How much number crunching is necessary in some simulations?

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In summary, simulations of cosmological structure formation, galaxy formation, collisions of galaxies, and planetary systems are typically done on massively parallel systems of computers. The computers are connected together and each works on a small piece of the problem, with information being exchanged between them to create a larger simulation. The largest simulation, the Illustris Simulation, used 8,192 compute cores and took 19 million CPU hours, which equates to approximately 3 months of elapsed time running on 8192 computers.
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lpetrich
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I've seen simulations like these, simulations that were done in *very* gory detail, and simulations that apparently required a large number of CPU cycles and a large amount of memory space.
  • Cosmological structure formation and galaxy formation
  • Collisions of galaxies
  • Formation of planetary systems and collisions of planets
  • Inspiral of black holes or neutron stars
Does anyone have any more details on any of that? Like what computers that they used and how long that they needed for a run.
 
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Almost all of these simulations are done on massively parallel systems of computers. Each computer is similar to the one in your laptop, but there are many thousands of them connected together. The problem is then split into pieces so that each computer is just solving a piece of the problem. In the cosmological structure simulations, each computer is working on a small volume of space, and the computers send information back and forth about what happens on the boundaries so the simulation can be stitched together into the whole volume. The Illustris Simulation, for example, states that "The largest was run on 8,192 compute cores, and took 19 million CPU hours". If you divide this out, it must have taken about 3 months of elapsed time running on 8192 computers.
 

1. How do you determine the amount of number crunching necessary for a simulation?

The amount of number crunching necessary for a simulation depends on several factors, including the complexity of the system being simulated, the desired level of accuracy, and the available computational resources. It is typically determined through trial and error and may require adjustments as the simulation progresses.

2. Why is number crunching necessary in simulations?

Number crunching, or performing calculations on large amounts of data, is necessary in simulations because it allows for the accurate representation of complex systems and their interactions. Without proper number crunching, simulations may not produce reliable or meaningful results.

3. How does the amount of number crunching affect the accuracy of a simulation?

The amount of number crunching can greatly affect the accuracy of a simulation. Generally, the more calculations that are performed, the more accurate the simulation will be. However, there is a point of diminishing returns, where the additional calculations may not significantly improve the accuracy of the simulation.

4. What are some ways to reduce the amount of number crunching in a simulation?

There are several techniques that can be used to reduce the amount of number crunching in a simulation. These include simplifying the model or system being simulated, using more efficient algorithms, and optimizing the code. Additionally, utilizing parallel processing or running the simulation on a high-performance computing system can also speed up the number crunching process.

5. How can one ensure that the amount of number crunching in a simulation is appropriate?

One way to ensure that the amount of number crunching in a simulation is appropriate is to benchmark the simulation against known results or experimental data. This can help identify any potential errors or inaccuracies in the simulation and allow for adjustments to be made. Additionally, seeking feedback from other experts in the field can also help determine if the amount of number crunching is appropriate for the specific simulation being performed.

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