLA deep learning accelerators delivering up to 21 TOPS at 15 Watts System Memory – 8 GB 128-bit LPDDR4x @ 51.2GB/s Storage – 16 GB eMMC 5.1 flash Video […]

October 29, 2019 by Jean-Luc Aufranc (CNXSoft) - 17 Comments

NVIDIA Launches Upgraded Shield TV with Tegra X1+ Processor

Ever since NVIDIA launched the Shield TV in 2015 it features in lists of best Android TV boxes in the $200 budget range, although it can raise to close to $300 if you do not live in a country where the Shield TV is not officially sold. The company launched a more compact version in 2017, and NVIDIA just officially announced upgraded Shield TV and Shield TV Pro 2019 models with a more powerful Tegra X1+ Processor delivering a 25% boost, as well as Dolby Atmos and Dolby Vision support. As you can see from the photo above the Shield TV now has a completely different cylindrical design, while the Shield TV Pro keeps the traditional design of the box. However, both share many of the same specifications: SoC – NVIDIA Tegra X1+ processor with a 256-core NVIDIA GPU Memory & Storage Shield: 2 GB RAM; 8GB eMMC flash; MicroSD card […]

July 24, 2019 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Waveshare Jetbot AI Kit for NVIDIA Jetson Nano Board Sells for $100 and Up

NVIDIA Jetson Nano developer kit was launched for $99 last March with impressive specifications for the price including one module with four Arm Cortex-A57 cores, a 128-core Maxwell GPU, and 4GB LPDDR4 RAM. The company also introduced Jetbot robot based on the new board, with all instructions available on Github, but until now you had to put some efforts to build it up as the fairly long list of parts had to be purchased or 3D printed separately. It’s now become easier, as Waveshare has started selling their Jetbot AI kit on Amazon for $122.99 without Jetson Nano, and $259.99 with, meaning you may be better off purchasing NVIDIA board separately for around $100, or you may purchase the complete kit directly on Waveshare website for $215.99 plus shipping, or $99.99 without the SBC. Jetbot AI kit content: Optional NVIDIA Jetson Nano SBC 64GB micro SD Card Metal box Camera […]

March 22, 2019March 22, 2019 by Jean-Luc Aufranc (CNXSoft) - 6 Comments

ZED Depth and Motion Tracking Camera Supports NVIDIA Jetson Nano Board

When NVIDIA launched their low cost Jetson Nano development board earlier this week, one reader asked whether it would support binocular depth mapping. It turns out Stereo Labs has updated the SDK (Software Development Kit) for the ZED depth and motion tracking camera in order to support the latest NVIDIA developer kit. Jetson Nano can manage depth and positional tracking at 30 fps in PERFORMANCE mode with 720p resolution, and while the more powerful and expensive Jetson TX2 achieves doubles the performance at 60 fps, it does so at a much higher cost. ZED depth and motion tracking camera specifications: Video 2.2K @ 15 fps (4416×1242 resolution) 1080p @ 30 fps (3840×1080 resolution) 720p @ 60 fps (2560×720 resolution) WVGA @ 100 fps (1344×376 resolution) Depth Resolution – Same as selected video resolution Range – 0.5 to 20 m Format – 32-bits Stereo Baseline – 120 mm Motion 6-axis Pose […]