Overclocking Raspberry Pi 5’s SoC To 3 GHz And 1 GHz GPU

Overclocking computer systems is a fun way to extract some free performance, or at least see how far you can push the hardware before you run into practical limitations. The newly released Raspberry Pi 5 with BCM2712 SoC is no exception here, with Tom’s Hardware having a go at seeing how far both the CPU and GPU in the SoC can be pushed. The BCM2712’s quad Cortex-A76 CPU is normally clocked at 2.4 GHz and the VideoCore VII GPU at 800 MHz. By modifying some settings in the /boot/config.txt configuration file these values can be adjusted.

In order to verify that an overclock was stable, the Stressberry application was used, which fully loads the CPU cores. Here something like a combination of stress-ng and glxgears could also be used, to stress both the CPU and GPU. With the official actively cooled heatsink the CPU reached a temperature of 74°C with a whole board power usage of about 10 Watts. At idle this dropped to 3 Watts at 46°C. At these speeds, the multiple Raspberry Pi 5 units OCed by Tom’s Hardware were mostly stable, though one of the team’s boards experienced a few crashes. This suggests that this level of OCing could still be subject to luck of the draw, and long-term stability would have to be investigated as well.

As for the practical use cases of OCing your Raspberry Pi 5, benchmarks showed a marked uplift in compression and Sysbench benchmark scores, but OCing the GPU had no real positive impact on YouTube or 3D performance, leading even to a massive increase in dropped frames with video playback. This probably means that increasing the CPU clock may be beneficial, but OCing the GPU could be futile without also OCing the RAM frequency, if at all possible.

Realistically, the Raspberry Pi SoCs never were speed monsters, with even the Raspberry Pi 4B’s SoC being beaten handily in 2020 by a budget dual-core Intel CPU.  The current Intel Alder-Lake-N-based N100 SoC has a 6 Watt TDP and boosts up to 3.4 GHz while its Xe-LP-based iGPU (with AV1 decoding support) makes for a decent gaming experience within a ~16 Watt power envelope. Clearly, any OCing of the Raspberry Pi boards is more for the challenge of it, but then so is running the latest Intel CPU at 10 GHz with liquid nitrogen cooling.

Turing Complete Programming On ARM With Two Instructions

There are many questions that can be asked for software projects, with most of these questions starting with ‘Why…?’. This is true for the challenge of proving that cascading stylesheets are Turing-complete, or that you don’t need all those fancy ISA bits of an ARM processors when you already got the LDM and STM commands in the 32-bit ISA. What originally started off as a bit of a running gag in a group of developers led to [Kellan Clark] implementing a Turing-complete computer and a functioning interpreter using nothing but these two opcodes.

Adding some Brainfsck to your ARM, inside your GBA.
Adding some Brainf**k to your ARM, inside your GBA.

These two opcodes essentially allow the storing or reading of data into memory from any combination of the 16 general-purpose registers (GPRs). This makes them both extremely versatile and also extremely open to ‘abuse’ like in this example. For a straightforward implementation that could prove the concept, [Kellan] decided to pick one of everyone’s favorite esoteric programming languages: Brainf**k, creating the charmingly titled Armf**k that allows anyone to write BF programs for any suitable ARM processor, like the ARM7TDMI in the Game Boy Advance that [Kellan] targeted.

As a proof of concept it’s unquestioningly intriguing, and a great example of how the most powerful parts of any ISA are those that move data around. After all, as anyone who writes ASM and C knows, computers are just machines that can copy bytes around really fast to make stuff happen. Mind-blowing examples like these serve to illustrate that point quite well.

Tip kindly provided by [eeucalyptus].

The Questionable Benefits Of Paying More For Air Quality Monitors

Does paying more for air quality monitors (AQMs) make sense? This was the question which [Achim Haug] at the Air Gradient project sought to answer, with the answer being a rather revealing ‘not at all’. Using data from the independent South Coast Air Quality Management District agency (South Coast AQMD), a plot was created of a range of commercially available AQMs for PM2.5 pollutants and their performance against a reference monitor. Here a value of 1.00 would mean performance equal to the (expensive, calibrated) reference.

R2 vs Price. Data Source: South Coast AQMD Data
R2 vs Price. Data Source: South Coast AQMD Data

This plot shows clearly that paying more for an AQM does not get you better performance, with the reason for this explored in a follow-up article by [Achim], where a range of AQMs are checked for which PM2.5 sensors they actually use. Perhaps unsurprisingly, most AQMs use the same PM2.5 sensors, with the sensor module not really affecting the cost of the AQM as they all cost about $10-20 in bulk.

Rather it seems that the other sensors (for CO2, NO2 and other measurements) along with features such as WiFi, LoRa determine much of the price tag. For getting good measurements, properties such as airflow over the sensors, the implemented compensation algorithms are probably the main things you want to look at when purchasing (or building)  an AQM.

(Heading image: particulate matter sizes, relative to a human hair. Credit: California ARB)

The Robot That Lends The Deaf-Blind Community A Hand

The loss of one’s sense of hearing or vision is likely to be devastating in the way that it impacts daily life. Fortunately many workarounds exist using one’s remaining senses — such as sign language — but what if not only your sense of hearing is gone, but you are also blind? Fortunately here, too, a workaround exists in the form of tactile signing, which is akin to visual sign language, except that it uses one’s sense of touch. This generally requires someone who knows tactile sign language to translate from spoken or written forms to tactile signaling. Yet what if you’re deaf-blind and without human assistance? This is where a new robotic system could conceivably fill in.

The Tatum T1 in use, with a more human-like skin covering the robot. (Credit: Tatum Robotics)
The Tatum T1 in use, with a more human-like skin covering the robot. (Credit: Tatum Robotics)

Developed by Tatum Robotics, the Tatum T1 is a a robotic hand and associated software that’s intended to provide this translation function, by taking in natural language information, whether spoken, written or in some digital format, and using a number of translation steps to create tactile sign language as output, whether it’s the ASL format, the BANZSL alphabet or another. These tactile signs are then expressed using the robotic hand, and a connected arm as needed, ideally using ASL gloss to convey as much information as quickly as possible, not unlike with visual ASL.

This also answers the question of why one would not just use a simple braille cell on a hand, as the signing speed is essential to keep up with real-time communications, unlike when, say, reading a book or email. A robotic companion like this could provide deaf-blind individuals with a critical bridge to the world around them. Currently the Tatum T1 is still in the testing phase, but hopefully before long it may be another tool for the tens of thousands of deaf-blind people in the US today.

Do Bounties Hurt FOSS?

As with many things in life, motivation is everything. This also applies to the development of software, which is a field that has become immensely important over the past decades. Within a commercial context, the motivation  to write software is primarily financial, in that a company’s products are developed by individuals who are being financially compensated for their time. This is often different with Free and Open Source Software (FOSS) projects, where the motivation to develop the software is in many cases derived more out of passion and sometimes a wildly successful hobby rather than any financial incentives.

Yet what if financial incentives are added by those who have a vested interest in seeing certain features added or changed in a FOSS project? While with a commercial project it’s clear (or should be) that the paying customers are the ones whose needs are to be met, with a volunteer-based FOSS project the addition of financial incentives make for a much more fuzzy system. This is where FOSS projects like the Zig programming language have put down their foot, calling FOSS bounties ‘damaging’.

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Beating Apple’s Secret Lid Angle Sensor Calibration With Custom Tool

Among the changes made by Apple to its laptops over the years, the transition from a Hall sensor-based sleep sensor to an angle sensor that determines when the lid is closed is a decidedly unpopular one. The reason for this is the need to calibrate this sensor after replacement, using a tool that Apple decided to keep for itself. That is, until recently [Stephan Steins] created a tool which he creatively called the ‘nerd.tool.1‘. This widget can perform this calibration procedure with the press of its two buttons, as demonstrated on [Louis Rossmann]’s YouTube channel.

This new angle sensor was first introduced in late 2019, with Apple’s official reason being an increased level of ‘precision’. As each sensor has to be calibrated correctly in order to measure the magnetic field and determine the associated lid angle, this means that third-party repair shops and determined MacBook owners have to transplant the chip containing the calibration data to a replacement sensor system. Until now, that is. Although the nerd.tool.1 is somewhat pricey at €169 ($179 USD), for a third-party MacBook repair shop this would seem to be a steal.

It is however unfortunate that Apple persists in such anti-repair methods, with recently [Hugh Jeffreys] also calling Apple out on this during a MacBook Pro M1/M2 teardown video. During this teardown [Hugh] came across this angle sensor issue by swapping parts between two otherwise identical MacBook Pros, indicating just how annoying this need to calibrate one tiny lid angle sensor is.

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Reviving An Old Lime-E Beta Rideshare E-Bicycle

What do you do when you come across a cheap electric bicycle on Facebook Marketplace from a seller who has a few hundred of the same ones available? If you’re someone like [Max Helmetag], you figure that it’s probably legit since nobody would be reselling hundreds of Lime ridesharing e-bikes. Thus, it makes for an excellent project to see how usable an old ridesharing bicycle is. According to the information on the e-bike’s frame, it was manufactured in 2017, and based on the plastic still covering parts of the bike, it had barely been used, if at all.

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