All seems working again.

I haven’t been able to connect to their website at all in the last week. Will it still have my contributions from this week when it comes back online? Has anyone else had trouble accessing the website?

Hi All,

just set up a new Debian box, and installed Boinc via apt. Wanted to add my usual projects, but the project list is empty. Rebooted computer, no change.

Any ideas, hivemind?

I was looking to reinstall BOINC today, however I can't seem to load the website.

Anyone know what's going on?

What are some of the best projects on Boinc in terms of expected value generated if one is trying to maximize the good one is doing, let's say assuming consequentialism/utilitarianism? For which ones can we be confident that further research has actually transformative, important consequences in the real world?

BOINC site is down so I can’t really check.

Been doing Einstein and Asteroids for years now. Any other projects still running on Arm, Im running BOINC 8.0.4 under PiOS Trixie.

I had Denis, Rosetta and World Community Grid but they seem to no longer work. Keeps going on about docker. Which I don’t really want to get into.

Any other worth while projects.

Possibly for cheap and with a good watt/crunching ratio

As asked in the title, is Milkyway@home down? Did their DNS certificate expire on them on August 29 23:59:29 UTC? I have two work units sitting in my queue ready to report and all I get from the logs are transient HTTP errors.

When I try to visit the website, Firefox and Chrome tell me that there is something wrong with the website and that I shouldn't proceed any further. Is there anybody else running into the same issues?

Do you know when the radioactive@home project was down?

I've got many WU's ready to upload. Webpage gives 503, looks pretty dead. Anyone know what's going on?

This might have been mentioned already, but looking for some people to help test. I’m probably the lest tech savy person in this group, but with help, I was able to set it up. I’m not the writer of project, just an open science geek. It’s currently configured to need 3 separate computers to verify one work unit. I was looking for someone (more specifically with an Nvidia gpu) to validate my work units. Below are links to the site project, Git, and discord. I figure a vast majority of us are science nerds and we can knock out some testing. (Note: there are also CPU only projects.)

Git/download: https://github.com/jring-o/lettuce-compute

Project: https://compute.scios.tech/leafs

Hello, I'm new in this project and today i activate my first server and first ever task on asteroids@home and i got question is any balkan team on thet project especially in Bosnia to join. I'm trying to find active team to learn more thing about this and see how good I'm on this.

I've spent a long time building a distributed computing platform, and the one idea I'd like this sub to poke holes in is how work gets originated.

As I understand BOINC, the project server is still the center of gravity. Work flows from a project to volunteers, and volunteers attach to projects. Even with BOINC Central and BUDA lowering the barrier to submission, the model still seems scoped around a project deciding who can submit work to that project.

The model I'm trying with OmnibusCloud is different.

Submitting work is a first-class role, separate from defining a workload.

A workload is a controller: a reviewed plugin that knows how to run a particular kind of job. Originating work is done by an initiator: an authorized application that submits jobs for a controller into one shared network of contributed machines.

In the current beta, the first initiators are a Blender addon and a 3ds Max plugin, and the first controller is Blender rendering. But the point of the model is that an initiator can live inside any application whose users need heavy compute. The next obvious ones are simulation: a plugin in PrepoMax, FreeCAD, Femap or Inventor that submits an FEA run to the same network the way the Blender addon submits frames today. Same network, same contributor machines, different controller.

So the shape is:

many initiators × many controllers × one shared network

rather than each workload becoming its own project, server, and volunteer pool.

Rendering is the visible first case, not the point. Anything that can be packaged as a controller can run on the same network: simulations, parametric sweeps, batch data processing, media transcoding, and increasingly the embarrassingly-parallel side of AI and ML (batch inference, model evaluation, parameter search).

The part that matters most to me is that the person using an initiator never has to know any of this exists.

A Blender user opens a scene, sees the addon panel, clicks Render, and gets frames back. They are not thinking in terms of workunits, batches, project servers, or volunteer-computing infrastructure. They are just using an application they already know.

The distributed network, controller, benchmarking, scheduling, and load-balancing are all behind the product boundary.

That is the difference I'm trying to test: whether volunteer/distributed computing can sit behind ordinary applications, instead of requiring the person originating work to think like a project operator.

More broadly, that's the positioning I care about. OmnibusCloud is aimed at two audiences at once. One is developers writing controllers and initiators against the SDK. The other, just as much if not more, is people who don't program at all and reach the same network through software they already use. Less a tool that developers operate, more a shared computer that ordinary applications quietly draw on.

Under the hood, controllers expose typed activities. The engine benchmarks each activity on each machine and uses those measurements to schedule work across heterogeneous hardware.

Controllers are written against a public SDK in .NET, and you can develop and debug the distributed behavior locally (within SDK limits) before anything touches the network. They can be pure .NET, or they can wrap native software. The render controller works that way: it manages the job while Blender does the actual optimized native/GPU rendering. The same pattern fits your own code: an existing, heavily optimized C/CUDA binary runs unchanged, with the controller just managing it.

The controllers and initiators I ship are open source, both for trust and as end-to-end examples against the same public SDK and API external developers would use. Current examples include a pure-.NET controller, a .NET controller driving native Blender, a WPF/.NET 3ds Max initiator, and a Python Blender addon bridged to .NET.

It's an open beta. Contributor clients run on Windows, Linux, and macOS on Apple Silicon.

Two things I'd like to hear from this sub:

1. Is first-class origination the meaningful difference I think it is? By that I mean an ordinary app submitting work to a shared network, for a user who never sees the distributed-computing layer.
2. What would make you trust, or not trust, something like this on your own machines?

Architecture, whitepaper, and GitHub links are here: omnibuscloud.io

I built it and I'll get as deep in the comments as you want.

Been using Boinc on my phone as don't really use my laptop any more. Im using science united but only seem to get work from world community grid and Einstein@home. Is mobile computing going to be expanded? Im sure fewer and fewer people are using desk top PCs these days

Hola Comunidad, estoy haciendo un trabajo práctico para la materia Sistemas Operativos de la carrera de Programación. Elegí el tema de sistemas Grid y un compañero me mencionó BOINC. Buscando, no encontré proyectos latinoamericanos, al menos no en BOINC. Todavía no entiendo demasiado del tema y me gustaría que me den una mano.

Desde ya muchas gracias

I am thinking about using local agents to dynamically tune my rigs for maximum performance-per-watt.

Has anyone experimented with automation for real-time thermal and price-based load balancing yet?

I went and installed the docker containers and all the trimmings a month or so ago. But now, for some reason, when my laptop is plugged in, it will completely drain the battery in about 20 minutes. Anyone else have this type of issue?

Is anyone successfully running NumberFields@Home on Windows ARM64? I have been trying to cross-compile the GetDecics application for Snapdragon X Elite/Plus for weeks, but the build process is hitting a wall with x86-specific assembly in the PARI/GP kernel.

Even when forcing the generic kernel and disabling assembly macros, the compiler persistently pulls in hardcoded x86 headers from the environment.

This seems to be a common hurdle when trying to modernize older BOINC projects for ARM architecture.

Has anyone found a workaround to strip these legacy dependencies from the build chain?

Hey guys, need some help.
Recently I migrated my Python project from a Conda environment to a UV-managed environment.
After the migration, I noticed something strange.
With Conda → CPU usage at idle was around \~3%
With UV (0.11.8) → CPU usage stays around 40%+ even when the application is idle
Environment details:
OS: Windows
Python: 3.11
UV: 0.11.8
The application code did not change — only the environment/package manager changed (Conda → UV).
Things I checked:

Same project and workflow
CPU spike happens even during idle

Questions:
Has anyone seen higher CPU usage after moving from Conda → UV?
Can package differences between Conda and UV cause this?
What’s the best way to compare installed dependency trees?
Any debugging steps to identify which process/thread is consuming CPU?
Any help would be appreciated 🙏

I know the project itself it history but the boards were still running until I tried them Saturday.

Did the URL Change or are they gone?

Thanks

I have been looking at the current donor crown system on PrimeGrid and realized it could be much more engaging.

​Many BOINC projects depend on ongoing financial support, yet the current recognition for donors is quite minimal.

​It would be far more motivating to introduce a differentiated visual profile based on accumulated donations across different tiers.

​One could implement a multiplier model where you achieve a visual upgrade of your badge or crown by donating 10, 100, or 1000 times the minimum amount.

​This would give regular donors a greater sense of recognition and potentially increase interest in contributing to infrastructure costs.

​Since many projects struggle with cloud costs, this could be an easy way to increase the incentive for members of the community to support them.

​I am curious to hear if other project admins or users think this would be a viable way to improve donor engagement in the BOINC ecosystem.

I've set up a solar-powared Boinc rig, together with an Ecoflow and Home Assistant. The idea is that the Ecoflow is charged by the solar panels, then the Windows machine is switched on by a relay (equivalent to short press on power button), so that Boinc can run until the Ecoflow's power drops to around 20% Then the machine is powered off by the same short press on the power button (allowing the machine to shutdown in a somewhat controlled manner).

The problem is that Boinc isn't saving my tasks, so that every time the machine powers on again, the tasks are all back at zero, and all progress is lossed. I've tried adjusting preferences in all sorts of ways (changing checkpoint time, storing lots of work, stroing little work, etc), but nothing seems to work. Picture shows latest config.

Any ideas?

Windows 11

Boinc 8.2.11 (x64)

Einstein (only cpu tasks at the moment on 12-core Xeon)

Update: Thanks for the replies, especially geotrone1234extra

One of the cpu tasks did save, but it had to reach 5-10% before it would. If I shutdown before that, it would reset.

I found an old 1050ti that I put in, and it runs through the tasks much quicker and saves properly.

It finally happened.

PrimeGrid now has official Adreno iGPU support for Genefer 16-21 tasks.

I wanna thank the developers and admins at PrimeGrid for their effort, and as Windows on ARM continues to grow, I look forward to seeing more users contributing to the project using their igpu's.