DDR3 Memory Overclocking Charts Based On 200.000+ Results

Memory by massman @ 2010-08-22

Everyone knows that the HWBOT database is filled with benchmark results, overclocking data and so much more. One of the perks of having a database like this is not only to amuse (and annoy) overclockers globally, but mainly to analyze the results afterwards and have a better understanding of how the overclocking game really works. Processor and video card charts are scattered around the website, but memory overclocking charts is something we have not touched before.

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Generating the charts

Generating the charts

Now that we have gathered all necessary data on formulas, relative scaling and data range, we can start building the charts. I will not elaborate too much on this topic as it’s pretty straight-forward what we did, but I will elaborate a bit more on the final stage of the creation of the charts.

After all data had been extracted from the database and the memory rating had been calculated, we had a set of absolute performance indications. The issue is that these absolute values have no meaning other than ‘X is higher than Y’. To standardize the chart, we had to scale the absolute results to a scale of 0 to 100, with 100 being the best and 0 being the worst.

Madshrimps (c)

Madshrimps (c)


Initially, we’d planned to make all performance relative to the best performing memory kit. In this particular case, the GTX2 memory kit would receive a rating of 100 and all other kits would receive a rating relative to this 100. Now, of course this is not the right way to standardize. Who are we to say that the GTX2 should receive a rating of 100/100? So, instead of using the absolute performance rating of the best scoring memory kit, we used the absolute performance rating of ideal memory kit, within reason. So, all memory kits received a rating relative to the performance index of a hypothetical memory kit that would average DDR3-2000 CL6-6.

We appreciate all feedback on this article and the methodology. If you have questions, or want to discuss our unique approach, you can just drop a post on our forums and we’ll be happy to listen to it.

Thank you for reading!




This article was first published at Hwbot here and has been reprinted with permission.

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Comment from thorgal @ 2010/08/23
This is a very nice effort, however, as you state yourself, Everest might not be the best tool to make your equations with.

We found out ourselves that the real world differences between fast/slow memory is only a couple of % (1-3%), however, everest makes the differences much bigger. There's also the question whether a better everest bandwidth score automatically means a better real world performance : it often does, but not always.

My biggest gripe is with the charts though, and is not "your fault" in any way : there are plenty of types of OCZ blades for example, some good, some bad, with different chips on them and different specs. Still : they're all thrown into one category "OCZ blade". Contrary to that : Corsair GTX is always elpida, so naturally sticks out (but should devided into several types itself). What this leads to is over generalization : "If I buy Corsair GTX I'll be ok", whereas a blade series @ eg 2ghz cas 7 is still better than a 1866 cas 8 corsair.

All in all, forgive me PJ, I find the graphs presented this way much too general to provide any real use.

 

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