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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
I'm sure someone has posted about this b4 but how do I return more results other than using more computers? such as is there a way to change the amout of task you are doing at once?
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
You got it right, use more or better computers
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
.....you cannot alter tasks
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
You got it right, use more or better computers ![]() Better computers? I was looking how points are calucated and it looks like have a better computer does not nessary give you much of an advantage? Disagree? " How are points calculated? Points are calculated in a two-step process which attempts to give a consistent number of points for similar amounts of research computation. First, the computational power/speed of the computer is determined by periodically running a benchmark calculation. Then, based on the central processing unit (CPU) time spent computing the research result for a work unit, the benchmark result is used to convert the time spent on a work unit into points. This adjusts the point value so that a slow computer or a fast computer would produce about the same number of points for calculating the research result for the same work unit. This value is the number of point credits "claimed" by the client. More information about that formula is available here. " |
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
You asked how to return more results, you did not ask about points. My answer was to give more results, faster computer.....however, if you are returning twice as many results than you were before then you are likely to have twice as many points.......on average.
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
The original question was "how do I return more results"; nothing about points or runtime.
To return more results you need to process them quicker, so that you can return more per day. To do that you need either:
Work units (WUs) from different projects are not necessarily all the same "size" in terms of the amount of work needed to do to complete them. If you look at the statistics pages you can see that at the moment average run times per result are: MCM: 0:000:04:51:14 CEP2: 0:000:07:07:38 FAAH: 0:000:04:58:39 so you should probably be running MCM. Of course, these are averages across all the computers that are processing them, and architectural differences between project code and computer hardware means that what you see on your own machine(s) may vary. Track it for a week and see. You could also make sure that you are using all the threads that your computer has available and that you're not limiting the work in any way. Check your BOINC settings. Of course, you may find that you need to limit things to keep your computer's temperature down to a reasonable level, but I've never had to do that with any of mine so far. Opinion seems to be that using TThrottle (I think I spelled that correctly, check elsewhere in the forum) is better than using BOINC limits. To try answer your question about a better computer not giving you an advantage, I think you slightly misunderstand. What the highlighted text is saying is that points are allocated in such a way that a WU will give the same number of points whether it runs on a slow machine or a fast one. Here's a result from two very different machines: Result Name App Version Number Status Sent Time Time Due / Return Time CPU Time / Elapsed Time (hours) Claimed/ Granted BOINC Credit MCM1_ 0001212_ 8545_ 1-- 728 Valid 05/01/14 22:17:28 06/01/14 22:37:31 16.91 134.8 / 122.3 MCM1_ 0001212_ 8545_ 0-- 728 Valid 05/01/14 22:17:14 06/01/14 11:40:59 5.40 109.8 / 122.3 You'll see that second machine processed the WU in a third the time of the first one, but the points claims were similar and the points granted were simply the mean of the two claims. Of course, in the time that first machine had processed the WU, the second one would have done that one and two more. So it would have earned three times the number of points and returned three times the number of results for the same runtime (assuming they both had the same number of threads). Hope that helps. |
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branjo
Master Cruncher Slovakia Joined: Jun 29, 2012 Post Count: 1892 Status: Offline Project Badges: ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() ![]() |
You got it right, use more or better computers ![]() Better computers? I was looking how points are calucated and it looks like have a better computer does not nessary give you much of an advantage? Disagree? " How are points calculated? Points are calculated in a two-step process which attempts to give a consistent number of points for similar amounts of research computation. First, the computational power/speed of the computer is determined by periodically running a benchmark calculation. Then, based on the central processing unit (CPU) time spent computing the research result for a work unit, the benchmark result is used to convert the time spent on a work unit into points. This adjusts the point value so that a slow computer or a fast computer would produce about the same number of points for calculating the research result for the same work unit. This value is the number of point credits "claimed" by the client. More information about that formula is available here. " The bolded part is 100% true. But there is one small "but": the stronger/faster computer will return, let say, 10 WU's during the time the weaker/slower one will return 1. So, the stronger/faster computer will earn 10x more points in the given time slot ![]() Cheers ![]() ![]() Crunching@Home since January 13 2000. Shrubbing@Home since January 5 2006 ![]() [Edit 1 times, last edit by branjo at Jan 7, 2014 6:44:58 PM] |
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Former Member
Cruncher Joined: May 22, 2018 Post Count: 0 Status: Offline |
ah, now it makes sense. Thankyou for the info!
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