Startup Claims It Can Boost CPU Performance By 2-100X

Although Moore’s Law has slowed at bit as chip makers reach the physical limits of transistor size, researchers are having to look to other things other than cramming more transistors on a chip to increase CPU performance. ARM is having a bit of a moment by improving the performance-per-watt of many computing platforms, but some other ideas need to come to the forefront to make any big pushes in this area. This startup called Flow Computing claims it can improve modern CPUs by a significant amount with a slight change to their standard architecture.

It hopes to make these improvements by adding a parallel processing unit, which they call the “back end” to a more-or-less standard CPU, the “front end”. These two computing units would be on the same chip, with a shared bus allowing them to communicate extremely quickly with the front end able to rapidly offload tasks to the back end that are more inclined for parallel processing. Since the front end maintains essentially the same components as a modern CPU, the startup hopes to maintain backwards compatibility with existing software while allowing developers to optimize for use of the new parallel computing unit when needed.

While we’ll take a step back and refrain from claiming this is the future of computing until we see some results and maybe a prototype or two, the idea does show some promise and is similar to some ARM computers which have multiple cores optimized for different tasks, or other computers which offload non-graphics tasks to a GPU which is more optimized for processing parallel tasks. Even the Raspberry Pi is starting to take advantage of external GPUs for tasks like these.

Make Your Code Slower With Multithreading

With the performance of modern CPU cores plateauing recently, the main performance gains are with multiple cores and multithreaded applications. Typically, a fast GPU is only so mind-bogglingly quick because thousands of cores operate in parallel on the same set of tasks. So, it would seem prudent for our applications to try to code in a multithreaded fashion to take advantage of this parallelism. Or so it would seem, but as [Marc Brooker] illustrates, it’s not as simple as one would assume, and it’s very easy to end up with far worse overall performance and no easy way to fix it.

[Marc] was rerunning an old experiment to calculate the expected number of birthdays in a shared group of people using brute force. The experiment was essentially a tight loop running a pseudorandom number generator, the standard libc rand() function. [Marc] profiled the code for single-thread and multithreaded versions and noted the runtime dramatically increased beyond two threads. Something fishy was going on. Running perf, [Marc] noted that there were significant L1 cache misses, but the real killer for performance was the increase in expensive context switches.  Perf indicated that for four threads, the was an overhead of nearly 50% servicing spin locks. There were no locks in the code, so after more perf magic, the syscalls taking all the time were identified.  Something in there was using a futex (or fast userspace mutex) a whole lot.

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Upgrading PC Cooling With Software

As computing power increases with each new iteration of processors, actual power consumption tends to increase as well. All that waste heat has to go somewhere, and while plenty of us are content to add fans and heat sinks for a passable air-cooled system there are others who prefer a liquid cooling solution of some sort. [Cal] uses a liquid cooler on his system, but when he upgraded his AMD chip to one with double the number of cores he noticed the cooling fans on the radiator were ramping quickly and often. To solve this problem he turned to Python instead of building a new cooling system.

The reason for the rapid and frequent fan cycling was that the only trigger for the cooling fans available on his particular motherboard is CPU temperature. For an air cooled system this might be fine, but a water cooled system with much more thermal mass should be better able to absorb these quick changes in CPU temperature without constantly adjusting fan speed. Using a python script set up to run as a systemd service, the control loop monitors not only the CPU temperature but also the case temperature and the temperature of the coolant, and then preferentially tries to dump heat from the CPU into the thermal mass of the water cooler before much ramping of cooling fans happens.

An additional improvement here is that the fans can run at a much lower speed, reducing dust in the computer case and also reducing noise compared to before the optimizations. The computer now reportedly runs almost silently unless it has been under load for several minutes. The script is specific to this setup but easily could be modified for other computers using liquid cooling, and using Grafana to monitor the changes can easily be done as [Cal] also demonstrates when calibrating and testing the system. On the other hand, if you prefer a more flashy cooling system as a living room centerpiece, we have you covered there as well.

Op-Amp Drag Race Turns Out Poorly For 741

When it was first introduced in 1968, Fairchild’s 741 op-amp made quite a splash. And with good reason; it packed a bunch of components into a compact package, and the applications for it were nearly limitless. The chip became hugely popular, to the point where “741” is almost synonymous with “op-amp” in the minds of many.

But should it be? Perhaps not, as [More Than Electronics] reveals with this head-to-head speed test that compares the 741 with its FET-input cousin, the TL081. The test setup is pretty simple, just a quick breadboard oscillator with component values selected to create a square wave at approximately 1-kHz, with oscilloscope probes on the output and across the 47-nF timing capacitor. The 741 was first up, and it was quickly apparent that the op-amp’s slew rate, or the rate of change of the output, wasn’t too great. Additionally, the peaks on the trace across the capacitor were noticeably blunted, indicating slow switching on the 741’s output stage. The TL081 fared quite a bit better in the same circuit, with slew rates of about 13 V/μS, or about 17 times better than the 741, and nice sharp transitions on the discharge trace.

As [How To Electronics] points out, comparing the 741 to the TL081 is almost apples to oranges. The 741 is a bipolar device, and comparing it to a device with JFET inputs is a little unfair. Still, it’s a good reminder that not all op-amps are created equal, and that just becuase two jelly bean parts are pin compatible doesn’t make them interchangeable. And extra caution is in order in a world where fake op-amps are thing, too.

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Robotic Acrobot Aces The Moves

[Daniel Simu] is a performance artist, among many other things, and does acrobatic shows, quite often with a partner “flyer”. Training for his acts gets interrupted if his flyer partner is not available due to travel, injury or other reasons. This prompted him to build Acrobotics — a robotic assistant to make sure he can continue training uninterrupted.

He has some electronics and coding chops, but had to teach himself CAD so that he could do all of the design, assembly and programming himself. Acrobotics was developed as part of a Summer Sessions residency at V2_ (Lab for the Unstable Media) at Rotterdam in 2022.

The design is built around a mannequin body and things are quite simple at the moment. There are only two rotational joints for the arms at the shoulder, and no other articulations. Two car wiper motors rotate the two arms 360 deg in either direction. Continuous rotation potentiometers attached to the motors provide position feedback.

An ESP32 controls the whole thing, and the motors get juice via a pair of BTS7960 motor drivers. All of this is housed in a cage built from 15 mm aluminium extrusion and embedded in the torso of the mannequin. [Daniel] doesn’t enlighten us how the motor movements are synchronized with the music, but we do see a trailing cable attached to the mannequin. It’s likely the cable could be for power delivery, as well as some form of data or timing signals.

He’s working on the next version of the prototype, so we hope to see improved performances soon. There’s definitely scope for adding a suite of sensors – an IMU would help a lot to determine spatial orientation, maybe some ultrasonic sensors, or a LiDAR for object detection or mapping, or additional articulated joints at the elbows and wrists. We gotta love “feature creep”, right ?

Check out the two videos after the break – in the first one, he does an overview of the Acrobotics, and the second one is the actual performance that he did. Robot or not, it’s quite an amazing project and performance.
CAVEAT : We know calling this a “robot” is stretching the definition, by a lot, but we’re going to let it slip through.

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3D Printed Circular Prototype Performance Prop Captivates Circus Spectators

When mathematically inspired maker [Henry Segerman] conspired with circus performer and acrobat [Marcus Paoletti] to advance the craft of acrobatics in round metal objects (such as cyr wheels and German Wheels), they came up with a fascinating concept that has taken shape in what [Henry] calls the Tao-Line.

Similar performance devices go in a straight line or can be turned on edge, but the Tao-Line is far more nimble. This is because the Tao-Line is not a continuous cylinder, but rather is made up of numerous circular shapes that allow the Tao-Line to be turned and inverted at different points in its rotation.

While a circus prop might not be your average Hackaday fare, it’s noteworthy because the Tao-Line started off as a 3D printed prototype, which was then turned into the metal fabrication you see in the video below the break.  It’s an excellent example of how modeling complex shapes as a physical product- not just a 3D model on the screen- can be helpful in the overall design and construction of the full scale piece.

If you’re looking to build something that’s under the big top but not quite so over the top, you might enjoy this mixed-media digital clock. Thanks to [Keith] for the great tip. Be sure to submit send your cool finds via the Tip Line!

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Guitar Pickguard Adds MIDI Capabilities

For a standard that has been in use since the 1980s, MIDI is still one of the most dominant forces on the musical scene even today. It’s fast, flexible, and offers a standard recognized industry-wide over many different types of electronic instruments. Even things which aren’t instruments can be turned into musical devices like the infamous banana keyboard via the magic of MIDI, and it also allows augmentation of standard instruments with other capabilities like this guitar with a MIDI interface built into the pick guard.

[Ezra] is the creator of this unique musical instrument which adds quite a few capabilities to his guitar. The setup is fairly straightforward: twelve wires run to the pick guard which are set up as capacitive sensors and correspond with a note on the chromatic scale. Instead of using touchpads, using wires allows him to bend away the “notes” that he doesn’t need for any particular piece of music. The wires are tied back to an Adafruit Feather 32u4 microcontroller behind the neck of the guitar which also has a few selectors for changing the way that the device creates tones. He can set the interface to emit single notes or continuously play notes, change the style, can change their octave, and plenty of other features as well.

One of the goals of this project was to increase a guitar player’s versatility when doing live performances, and we would have to agree that this gives a musician a much wider range of abilities without otherwise needing a lot of complex or expensive equipment on stage. We’ve seen a few other MIDI-based builds focused on live performances lately, too, like this one which allows a band to stay in sync with each other.

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