Recent content by graysky

Gotta disagree with that... there are distributions of data in many MANY populations. No sensors is perfect. My point is basing an entire run of say 1400 samples on 1 sample or a 0.0007 % of the samples doesn't make sense to me. Also, I do believe that I sampled out enough based on the plots...

Sorry, I still don't understand your reasoning for using max rather than mean or median for this particular question. Most of the math I do with large sets excludes outliers but your strategy is the polar opposite: you are looking for trends based on them :/

I sort of follow your thinking, but have you looked at the distribution of temps per run? By selecting the max, you are intentionally increasing the amount of bounce in the data by picking the highest flyer in the distribution. For example, there are roughly 1400 data points in the prime95...

Sorry dude, it's been years since calculus. My simplistic take on it is: how much has the mean temp for a stress event decreased over time. Set a zero point, test at known intervals, report the mean result and compare back to the zero point. Your rate of change calculation and what it tells...

If you're only extracting the max value from each run I don't believe that is a sound strategy. Select either the median or mean and be sure to exclude the first 400 data points for each run. I don't understand your code at all (not a database guy).

Guess I'm not sure what you're plotting. The trend is pretty clear to me: represented by the dashed green line on my plot.

I will check it again in a few weeks.

Still not sure what you're plotting.. you want the ave diff between the endpoints in my graphs above? time = time in hours since seating burnP6 = average temp accounting for ambient from burnP6 stress mprime-440k = average temp accounting for ambient for mprime stress time burnP6...

Low 60s in F scale... there is a col that converts it to C since the coretemp values are in C.

You might need to unpivot the data with respect to core0-core3 which is how I worked with it in the plots. No idea why openoffice can't read a csv file... did you uncompress it first? It is compressed by gzip.

Not a problem, perhaps I didn't make it clear... I'm not a very good writer. Not exactly sure how to plot that... I have made both the raw data and the expanded data tables available. Perhaps you can plots it and post the result.

I tested MX4 multiple times and was disappointed with the results. Always hotter than AS5 without curing. Maybe I got a bad tube? Others have reported better.

No, you don't have that quite right, see here: and, here: So collectively, it was 42 min stressing, 78 idle, then repeat for 3 days, then once every 4 hours for a few days, then once every 6 hours for a few days. Many power cycles in other words. Look at the data table, fan RPM speed was...

OK, ran out to ~200 hours and as expected, no change in the conclusion. The original post was updated with these results.

Purpose According to the manufacture of AS5, there can be up to 200 hours of break in time required for temps to stabilize. This claim has been tested the results are shared in this thread. Materials, software, and experiment A delidded i7-3770k (over-clocked to 44x100 with fixed vcore) was...