What is Asteroids@home?

Asteroids are the most numerous objects in the solar system. So far, hundreds of thousands of asteroids are known, with hundres of new discoveries every day. Altough the total number of known asteroids is large, very little is known about the physical properties of individual objects. For a significant part of the population, only the size of the bodies is known. Other physical parameters (the shape, the rotation period, direction of the rotation axis,...) are known only for hundreds of objects.
Because asteroids have in general irregular shapes and they rotate, the amount of sunlight they scatter towards the observer varies with time. This variation of brightness with time is called a lightcurve. The shape of a lightcurve depends on the shape of asteroid and also on the viewing and illumination geometry. If a sufficient number of lightcurves observed under various geometries is collected, a unique physical model of the asteroid can be reconstucted by the lightcurve inversion method.
The project Asteroids@home was started with the aim to significanly enlarge our knowledge of physical properties of asteroids. The BOINC application uses photometric measurements of asteroids observed by professional big all-sky surveys as well as 'backyard' astronomers. The data is processed using the lightcurve inversion method and a 3D shape model of an asteroid together with the rotation period and the direction of the spin axis are derived.
Because the photometric data from all-sky surveys are typically sparse in time, the rotation period is not directly 'visible' in the data and the huge parameter space has to be scanned to find the best solution. In such cases, the lightcurve inversion is very time-consuming and the distributed computation is the only way how to efficiently deal with photometry of hundres of thousands of asteroids. Moreover, in order to reveal biases in the method and reconstruct the real distribution of physical parameters in the asteroid population, it is necessary to process large data sets of 'synthetic' populations.
Asteroids@home is based at Astronomical Institute, Charles University in Prague.
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News
New Raspbian OS aarch64 (armv8) application is here
Hi everyone,
A new, 64bit, version of the Period search application for the Raspberry Pi was released today supporting aarch64 (armv8) architecture!
It will be interesting to get some feedback from you about how it performs as there still could be some issues to be solved.
Happy crunching and don't forget to use active cooling on your boards as the app can be very aggressive to the cores on times.
Cheers!
Georgi
New FMA application released
We are happy to present you another set of applications that will utilize those CPUs, which possess the FMA instruction set!
It was built to support both Linux and Windows OS with 64bit architecture.
What must be taken into account with these applications is that depending on the CPU architecture, generation, model, version, speed and number of utilized cores, in some cases the FMA applications may run slower than the corresponding AVX ones because of how those instructions are handled on different architectures, details that I'll not going further here as there is a lot of information on Internet. Also, there could be another case using even the same FMA application. For instance, there could be a situation where on the same particular system, having your preferences restrict the use of just a single core of, let's say, an Intel(R) Xeon(R) W Processor Xeon W-2195 of the Skylake-W Architecture, that single core will run much faster, close to processors' Turbo frequency of 4.3GHz, than if your configuration allows the client to utilize let's say 12 or more cores. In the second case those cores will run close to the processors' base frequency of 2.3GHz, depending on their actual number, which will result drastically in lowering of the application performance. Take a look at this article where under the "Per Core Turbo Data" chapter you will find explanation about how the Turbo ratio limits works.
Still, while the Boinc server is capable of finding the best performed application for every particular system, taking into account multiple factors, and after a while it will start sending the right one for every particular system. Which means that even if your CPU is equipped with the FMA engine it still might receive an AVX tasks and there is nothing to be concerned.
So happy crunching and thank you for your support!
Radim Vančo (FoxKyong)
New CUDA application released
We are happy to present you our latest CUDA application v102.16!
It was built on top of CUDA's v11.8 SDK and thus it will be able to utilize the vast majority of cards with Compute Capabilities (CC) between 5.0 till 8.9 adding support for the Ampere & Ada Lovelace micro architecture, and all the Tegra & Jetson modules.
Of course, it comes with its own requirements for the driver's versions, depending on your architecture, as those before it.
In order your client to be able to receive it your computer must have one of the following Nvidia driver versions installed:
- For Linux x86_64 and Linux AArch64 >= 450.80.02
- For Windows x86_64 >= 452.39
(https://docs.nvidia.com/cuda/cuda-toolkit-release-notes/index.html)
Here is the list of supported by the v102.16 application GPUs by their CC provided by Nvidia.
So happy crunching and thank you for your support!
Radim Vančo (FoxKyong)
Server is up and running again
Hi everyone,
Server is finally up and running again after more than a year of being down. Everything is migrated to a new server and we hope it will run smoothly for a long time. There are still some minor issues but nothing crutial and all minor tweeks will be done during the time.
I would also like to thank to Georgi Vidinski who has helped with solving some problems.
Radim Vančo (FoxKyong)
Server status update
Server is now ready to continue operating and there will be more workunits to send. But please be aware that it is still a temporary solution because new server won't by any sooner then on May or June and there still might happen some problems.
Radim Vančo (FoxKyong)

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