Rather than trying to nail down the remaining regressions, I think I am just going to give the data I've collected, which illustrates a problem, namely that in a very short space there can be massive improvements, immediately followed by massive regressions. This essentially violates the git bisect working assumption that there is one bad commit and you are trying to find it.
Here is a list of commits I have hit during various commits and the times I got for those commits. There was also another commit I hit where the time improved by a factor of 2, but all subsequent attempts to build any commits of Julia failed and so I had to clone the repository again. Because of this, I threw that data point away as likely corrupt. 41fb1ba good 15s 79a0d7b good 5ea20fc good 275c7e8 good bea07fc good c5704ed good 0318444 good 6396218 bad1 3b7f18a bad1 63daf4f bad1 1bfabbb bad1 179a439 bad1 0b6cab6 bad1 d8ec4a7 bad1 064b03c bad1 53b02a6 bad1 ca6f253 bad1 42s 8f4238a bad2 59s f67203c bad2 53s af81431 bad2 58s 6382116 bad3 73s 24276a5 bad3 74s 79b08ca bad3 73s 93cb2ae bad3 71s 5baedf4 bad3 72s 70a3120 ?? 48s 8af0134 bad4 82s def50a0 bad4 78s 039f57b bad4 78s 597dc7b bad4 78s adc1ed8 bad4 78s fc469b6 bad4 78s be9f208 bad5 87s master bad5 90s In summary, the commits that I know are serious regressions for sure are: 6396218 8f4238a 6382116 8af0134 There's also a regression somewhere between fc469b6 and cf68f4d3 (the latter being master some time today) which I didn't bisect yet. At this point I'm not sure how useful this is. Bill.
