From: vmakarov@... Date: 2016-03-04T17:35:06+00:00 Subject: [ruby-core:74144] [Ruby trunk Feature#12142] Hash tables with open addressing Issue #12142 has been updated by Vladimir Makarov. Yura Sokolov wrote: > Great! > Thanks. > Notes: > - num_entries should remain num_entries. It is easier for you to change naming than fix all rubygems. Thanks for pointing this out. > - do not change formatting of a code you do not change, it is awful to read and check that part of your patch. I'll restore it. It is probably because I work on other projects which uses a different formatting. > - speed improvement is not from open addressing but from array storage for elements. You can use chaining with "next_index" with same result. But perhaps open addressing is simpler to implement. Sorry, I doubt in this conclusion unless you prove it by benchmarks. Open addressing removes pointer making a smaller element which increases probability to be read from memory by reading the same cache line or/and probability to stay in a cache. In case of collisions, I believe checking other entry again improves data locality in comparison with going by pointers through disperse elements (may be allocated originally for different tables). On the other hand, you are right. I think the biggest improvement comes from putting elements into an array. Open addressing is not simpler to implement too. The code might be smaller. For example, I suspect CPython has a wrong implementation of hash tables and can be cycled in extremely rare cases. For open addressing, someone should implement a full cycle linear congruential generator. I use X_next = (5 * X_prev + 1) mod pow_of_2 since it satisfies the requirements of the Hull-Dobell theorem. CPython function lookdict violates the theorem requirement 0 <= X < 'the module' and consequently not a full cycle linear congruential generator. So implementing a correct open addressing is not easy. It is easy if you use prime numbers (that is what GCC hash tables uses) but dividing big values (hashes) by prime numbers is even slower (> 100 cycles) than access to main memory. By the way I tried using prime numbers too (in average the implementation was faster than the current tables but there were a few benchmarks where it was slower). > - if you stick with open-addressing, then it could be even faster, if you store hashsum in st_entry. I tried something analogous and it did not work. Storing hash with entries increases the table size as the array entries is bigger than the array elements. > - st_foreach is broken in case table were rebuilt. > Sorry, I did not catch what you meant. St_foreach works fine in the proposed implementation even if the table rebuilds. Moreover st_foreach in the proposed implementation can work forever adding and removing elements meanwhile the current implementation will result out of memory in such case. > Any way, it is a great attempt I wished to do by myself, but didn't give time for. I hope, you'll fix all issues and change will be accepted. I don't think the faster hash tables is that important for general Ruby speed. Simply I need to start with some simpler project on MRI. ---------------------------------------- Feature #12142: Hash tables with open addressing https://bugs.ruby-lang.org/issues/12142#change-57288 * Author: Vladimir Makarov * Status: Open * Priority: Normal * Assignee: ---------------------------------------- ~~~ Hello, the following patch contains a new implementation of hash tables (major files st.c and include/ruby/st.h). Modern processors have several levels of cache. Usually,the CPU reads one or a few lines of the cache from memory (or another level of cache). So CPU is much faster at reading data stored close to each other. The current implementation of Ruby hash tables does not fit well to modern processor cache organization, which requires better data locality for faster program speed. The new hash table implementation achieves a better data locality mainly by o switching to open addressing hash tables for access by keys. Removing hash collision lists lets us avoid *pointer chasing*, a common problem that produces bad data locality. I see a tendency to move from chaining hash tables to open addressing hash tables due to their better fit to modern CPU memory organizations. CPython recently made such switch (https://hg.python.org/cpython/file/ff1938d12240/Objects/dictobject.c). PHP did this a bit earlier https://nikic.github.io/2014/12/22/PHPs-new-hashtable-implementation.html. GCC has widely-used such hash tables (https://gcc.gnu.org/svn/gcc/trunk/libiberty/hashtab.c) internally for more than 15 years. o removing doubly linked lists and putting the elements into an array for accessing to elements by their inclusion order. That also removes pointer chaising on the doubly linked lists used for traversing elements by their inclusion order. A more detailed description of the proposed implementation can be found in the top comment of the file st.c. The new implementation was benchmarked on 21 MRI hash table benchmarks for two most widely used targets x86-64 (Intel 4.2GHz i7-4790K) and ARM (Exynos 5410 - 1.6GHz Cortex-A15): make benchmark-each ITEM=bm_hash OPTS='-r 3 -v' COMPARE_RUBY='' Here the results for x86-64: hash_aref_dsym 1.094 hash_aref_dsym_long 1.383 hash_aref_fix 1.048 hash_aref_flo 1.860 hash_aref_miss 1.107 hash_aref_str 1.107 hash_aref_sym 1.191 hash_aref_sym_long 1.113 hash_flatten 1.258 hash_ident_flo 1.627 hash_ident_num 1.045 hash_ident_obj 1.143 hash_ident_str 1.127 hash_ident_sym 1.152 hash_keys 2.714 hash_shift 2.209 hash_shift_u16 1.442 hash_shift_u24 1.413 hash_shift_u32 1.396 hash_to_proc 2.831 hash_values 2.701 The average performance improvement is more 50%. ARM results are analogous -- no any benchmark performance degradation and about the same average improvement. The patch can be seen as https://github.com/vnmakarov/ruby/compare/trunk...hash_tables_with_open_addressing.patch or in a less convenient way as pull request changes https://github.com/ruby/ruby/pull/1264/files This is my first patch for MRI and may be my proposal and implementation have pitfalls. But I am keen to learn and work on inclusion of this code into MRI. ~~~ -- https://bugs.ruby-lang.org/ Unsubscribe: