Since the kernel library no longer depends on the system file, move it
to the common library instead in accordance to the diagram in
doc/design/libraries.md.
2022917223 Add secp256k1_selftest call (Pieter Wuille)
3bfca788b0 Remove explicit enabling of default modules (Pieter Wuille)
4462cb0498 Adapt to libsecp256k1 API changes (Pieter Wuille)
9d47e7b71b Squashed 'src/secp256k1/' changes from 44c2452fd3..21ffe4b22a (Pieter Wuille)
Pull request description:
Now that libsecp256k1 has a release (https://lists.linuxfoundation.org/pipermail/bitcoin-dev/2022-December/021271.html), update the subtree to match it.
The changes themselves are not very impactful for Bitcoin Core, but include:
* It's no longer needed to specify whether contexts are for signing or verification or both (all contexts support everything), so make use of that in this PR.
* Verification operations can use the static context now, removing the need for some infrastructure in pubkey.cpp to make sure a context exists.
* Most modules are now enabled by default, so we can drop explicit enabling for them.
* CI improvements (in particular, MSVC and more recent MacOS)
* Introduction of an internal int128 type, which has no effect for GCC/Clang builds, but enables 128-bit multiplication in MSVC, giving a ~20% speedup there (but still slower than GCC/Clang).
* Release process changes (process documentation, changelog, ...).
ACKs for top commit:
Sjors:
ACK 2022917223, but 4462cb0498 could use more eyes on it.
achow101:
ACK 2022917223
jonasnick:
utACK 2022917223
Tree-SHA512: 8a9fe28852abe74abd6f96fef16a94d5a427b1d99bff4caab1699014d24698aab9b966a5364a46ed1001c07a7c1d825154ed4e6557c7decce952b77330a8616b
* Use SECP256K1_CONTEXT_NONE when creating signing context, as
SECP256K1_CONTEXT_SIGN is deprecated and unnecessary.
* Use secp256k1_static_context where applicable.
Includes a memory leak in the checkqueue unit test (but not in
the actual code). WE really need to switch our checkqueue to use
std::unique_pointer rather than bare pointers. But this would be
invasive enough that I want to do it in a followup PR.
Also pretty-much disable the validation_flush_cache unit test.
This is a stupid and irritating test which tries to unit-test
exact memory usage of std containers. It already has at least
one "remove wrong assumptions" update upstream and after many
tries I was unable to change all the magic numbers in a way
that'd consistently pass CI for Elements.
Also adds a couple ubsan suppressions about perfectly-legitimate
conversions of integer types.
This replaces the current benchmarking framework with nanobench [1], an
MIT licensed single-header benchmarking library, of which I am the
autor. This has in my opinion several advantages, especially on Linux:
* fast: Running all benchmarks takes ~6 seconds instead of 4m13s on
an Intel i7-8700 CPU @ 3.20GHz.
* accurate: I ran e.g. the benchmark for SipHash_32b 10 times and
calculate standard deviation / mean = coefficient of variation:
* 0.57% CV for old benchmarking framework
* 0.20% CV for nanobench
So the benchmark results with nanobench seem to vary less than with
the old framework.
* It automatically determines runtime based on clock precision, no need
to specify number of evaluations.
* measure instructions, cycles, branches, instructions per cycle,
branch misses (only Linux, when performance counters are available)
* output in markdown table format.
* Warn about unstable environment (frequency scaling, turbo, ...)
* For better profiling, it is possible to set the environment variable
NANOBENCH_ENDLESS to force endless running of a particular benchmark
without the need to recompile. This makes it to e.g. run "perf top"
and look at hotspots.
Here is an example copy & pasted from the terminal output:
| ns/byte | byte/s | err% | ins/byte | cyc/byte | IPC | bra/byte | miss% | total | benchmark
|--------------------:|--------------------:|--------:|----------------:|----------------:|-------:|---------------:|--------:|----------:|:----------
| 2.52 | 396,529,415.94 | 0.6% | 25.42 | 8.02 | 3.169 | 0.06 | 0.0% | 0.03 | `bench/crypto_hash.cpp RIPEMD160`
| 1.87 | 535,161,444.83 | 0.3% | 21.36 | 5.95 | 3.589 | 0.06 | 0.0% | 0.02 | `bench/crypto_hash.cpp SHA1`
| 3.22 | 310,344,174.79 | 1.1% | 36.80 | 10.22 | 3.601 | 0.09 | 0.0% | 0.04 | `bench/crypto_hash.cpp SHA256`
| 2.01 | 496,375,796.23 | 0.0% | 18.72 | 6.43 | 2.911 | 0.01 | 1.0% | 0.00 | `bench/crypto_hash.cpp SHA256D64_1024`
| 7.23 | 138,263,519.35 | 0.1% | 82.66 | 23.11 | 3.577 | 1.63 | 0.1% | 0.00 | `bench/crypto_hash.cpp SHA256_32b`
| 3.04 | 328,780,166.40 | 0.3% | 35.82 | 9.69 | 3.696 | 0.03 | 0.0% | 0.03 | `bench/crypto_hash.cpp SHA512`
[1] https://github.com/martinus/nanobench
* Adds support for asymptotes
This adds support to calculate asymptotic complexity of a benchmark.
This is similar to #17375, but currently only one asymptote is
supported, and I have added support in the benchmark `ComplexMemPool`
as an example.
Usage is e.g. like this:
```
./bench_bitcoin -filter=ComplexMemPool -asymptote=25,50,100,200,400,600,800
```
This runs the benchmark `ComplexMemPool` several times but with
different complexityN settings. The benchmark can extract that number
and use it accordingly. Here, it's used for `childTxs`. The output is
this:
| complexityN | ns/op | op/s | err% | ins/op | cyc/op | IPC | total | benchmark
|------------:|--------------------:|--------------------:|--------:|----------------:|----------------:|-------:|----------:|:----------
| 25 | 1,064,241.00 | 939.64 | 1.4% | 3,960,279.00 | 2,829,708.00 | 1.400 | 0.01 | `ComplexMemPool`
| 50 | 1,579,530.00 | 633.10 | 1.0% | 6,231,810.00 | 4,412,674.00 | 1.412 | 0.02 | `ComplexMemPool`
| 100 | 4,022,774.00 | 248.58 | 0.6% | 16,544,406.00 | 11,889,535.00 | 1.392 | 0.04 | `ComplexMemPool`
| 200 | 15,390,986.00 | 64.97 | 0.2% | 63,904,254.00 | 47,731,705.00 | 1.339 | 0.17 | `ComplexMemPool`
| 400 | 69,394,711.00 | 14.41 | 0.1% | 272,602,461.00 | 219,014,691.00 | 1.245 | 0.76 | `ComplexMemPool`
| 600 | 168,977,165.00 | 5.92 | 0.1% | 639,108,082.00 | 535,316,887.00 | 1.194 | 1.86 | `ComplexMemPool`
| 800 | 310,109,077.00 | 3.22 | 0.1% |1,149,134,246.00 | 984,620,812.00 | 1.167 | 3.41 | `ComplexMemPool`
| coefficient | err% | complexity
|--------------:|-------:|------------
| 4.78486e-07 | 4.5% | O(n^2)
| 6.38557e-10 | 21.7% | O(n^3)
| 3.42338e-05 | 38.0% | O(n log n)
| 0.000313914 | 46.9% | O(n)
| 0.0129823 | 114.4% | O(log n)
| 0.0815055 | 133.8% | O(1)
The best fitting curve is O(n^2), so the algorithm seems to scale
quadratic with `childTxs` in the range 25 to 800.
* inline performance critical code
* Average runtime is specified and used to calculate iterations.
* Console: show median of multiple runs
* plot: show box plot
* filter benchmarks
* specify scaling factor
* ignore src/test and src/bench in command line check script
* number of iterations instead of time
* Replaced runtime in BENCHMARK makro number of iterations.
* Added -? to bench_bitcoin
* Benchmark plotly.js URL, width, height can be customized
* Fixed incorrect precision warning
