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uptime.lab

🛠️ Hackathon every day
Hello! I'm Ivan. Here I post my daily work as well as my personal projects. Unique devices and inventions almost every day

Uptime Lab
Sometimes unpacking goes too far... Have you ever Sometimes unpacking goes too far...
Have you ever seen Qualcomm Snapdragon Compute Platform?
These are the insides of the device from the last picture in the carousel. I bought it a few months ago. Windows 11 ARM on board. Not very fast, even compared to the Raspberry, but will do as a media server or as part of a Ci/Cd system to test on Windows 11 under the ARM platform.
Ordered some more devices that don't have official Microsoft support, but hopefully, Windows will work.
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#disassembly #hardware #apcsilmic #windows11 #qualcomm #snapdragon
It really frustrates me that my home computer some It really frustrates me that my home computer sometimes starts doing woohoo. In spite of all kinds of software settings. The 5950x is a very hot processor. Especially during rendering. Decided to radically solve the problem and close my teenage gestalt (I like PC modding for decades). By assembling a water cooling system. And at the same time to make myself a birthday present (it was on the 1st of June).
This will be my first experience assembling such a system and I already found a little hack to simplify the task. Figured out how to make a stencil for hard tubing to find the best bends, etc. There are the "hands" from a cheap "third hand" tool. Even the thread fits 🙂
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#watercooling #hardware #pccooling #pcmodding #ekwb
We haven't heard from the UpBerry device in a long We haven't heard from the UpBerry device in a long time. And they are generally doing great.
Three versions (0.3, 0.5, 0.7) in production, they replaced 1 Chomebox and 2 Chromebits in the company where I work full time. And the oldest UpBerry has been running for 8 months already O_o.
I think these devices have a great future and I will get back to them as soon as I can. What I can say for sure is that it will be Open Source, but when unfortunately I can't say. As soon as I can... 
The device is based on the Raspberry Pi Compute Module 4. Anodized aluminum case with a plastic bottom. Button (in the hole) for flashing or accessing CM4 internal memory from another computer by USB.
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#raspberrypi4 #raspberrypi #UpBerry #hardware #cncmachining #diyelectronics
I built a demo stand to test the Jetson Nano. Did I built a demo stand to test the Jetson Nano.
Did you know that the original dev board is compatible with Raspberry Pi HATs? Including PoE Hat. 
The HDMI port in the photo has a screen emulator plugged in
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#raspberrypi #nvidia #jetsonnano #hardware #poweroverethernet #developers
Just thoughts about the Jetson Nano based cluster. Just thoughts about the Jetson Nano based cluster.
Looks like Jetson can be nice option for Compute Node concept which I showed a few months ago (repeated on the last picture in the carousel). Carrier board can be the size of Raspberry Pi 4
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#raspberrypi4 #jetsonnano #nvidia #computeblade #hardware #diyelectronics #engineering
Demonstration of the Fan Unit powering system for Demonstration of the Fan Unit powering system
for the BladeRunner. This is the enclosure for Compute Blades.
Fan Unit gets power from both blades and switches without shutting down the logic.
There is also feedback (you can find out where the power comes from) and the ability to specify which blade the Fan Unit will take power from.
A detailed description of the features in the previous post. But I'll repeat it here 🙂
- Based on RP2040 and EMC2101
- PWM fan
- 2 temperature sensors
- 2 UARTs for interfacing with blades
- Button that can be assigned to any action
- 2 LEDs for indicating which blade is working
- 2 Digital RGB LEDs
- 1 LED to GPIO25
- Reset and boot buttons
Without SMD components, it can work with one blade in normal PWM fan mode (the blade can control it and know the rotation speed). This is a kind of simple model.
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#raspberrypi #RP2040 #computeblade #raspberrypi4 #soldering #diyelectronics #hardware
Fan Unit for Compute Blade enclosure. Power Multip Fan Unit for Compute Blade enclosure. Power Multiplexer Debugging
I messed up the logic and had to remove GND on one pin and add a pull-down resistor for the other pin.
But in the end, it works as planned:
Fan Unit gets power from both blades.
Well, from one (which has more voltage, i.e., if the voltage drops on one of the blades due to CPU load, the Fan Unit will not be an unnecessary consumer). It switches without shutting down the logic. There is also feedback (you can find out where the power comes from) and the ability to specify which blade the Fan Unit will take power from.
Other features:
- Based on RP2040 and EMC2101
- PWM fan
- 2 temperature sensors
- 2 UARTs for interfacing with blades
- Button that can be assigned to any action
- 2 LEDs for indicating which blade is working
- 2 Digital RGB LEDs
- 1 LED to GPIO25
- Reset and boot buttons
- USB-C for firmware update 
Without SMD components, it can work with one blade in normal PWM fan mode (the blade can control it and know the rotation speed). This is a kind of simple mode. 
Tomorrow I'll share a video demonstration not to spam here, but it's already on Twitter (nickname "merocle") 🙂
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#raspberrypi #computeblade #hardware #soldering #diyelectronics #RP2040 #adafruit
Compute Blades platform or BladeRunner 🔪 For 20 Compute Blades platform or
BladeRunner 🔪
For 20 nodes in 1 rack unit (19 inch)
3D printed enclosure with 10 PWM fans 40*40*20 mm.
Each Blade is a carried board for Raspberry Pi CM4 with NVMe SSD (up to 22110) and PoE (and many other features)
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P.S. Most of you know this, but for new subscribers it might be interesting. More about Blades on Twitter (nickname "merocle") and on the website, link in the profile. There is the review, and change-log article with all features and progress.
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#raspberrypi #3dprinted #3ddruck #raspberrypi4 #computeblade #hardware #servers #kubernetes
Jetson AGX Xavier Developer Kit It has very outsta Jetson AGX Xavier Developer Kit
It has very outstanding features, some of them:
512-core Volta GPU with Tensor Cores
8-core ARM v8.2 64-bit CPU, 8MB L2 + 4MB L3
32GB 256-Bit LPDDR4x | 137GB/s
32GB eMMC 5.1
(2x) NVDLA Engines
7-way VLIW Vision Processor
(2x) 4Kp60 | HEVC/(2x) 4Kp60 | 12-Bit Support
x8 PCIe Gen4/x8 SLVS-EC
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When I have time, I wanted to attach it to my four-legged robot.
For now, just some pictures, the device is awesome itself.
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#nvidia #jetsonagxxavier #machinelearning #hardware #developer #computervision #robots
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