Recent items from the news feeds of various BOINC projects.

[YAFU] Aliquot sequence 3612120 has terminated!!!

Aliquot sequence 3612120 has terminated!!!

View article · Wed, 7 May 2025 20:21:59 +0000

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[YAFU] Aliquot sequence 3786600 has terminated!!!

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View article · Fri, 2 May 2025 18:48:28 +0000

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[Minecraft@Home] Xoroshigo2 v1.06 - MacOS

Hi everyone,

We've added some new binaries for this project to allow macs to run.
Both x86 and ARM64 based macs should run just fine.

The linux and windows binaries remain at v1.05, there'd be nothing new for them if we did bump them to 1.06.
Macos is on 1.06 because I uncovered a bug in my deployment of the macos binaries and had to use a version bump to replace the old version.

Anyway, something interesting I've discovered is that M1 (and really, all apple silicon so far) LOVES these tasks.

On a sample mini task, I got 120 seconds on my 12700k, and 61 seconds on my M1 macbook air.
On the same sample mini task, one of our project developers tried it on their M4 Pro and got 43 seconds.
Of course, that's not perfectly reflective of runtimes, but I expect to see apple silicon based machines top the charts for this app based on these preliminary results.

Happy crunching, everyone!

View article · Wed, 23 Apr 2025 23:49:47 +0000

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[Minecraft@Home] New Badges

Hi everyone,

I've added the following new badges while I was doing some database work today.

1. 1.21 Panorama badge. It's a copper bulb block from Minecraft, which is a block found in Trial Chambers. The pano121 app attempted to find a seed which produces a particular trial chamber matching the one found in the title screen panorama for 1.21.
2. Xoroshigo v1.0. This art was created largely by the lead developer of the xoroshigo project, but I added the "alpha" symbol at the bottom right to represent that it was the first run of the app before optimizations were made.
3. Xoroshigo v1.1. Same art as v1.0, but without the alpha symbol.
4. Xoroshigo Infinity. Same art as v1.0 and v1.1, but with an infinity symbol. I attempted to identify everyone who submitted a task after deadline during the time we had a broken version of the app running that caused runtimes measuring in multiple days for some configurations. If you believe I missed you in error, please let me know. We're in the middle of optimizing the amount of data we're storing in our database, so I may need to review previous versions of the data to ensure I don't miss anybody.

I also managed to re-run the badge assignment for the tall cactus project from years ago. Around 2300 or so participants gained the badge, congratulations!
The discrepancy was likely caused by the method that the previous administrator before me used to apply the badge. Since it did not use a sql clause, it likely used a "snapshot" of data without keeping it updated.

All that said, I will probably also add a loneliest seed badge tonight before I wrap up, but I'll update here if I do.

Thanks for your patience as we've been working diligently to get things running smoothly here.

View article · Mon, 21 Apr 2025 06:22:16 +0000

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[Minecraft@Home] Xoroshigo2 v1.05 - Runtime fix

Hi everyone,

I appreciate your patience while we worked through this.

v1.05 addresses the extreme runtime issues we've been facing lately.

I would recommend cancelling any v1.04 tasks that are running too long.

I'm looking into ways we can credit those who attempted to run broken v1.04 tasks, but as far as I can tell, boinc does not support that scenario. So I don't have an answer quite yet.

I'm deploying some more tasks worth 10,000 credits each as a consolation for this.

Please let me know if you run into any issues.

View article · Fri, 18 Apr 2025 21:45:46 +0000

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View article · Tue, 15 Apr 2025 18:51:09 +0000

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[Minecraft@Home] Xoroshigo2 v1.04 - New plan classes

Hello everyone,

We've generated some new work, and while I was at it, I implemented the plan class changes I alluded to in discussion with a few users who were trying to use Windows 7 to run xoroshigo.

Python does not support Windows 7 anymore, hasn't since Python 3.8 back in 2018. 3.9 made breaking changes for Windows 7 and will not run on Windows 7.

To remedy the issue, we've implemented "win-modern" and "lin-modern" as plan classes we can use if our apps won't run on older OSes.

Put simply, on linux if your GLIBC is older than 2.27, you won't get work for xoroshigo2 (or any other app that requires lin-modern - which is likely to be all of our work in the future.)
On Windows, your windows version must be 8.1 or higher.

Let us know if you run into any issues running our apps. Happy crunching!

View article · Sun, 13 Apr 2025 01:15:04 +0000

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[YAFU] Aliquot sequence 3133782 and 3277056 have terminated!!!

Aliquot sequence 3133782 and 3277056 have terminated!!!

View article · Thu, 10 Apr 2025 16:28:07 +0000

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[Minecraft@Home] Xoroshiro128++ - New version available, new input data

Hi everyone,

As I'm sure was noticed, there's a 2nd version of the "xoroshigo" project denoted by v1.1.
This new version has had changes made to its input variables that made it incompatible with the old version, so we could not run it as an updated version of the same app.

That being said, after extensive testing, we've deployed v1.02 of xoroshigo2(or v1.1.1.02, depending on who you ask) to production.
I believe there should also be a potential fix for the issue where work would not suspend when changes are made to computing preferences or work is just simply suspended.

The most notable change is that a member of our team, Andrew, developed a port of one of the most expensive functions (95+% of execution time spent in this function) used in the app to run it as native code for a 20x speedup.
We've cranked the dials, so tasks should be roughly the same size as before, but you may experience runtime variances compared to before. Overall this just means you're completing 20x what you used to in the same amount of time (cheaper on compute resources) - so the credit values are remaining the same.

There is also now an aarch64 build of this app available. We've made best efforts to test this with our limited aarch64 machines, so if any issues are encountered, please let us know.

Finally, I wanted to mention that as of now, we're enforcing a GLIBC 2.17 or above requirement for our apps going forward. I've built a lot of CI test harnesses over the last day or two that allow me to detect issues before they ever hit BOINC, and while I had been doing this already, there is now a check on our internal repo preventing any merges with binaries with a GLIBC over 2.17. This does also mean you'll need GLIBC 2.17 or higher to run the apps we build going forward.

Anyway, happy crunching! As always, please let us know if you run into any issues.

View article · Fri, 4 Apr 2025 07:46:02 +0000

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[SETI@home] Website outage

Multiple disk failure resulted in a web site outage. We think we've recovered almost everything from the web site, so it should be back up and running.

View article · Thu, 3 Apr 2025 20:49:48 +0000

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[YAFU] Aliquot sequence 3072384, 3176376, 3246240 have terminated!!!

Aliquot sequence 3072384, 3176376, 3246240 have terminated!!!

View article · Thu, 3 Apr 2025 19:04:21 +0000

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[Minecraft@Home] Xoroshiro128++ Guessing Order Optimization Project

You may have noticed some new workunits hit the queue. As of the time of writing, the workunits that are available should be considered "beta" as we're working out a few kinks.
That said, this is a new CPU app! As time goes on, we'll be replacing configuration files for it to further refine the results, so work will be sent out in stages and we'll feel out how much workunits make sense for each stage.

I've included a fairly technical explanation from the primary author of the app, MC, longtime contributor to Minecraft@Home:

The Xoroshiro Guessing Order project aims to uncover exploitable statistical weaknesses in the xoroshiro128++ pseudorandom number generator (PRNG). Recent versions of Minecraft now use xoroshiro128++ for specific aspects of world generation, replacing Java's default PRNG. Unfortunately, this shift creates significant challenges for seedcracking projects, as no efficient algorithm currently exists to reconstruct the internal state of xoroshiro from its outputs.

Our primary goal is to develop a reliable method for recovering the PRNG's 128-bit seed from just two sequential 64-bit outputs. Currently, the most efficient known method (excluding SAT solvers) involves guessing 54 bits of the state, after which the remaining bits can be derived, a process requiring roughly 9 quadrillion attempts on average. Our aim is to significantly reduce this computational requirement.

Xoroshiro128++ belongs to the "xorshift" family of PRNGs, which means its core operations are linear. The internal state can therefore be represented as a binary vector within a 128-dimensional vector space, with state transitions represented as matrix multiplications. However, the primary challenge arises from its use of a non-linear "scrambler" function, which maps the internal state to its output. Due to this scrambler, there is no straightforward one-to-one relationship between the 128-dimensional internal state and the 128-bit output.

Fortunately, the scrambler function is imperfect. Most of the information provided by each output bit is concentrated in a relatively small subset, approximately a dozen dimensions, of the total 128-dimensional state. Even with a partial, lower-dimensional guess of the state, it is frequently possible to determine whether the guess is incorrect based on the known output. If we can identify low-dimensional subsets of the state space that are significantly constrained by the outputs, we can efficiently guess and verify these smaller portions first, rapidly eliminating incorrect possibilities.

Participants in our project analyze these lower-dimensional subsets of the state space, identifying those subsets most constrained by observed outputs. To facilitate this process, we use a large precomputed table that estimates the amount of information (in bits) xoroshiro's output data provides about each subset of state dimensions.

By ultimately identifying an optimal sequence of highly constrained subspaces, we can incrementally guess the state one dimension at a time, discarding incorrect possibilities early on. Achieving this optimal guessing order would produce a highly efficient algorithm capable of recovering the PRNG's internal state within a small number of attempts, significantly advancing future efforts in Minecraft seedcracking and related research.

View article · Sat, 29 Mar 2025 05:56:02 +0000

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[Minecraft@Home] Loneliest Seed v1.08

Hi folks!

I know it's been a bit, life gets in the way sometimes. However, I've released v1.08 of the Loneliest Seed project which aims to address the checkpointing issue.

We're experimenting with a CPU project separate from this as well, so stay tuned for that! If the experiments go well on our end we're anticipating launching a CPU app that will aid us in our years-long research into finding methods of reversing PRNG states in the Xoroshiro128++ algorithm.

Best regards,
Minecraft@Home Team

View article · Wed, 26 Mar 2025 15:09:17 +0000

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[DENIS@Home] We are back! // ¡Estamos de vuelta!

Dear volunteers,
We are back! The wait has been longer than we would have liked, but surprisingly, what we bring comes sooner than we expected. Ivan Royo has been working this term on the 1D version of DENIS (denis-fiber) and we already have a first version to start testing. It is a fairly advanced version of what will be the final one (still without checkpoints), but at this point it is very useful to start testing to see that everything is going well and to polish the last details.

Thanks to a grant from the Ministry, Iván is studying how cellular differences (interpatient variations) affect the propagation of the electrical impulse in the heart, and for this we need to scale up. If the tests go well, we will start running simulations within this new project. For now, they are all functional tests. We will start with manageable simulation sizes and gradually increase the number based on how the server responds and our post-processing capacity.

The optimization of the models is still pending as well, I hope we can resume it soon.

Best regards,
Jesús.

================================================================================

Estimados voluntarios:
¡Estamos de vuelta! La espera ha sido más larga de lo que habríamos querido, pero sorprendentemente, lo que traemos viene antes de lo que esperábamos. Ivan Royo ha estado este curso trabajando en la versión 1D de DENIS (denis-fiber) y ya tenemos una primera versión para empezar a hacer pruebas. Es una versión bastante avanzada de lo que será la final (aún sin chekpoints), pero en este punto nos viene muy bien poder empezar a hacer pruebas para ver que todo marcha bien e ir puliendo los últimos detalles.

Gracias a una beca del Ministerio, Iván está estudiando cómo afectan las diferencias celulares (variaciones interpaciente) en la propagación del impulso eléctrico en el corazón, y para ello necesitamos subir de escala. Si las pruebas van bien, comenzaremos a lanzar simulaciones dentro de este nuevo proyecto. De momento son todo pruebas de funcionamiento. Vamos a empezar con tamaños de simulaciones manejables e ir aumentando el número para cómo va respondiendo el servidor y nuestras capacidad de postprocesado.

La parte de la optimización de los modelos está aún pendiente también, espero que podamos retomarla en breve.

Un saludo,
Jesús.

View article · Wed, 26 Mar 2025 09:09:41 +0000

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View article · Mon, 24 Mar 2025 21:51:21 +0000

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View article · Mon, 17 Mar 2025 17:45:13 +0000

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[YAFU] Aliquot sequence 3264096, 3251448, 3192612, 3255870 have terminated!!!

Aliquot sequence 3264096, 3251448, 3192612, 3255870 have terminated!!!

View article · Sun, 16 Mar 2025 12:53:22 +0000

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[Einstein@home] Update on “Einstein@Home: Pulsar Seekers”

Dear Einstein@Home volunteers,

You may remember that we launched a Zooniverse project called “Einstein@Home: Pulsar Seekers” in October 2023. Now we have the first promising results.

Zooniverse volunteers have made millions of classifications for more than 240,000 candidates found in the Arecibo telescope's PALFA pulsar survey. More than 4400 candidates have been classified as promising after review by our scientists.

read more

View article · Fri, 14 Mar 2025 16:08:20 +0000

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[YAFU] Aliquot sequence 3197960 and 3270576 have terminated!!!

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View article · Thu, 13 Mar 2025 17:05:22 +0000

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[LHC@home] Maintenance downtime

Our BOINC services will be unavailable for a while this morning between 8 and 9AM CET for a database upgrade.

View article · Tue, 11 Mar 2025 06:16:13 +0000

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View article · Sat, 8 Mar 2025 20:27:35 +0000

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View article · Thu, 6 Mar 2025 20:30:08 +0000

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[Rosetta@home] Rosetta@home Update

First, we’d like to thank all our contributors who have supported and continue to contribute to our scientific projects through Rosetta@home. We want to update you on the status of Rosetta@home projects and our future plans.

With the advancement of AI models like AlphaFold and RosettaFold for protein structure predictions, Rosetta@home has been less used for this purpose. However, researchers are now utilizing Rosetta@home for small molecule and peptide designs, where even the current state-of-the-art AI models struggle due to limitations in generalizability to novel small molecules and non-canonical peptides.

Recently, we have developed a virtual screening protocol in Rosetta, named RosettaVS, for small molecule drug discovery. This work has been published in Nature Communications (https://doi.org/10.1038/s41467-024-52061-7), demonstrating that RosettaVS is one of the best physics-based virtual screening protocols. Combined with deep learning techniques, it can effectively screen multi-billion compound libraries and discover novel compounds for pharmaceutical targets.

While deep learning models like AlphaFold and RosettaFold can predict canonical peptide structures, they cannot handle peptides with non-canonical amino acids or mixed chirality. The physics-based force field in Rosetta has specialized terms to simulate these amino acids. Rosetta will be used to sample hundreds of thousands of different conformations of the designed peptide to validate the structure.

Looking ahead, Rosetta@home will be an invaluable platform for large-scale virtual screening and peptide simulations for drug discovery. We plan to launch more virtual screening jobs and peptide simulations on Rosetta@home in the near future.

Thank you!

View article · Tue, 4 Mar 2025 04:50:22 +0000

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[YAFU] Aliquot sequence 3075240 has terminated!!!

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View article · Thu, 27 Feb 2025 20:30:29 +0000

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