Markus Amsler a écrit :
Eric Pouech wrote:
Markus Amsler a écrit :
Eric Pouech wrote:
Markus Amsler a écrit :
I've played around with dbghelp performance. My test case was breaking at an unknown symbol (break gaga) while WoW was loaded in the debugger (wine winedbg WoW.exe). The time was hand stopped, memory usage measured with ps -AF and looked at the RSS column.
Test Time(s) Memory Usage(MB) current git 4.5 54 pool_heap.patch 4.5 63 process_heap.patch 4.5 126 insert_first.patch 4.5 54 current git, r300 115 146 pool_heap.patch, r300 17 119 process_heap.patch, r300 17 260 insert_first.patch, r300 27 167
insert_first is the patch from Eric Pouech. r300 means with the debug version of Mesas r300_dri.so, which has a total compilation unit size of around 9.2M (compared to the second biggest Wines user32 with 1.1M).
Hi Markus, does the slightly modified version of pool_heap improve your performances (it shouldn't modify the perf for large files(or just a bit), but should reduce memory consumption for small pools (from 1 to 2M depending on your configuration)
A+
No, performance is exactly the same as pool_heap :( .
even for memory consumption ???
I analyzed why your original insert_first version was slower and memory hungrier then pool_heap. It turned out pool_realloc is the problem, not pool_alloc. First there's a memory leak, if the memory is moved the old one is not freed. Second pool_realloc is O(n) that's the reason for the speed hits. Directly using heap functions for reallocs solves both problems (but looks to hackish to get commited, perhaps you have a better idea).
we could try not to realloc the array of arrays but rather use a tree of arrays which should solve most of the issues, but that would make the code complicated another way is to double the size of the bucket each time we need to increase size (instead of adding one bucket)
Here the results for pool_realloc on top of insert_first pool_realloc 4.5s 54M pool_realloc,r300 17s 104M The next problem is vector_iter_[up|down], because vector_position is O(n). Explicitly storing the current iter position speeds r300 up to 8s (from original 115s)! But I'm not sure how to implement it cleanly. Directly use for() instead of vector_iter_*(), use an iterator, ...
likely use an interator which keeps track of current position (as we do for the hash tables) A+