Commit graph

9 commits

Author SHA1 Message Date
Justine Tunney
135d538b1d
Make ctl::set use 30% less memory than libcxx 2024-07-04 02:46:27 -07:00
Justine Tunney
1bf2d8e308
Further improve mmap() locking story
The way to use double linked lists, is to remove all the things you want
to work on, insert them into a new list on the stack. Then once you have
all the work items, you release the lock, do your work, and then lock it
again, to add the shelled out items back to a global freelist.
2024-06-29 17:12:43 -07:00
Justine Tunney
98e684622b
Add iostream to CTL 2024-06-29 15:45:09 -07:00
Justine Tunney
021c53ba32
Add more CTL content 2024-06-28 19:09:54 -07:00
Justine Tunney
38921dc46b
Introduce more CTL content
This change introduces accumulate, addressof, advance, all_of, distance,
array, enable_if, allocator_traits, back_inserter, bad_alloc, is_signed,
any_of, copy, exception, fill, fill_n, is_same, is_same_v, out_of_range,
lexicographical_compare, is_integral, uninitialized_fill_n, is_unsigned,
numeric_limits, uninitialized_fill, iterator_traits, move_backward, min,
max, iterator_tag, move_iterator, reverse_iterator, uninitialized_move_n

This change experiments with rewriting the ctl::vector class to make the
CTL design more similar to the STL. So far it has not slowed things down
to have 42 #include lines rather than 2, since it's still almost nothing
compared to LLVM's code. In fact the closer we can flirt with being just
like libcxx, the better chance we might have of discovering exactly what
makes it so slow to compile. It would be an enormous discovery if we can
find one simple trick to solving the issue there instead.

This also fixes a bug in `ctl::string(const string &s)` when `s` is big.
2024-06-27 22:42:32 -07:00
Steven Dee (Jōshin)
054da021d0
ctl::string benchmarking code (#1200) 2024-06-26 21:30:05 -04:00
Justine Tunney
c4c812c154
Introduce ctl::set and ctl::map
We now have a C++ red-black tree implementation that implements standard
template library compatible APIs while compiling 10x faster than libcxx.
It's not as beautiful as the red-black tree implementation in Plinko but
this will get the job done and the test proves it upholds all invariants

This change also restores CheckForMemoryLeaks() support and fixes a real
actual bug I discovered with Doug Lea's dlmalloc_inspect_all() function.
2024-06-23 22:27:11 -07:00
Justine Tunney
3609f65de3
Make malloc() go 200x faster
If pthread_create() is linked into the binary, then the cosmo runtime
will create an independent dlmalloc arena for each core. Whenever the
malloc() function is used it will index `g_heaps[sched_getcpu() / 2]`
to find the arena with the greatest hyperthread / numa locality. This
may be configured via an environment variable. For example if you say
`export COSMOPOLITAN_HEAP_COUNT=1` then you can restore the old ways.
Your process may be configured to have anywhere between 1 - 128 heaps

We need this revision because it makes multithreaded C++ applications
faster. For example, an HTTP server I'm working on that makes extreme
use of the STL went from 16k to 2000k requests per second, after this
change was made. To understand why, try out the malloc_test benchmark
which calls malloc() + realloc() in a loop across many threads, which
sees a a 250x improvement in process clock time and 200x on wall time

The tradeoff is this adds ~25ns of latency to individual malloc calls
compared to MODE=tiny, once the cosmo runtime has transitioned into a
fully multi-threaded state. If you don't need malloc() to be scalable
then cosmo provides many options for you. For starters the heap count
variable above can be set to put the process back in single heap mode
plus you can go even faster still, if you include tinymalloc.inc like
many of the programs in tool/build/.. are already doing since that'll
shave tens of kb off your binary footprint too. Theres also MODE=tiny
which is configured to use just 1 plain old dlmalloc arena by default

Another tradeoff is we need more memory now (except in MODE=tiny), to
track the provenance of memory allocation. This is so allocations can
be freely shared across threads, and because OSes can reschedule code
to different CPUs at any time.
2024-06-05 02:02:14 -07:00
Justine Tunney
4937843f70
Introduce Cosmopolitan Templates Library (CTL) 2024-06-03 09:21:59 -07:00