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Add Trevis CI support Add Travis CI support to GitHub repo. After every push to master, Travis will build the sources directly from GitHub repo according to .travis.yml and verify everything is ok. No functional change.
2015-10-05 02:09:03 -06:00
language: cpp
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
dist: bionic
Add Trevis CI support Add Travis CI support to GitHub repo. After every push to master, Travis will build the sources directly from GitHub repo according to .travis.yml and verify everything is ok. No functional change.
2015-10-05 02:09:03 -06:00
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
matrix:
include:
- os: linux
compiler: gcc
addons:
apt:
Update our continuous integration machinery (#1889) * Update our continuous integration machinery Ubuntu 16.04 can now be used with travis. Updating all the other stuff when there. Invoking the lld linker seems to save 5 minutes with clang on linux. No functional change. * fix
2018-12-23 10:17:44 -07:00
packages: ['g++-8', 'g++-8-multilib', 'g++-multilib', 'valgrind', 'expect', 'curl']
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
env:
Update our continuous integration machinery (#1889) * Update our continuous integration machinery Ubuntu 16.04 can now be used with travis. Updating all the other stuff when there. Invoking the lld linker seems to save 5 minutes with clang on linux. No functional change. * fix
2018-12-23 10:17:44 -07:00
- COMPILER=g++-8
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
- COMP=gcc
Add Trevis CI support Add Travis CI support to GitHub repo. After every push to master, Travis will build the sources directly from GitHub repo according to .travis.yml and verify everything is ok. No functional change.
2015-10-05 02:09:03 -06:00
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
- os: linux
compiler: clang
addons:
apt:
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
packages: ['clang-10', 'llvm-10-dev', 'g++-multilib', 'valgrind', 'expect', 'curl']
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
env:
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
- COMPILER=clang++-10
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
- COMP=clang
Travis CI: add gcc 4.8 for osx This setup was still missing. Suggested by Stéphane Nicolet. No functional change.
2015-10-07 12:33:37 -06:00
- os: osx
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
osx_image: xcode12
Travis CI: add gcc 4.8 for osx This setup was still missing. Suggested by Stéphane Nicolet. No functional change.
2015-10-07 12:33:37 -06:00
compiler: gcc
env:
Fix Travis Cl Broken after "32-bit/64-bit Makefile fix" commit. Ubuntu "Precise" 12.04.5 supports multilib only until g++ 4.6 that is not enough to compile Stockfish. So move to Ubuntu 14.04.4 LTS (Trusty Tahr) No functional change.
2016-04-09 00:58:14 -06:00
- COMPILER=g++
Travis CI: add gcc 4.8 for osx This setup was still missing. Suggested by Stéphane Nicolet. No functional change.
2015-10-07 12:33:37 -06:00
- COMP=gcc
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
- os: osx
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
osx_image: xcode12
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
compiler: clang
env:
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
- COMPILER=clang++
Travis CI: add clang and osx Extend builds to clang and osx platforms. And check bench numbers. No functional change.
2015-10-06 03:59:06 -06:00
- COMP=clang
Add Trevis CI support Add Travis CI support to GitHub repo. After every push to master, Travis will build the sources directly from GitHub repo according to .travis.yml and verify everything is ok. No functional change.
2015-10-05 02:09:03 -06:00
branches:
only:
- master
before_script:
- cd src
script:
This commit enables a mixed bench, to improve CI and allow for PGO (profile-build) of the NNUE part of the code. Joint work gvreuls / vondele * Download the default NNUE net in AppVeyor * Download net in travis CI `make net` * Adjust tests to cover more archs, speedup instrumented testing * Introduce 'mixed' bench as default, with further options: classical, NNUE, mixed. mixed (default) and NNUE require the default net to be present, which can be obtained with ``` make net ``` Further examples (first is equivalent to `./stockfish bench`): ``` ./stockfish bench 16 1 13 default depth mixed ./stockfish bench 16 1 13 default depth classical ./stockfish bench 16 1 13 default depth NNUE ``` The net is now downloaded automatically if needed for `profile-build` (usual `build` works fine without net present) PGO gives a nice speedup on fishtest: passed STC: LLR: 2.93 (-2.94,2.94) {-0.50,1.50} Total: 3360 W: 469 L: 343 D: 2548 Ptnml(0-2): 20, 246, 1030, 356, 28 https://tests.stockfishchess.org/tests/view/5f31b5499081672066537569 passed LTC: LLR: 2.97 (-2.94,2.94) {0.25,1.75} Total: 8824 W: 609 L: 502 D: 7713 Ptnml(0-2): 8, 430, 3438, 519, 17 https://tests.stockfishchess.org/tests/view/5f31c87b908167206653757c closes https://github.com/official-stockfish/Stockfish/pull/2931 fixes https://github.com/official-stockfish/Stockfish/issues/2907 requires fishtest updates before commit Bench: 4290577
2020-08-07 09:07:46 -06:00
# Download net
- make net
Speed up Trevis CI Avoid a couple of redundant rebuilds and compile with 2 threads since travis gives 2vCPUs. Also enable -O1 optimization for valgrind and sanitizers, it should be safe withouth false positives and it gives a very sensible speed up, especially with valgrind. The spee dup allow us to increase testing to depth 10, useful for thread sanitizer. No functional change.
2017-08-16 03:28:54 -06:00
# Obtain bench reference from git log
More robust bench extraction Allow travis.yml to recognize a variety of bench formats in commit messages, for instance: Bench: 5023593. (really). bench: 5023593 (it was 1234567) bench : 5023593 (blah blah) Bench:5023593 Bench: 5023593. 567 something (1234567) 563 No functional change.
2018-02-06 17:26:46 -07:00
- git log HEAD | grep "\b[Bb]ench[ :]\+[0-9]\{7\}" | head -n 1 | sed "s/[^0-9]*\([0-9]*\).*/\1/g" > git_sig
Trevis CI: use commit bench number as a reference No functional change.
2017-01-09 04:40:07 -07:00
- export benchref=$(cat git_sig)
New shell scripts for testing, used for travis CI (#957) Perform more complex verification and validation. - signature.sh : extract and optionally compare Bench/Signature/Node count. - perft.sh : verify perft counts for a number of positions. - instrumented.sh : run a few commands or uci sequences through valgrind/sanitizer instrumented binaries. - reprosearch.sh : verify reproducibility of search. These script can be used from directly from the command line in the src directory. Update travis script to use these shell scripts. No functional change.
2017-01-09 02:30:57 -07:00
- echo "Reference bench:" $benchref
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
# Compiler version string
- $COMPILER -v
Add further targets to travis testing general-32, general-64 and help closes https://github.com/official-stockfish/Stockfish/pull/3014 No functional change
2020-08-16 05:21:07 -06:00
# test help target
- make help
Speed up Trevis CI Avoid a couple of redundant rebuilds and compile with 2 threads since travis gives 2vCPUs. Also enable -O1 optimization for valgrind and sanitizers, it should be safe withouth false positives and it gives a very sensible speed up, especially with valgrind. The spee dup allow us to increase testing to depth 10, useful for thread sanitizer. No functional change.
2017-08-16 03:28:54 -06:00
# Verify bench number against various builds
Improve CI testing also enable CXXFLAGS="-D_GLIBCXX_DEBUG" in CI. closes https://github.com/official-stockfish/Stockfish/pull/2692 No functional change.
2020-05-21 00:25:37 -06:00
- export CXXFLAGS="-Werror -D_GLIBCXX_DEBUG"
This commit enables a mixed bench, to improve CI and allow for PGO (profile-build) of the NNUE part of the code. Joint work gvreuls / vondele * Download the default NNUE net in AppVeyor * Download net in travis CI `make net` * Adjust tests to cover more archs, speedup instrumented testing * Introduce 'mixed' bench as default, with further options: classical, NNUE, mixed. mixed (default) and NNUE require the default net to be present, which can be obtained with ``` make net ``` Further examples (first is equivalent to `./stockfish bench`): ``` ./stockfish bench 16 1 13 default depth mixed ./stockfish bench 16 1 13 default depth classical ./stockfish bench 16 1 13 default depth NNUE ``` The net is now downloaded automatically if needed for `profile-build` (usual `build` works fine without net present) PGO gives a nice speedup on fishtest: passed STC: LLR: 2.93 (-2.94,2.94) {-0.50,1.50} Total: 3360 W: 469 L: 343 D: 2548 Ptnml(0-2): 20, 246, 1030, 356, 28 https://tests.stockfishchess.org/tests/view/5f31b5499081672066537569 passed LTC: LLR: 2.97 (-2.94,2.94) {0.25,1.75} Total: 8824 W: 609 L: 502 D: 7713 Ptnml(0-2): 8, 430, 3438, 519, 17 https://tests.stockfishchess.org/tests/view/5f31c87b908167206653757c closes https://github.com/official-stockfish/Stockfish/pull/2931 fixes https://github.com/official-stockfish/Stockfish/issues/2907 requires fishtest updates before commit Bench: 4290577
2020-08-07 09:07:46 -06:00
- make clean && make -j2 ARCH=x86-64-modern optimize=no debug=yes build && ../tests/signature.sh $benchref
- export CXXFLAGS="-Werror"
- make clean && make -j2 ARCH=x86-64-modern build && ../tests/signature.sh $benchref
- make clean && make -j2 ARCH=x86-64-ssse3 build && ../tests/signature.sh $benchref
- make clean && make -j2 ARCH=x86-64-sse3-popcnt build && ../tests/signature.sh $benchref
- make clean && make -j2 ARCH=x86-64 build && ../tests/signature.sh $benchref
Add further targets to travis testing general-32, general-64 and help closes https://github.com/official-stockfish/Stockfish/pull/3014 No functional change
2020-08-16 05:21:07 -06:00
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=general-64 build && ../tests/signature.sh $benchref; fi
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-32 optimize=no debug=yes build && ../tests/signature.sh $benchref; fi
Expanded support for x86-32 architectures. add new ARCH targets x86-32-sse41-popcnt > x86 32-bit with sse41 and popcnt support x86-32-sse2 > x86 32-bit with sse2 support x86-32 > x86 32-bit generic (with mmx and sse support) retire x86-32-old (use general-32) closes https://github.com/official-stockfish/Stockfish/pull/3022 No functional change.
2020-08-17 17:56:12 -06:00
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-32-sse41-popcnt build && ../tests/signature.sh $benchref; fi
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-32-sse2 build && ../tests/signature.sh $benchref; fi
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-32 build && ../tests/signature.sh $benchref; fi
Add further targets to travis testing general-32, general-64 and help closes https://github.com/official-stockfish/Stockfish/pull/3014 No functional change
2020-08-16 05:21:07 -06:00
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=general-32 build && ../tests/signature.sh $benchref; fi
Update Makefile for macOS Changes to deal with compilation (particularly profile-build) on macOS. (1) The default toolchain has gcc masquerading as clang, the previous Makefile was not picking up the required changes to the different profiling tools. (2) The previous Makefile test for gccisclang occurred before a potential overwrite of CXX by COMPCXX (3) llvm-profdata no longer runs as a command on macOS and instead is invoked by ``xcrun llvm-profdata`` (4) Needs to support use of true gcc using e.g. ``make build ... COMPCXX=g++-10`` (5) enable profile-build in travis for macOS closes https://github.com/official-stockfish/Stockfish/pull/3043 No functional change
2020-08-21 04:28:53 -06:00
# workaround: exclude a custom version of llvm+clang, which doesn't find llvm-profdata on ubuntu
- if [[ "$TRAVIS_OS_NAME" != "linux" || "$COMP" == "gcc" ]]; then make clean && make -j2 ARCH=x86-64-modern profile-build && ../tests/signature.sh $benchref; fi
This commit enables a mixed bench, to improve CI and allow for PGO (profile-build) of the NNUE part of the code. Joint work gvreuls / vondele * Download the default NNUE net in AppVeyor * Download net in travis CI `make net` * Adjust tests to cover more archs, speedup instrumented testing * Introduce 'mixed' bench as default, with further options: classical, NNUE, mixed. mixed (default) and NNUE require the default net to be present, which can be obtained with ``` make net ``` Further examples (first is equivalent to `./stockfish bench`): ``` ./stockfish bench 16 1 13 default depth mixed ./stockfish bench 16 1 13 default depth classical ./stockfish bench 16 1 13 default depth NNUE ``` The net is now downloaded automatically if needed for `profile-build` (usual `build` works fine without net present) PGO gives a nice speedup on fishtest: passed STC: LLR: 2.93 (-2.94,2.94) {-0.50,1.50} Total: 3360 W: 469 L: 343 D: 2548 Ptnml(0-2): 20, 246, 1030, 356, 28 https://tests.stockfishchess.org/tests/view/5f31b5499081672066537569 passed LTC: LLR: 2.97 (-2.94,2.94) {0.25,1.75} Total: 8824 W: 609 L: 502 D: 7713 Ptnml(0-2): 8, 430, 3438, 519, 17 https://tests.stockfishchess.org/tests/view/5f31c87b908167206653757c closes https://github.com/official-stockfish/Stockfish/pull/2931 fixes https://github.com/official-stockfish/Stockfish/issues/2907 requires fishtest updates before commit Bench: 4290577
2020-08-07 09:07:46 -06:00
# compile only for some more advanced architectures (might not run in travis)
- make clean && make -j2 ARCH=x86-64-avx2 build
- make clean && make -j2 ARCH=x86-64-bmi2 build
Support VNNI on 256bit vectors due to downclocking on current chips (tested up to cascade lake) supporting avx512 and vnni512, it is better to use avx2 or vnni256 in multithreaded (in particular hyperthreaded) engine use. In single threaded use, the picture is different. gcc compilation for vnni256 requires a toolchain for gcc >= 9. closes https://github.com/official-stockfish/Stockfish/pull/3038 No functional change
2020-08-20 17:59:27 -06:00
- make clean && make -j2 ARCH=x86-64-avx512 build
- make clean && make -j2 ARCH=x86-64-vnni512 build
Allow for VNNI256 compilation with g++-8 explicitly pass needed -mavx512f -mavx512bw flags closes https://github.com/official-stockfish/Stockfish/pull/3061 No functional change
2020-08-24 04:38:01 -06:00
- make clean && make -j2 ARCH=x86-64-vnni256 build
Make ONE_PLY value independent again And a Trevis CI test to catch future issues. No functional change.
2019-01-27 01:20:38 -07:00
New shell scripts for testing, used for travis CI (#957) Perform more complex verification and validation. - signature.sh : extract and optionally compare Bench/Signature/Node count. - perft.sh : verify perft counts for a number of positions. - instrumented.sh : run a few commands or uci sequences through valgrind/sanitizer instrumented binaries. - reprosearch.sh : verify reproducibility of search. These script can be used from directly from the command line in the src directory. Update travis script to use these shell scripts. No functional change.
2017-01-09 02:30:57 -07:00
#
Speed up Trevis CI Avoid a couple of redundant rebuilds and compile with 2 threads since travis gives 2vCPUs. Also enable -O1 optimization for valgrind and sanitizers, it should be safe withouth false positives and it gives a very sensible speed up, especially with valgrind. The spee dup allow us to increase testing to depth 10, useful for thread sanitizer. No functional change.
2017-08-16 03:28:54 -06:00
# Check perft and reproducible search
This commit enables a mixed bench, to improve CI and allow for PGO (profile-build) of the NNUE part of the code. Joint work gvreuls / vondele * Download the default NNUE net in AppVeyor * Download net in travis CI `make net` * Adjust tests to cover more archs, speedup instrumented testing * Introduce 'mixed' bench as default, with further options: classical, NNUE, mixed. mixed (default) and NNUE require the default net to be present, which can be obtained with ``` make net ``` Further examples (first is equivalent to `./stockfish bench`): ``` ./stockfish bench 16 1 13 default depth mixed ./stockfish bench 16 1 13 default depth classical ./stockfish bench 16 1 13 default depth NNUE ``` The net is now downloaded automatically if needed for `profile-build` (usual `build` works fine without net present) PGO gives a nice speedup on fishtest: passed STC: LLR: 2.93 (-2.94,2.94) {-0.50,1.50} Total: 3360 W: 469 L: 343 D: 2548 Ptnml(0-2): 20, 246, 1030, 356, 28 https://tests.stockfishchess.org/tests/view/5f31b5499081672066537569 passed LTC: LLR: 2.97 (-2.94,2.94) {0.25,1.75} Total: 8824 W: 609 L: 502 D: 7713 Ptnml(0-2): 8, 430, 3438, 519, 17 https://tests.stockfishchess.org/tests/view/5f31c87b908167206653757c closes https://github.com/official-stockfish/Stockfish/pull/2931 fixes https://github.com/official-stockfish/Stockfish/issues/2907 requires fishtest updates before commit Bench: 4290577
2020-08-07 09:07:46 -06:00
- make clean && make -j2 ARCH=x86-64-modern build
Speed up Trevis CI Avoid a couple of redundant rebuilds and compile with 2 threads since travis gives 2vCPUs. Also enable -O1 optimization for valgrind and sanitizers, it should be safe withouth false positives and it gives a very sensible speed up, especially with valgrind. The spee dup allow us to increase testing to depth 10, useful for thread sanitizer. No functional change.
2017-08-16 03:28:54 -06:00
- ../tests/perft.sh
- ../tests/reprosearch.sh
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
New shell scripts for testing, used for travis CI (#957) Perform more complex verification and validation. - signature.sh : extract and optionally compare Bench/Signature/Node count. - perft.sh : verify perft counts for a number of positions. - instrumented.sh : run a few commands or uci sequences through valgrind/sanitizer instrumented binaries. - reprosearch.sh : verify reproducibility of search. These script can be used from directly from the command line in the src directory. Update travis script to use these shell scripts. No functional change.
2017-01-09 02:30:57 -07:00
#
Speed up Trevis CI Avoid a couple of redundant rebuilds and compile with 2 threads since travis gives 2vCPUs. Also enable -O1 optimization for valgrind and sanitizers, it should be safe withouth false positives and it gives a very sensible speed up, especially with valgrind. The spee dup allow us to increase testing to depth 10, useful for thread sanitizer. No functional change.
2017-08-16 03:28:54 -06:00
# Valgrind
New shell scripts for testing, used for travis CI (#957) Perform more complex verification and validation. - signature.sh : extract and optionally compare Bench/Signature/Node count. - perft.sh : verify perft counts for a number of positions. - instrumented.sh : run a few commands or uci sequences through valgrind/sanitizer instrumented binaries. - reprosearch.sh : verify reproducibility of search. These script can be used from directly from the command line in the src directory. Update travis script to use these shell scripts. No functional change.
2017-01-09 02:30:57 -07:00
#
Small improvements to the CI infrastructure - avoid inlining for the debug testing so that suppressions work - provide more output for triggered errors No functional change.
2019-01-09 08:14:34 -07:00
- export CXXFLAGS="-O1 -fno-inline"
This commit enables a mixed bench, to improve CI and allow for PGO (profile-build) of the NNUE part of the code. Joint work gvreuls / vondele * Download the default NNUE net in AppVeyor * Download net in travis CI `make net` * Adjust tests to cover more archs, speedup instrumented testing * Introduce 'mixed' bench as default, with further options: classical, NNUE, mixed. mixed (default) and NNUE require the default net to be present, which can be obtained with ``` make net ``` Further examples (first is equivalent to `./stockfish bench`): ``` ./stockfish bench 16 1 13 default depth mixed ./stockfish bench 16 1 13 default depth classical ./stockfish bench 16 1 13 default depth NNUE ``` The net is now downloaded automatically if needed for `profile-build` (usual `build` works fine without net present) PGO gives a nice speedup on fishtest: passed STC: LLR: 2.93 (-2.94,2.94) {-0.50,1.50} Total: 3360 W: 469 L: 343 D: 2548 Ptnml(0-2): 20, 246, 1030, 356, 28 https://tests.stockfishchess.org/tests/view/5f31b5499081672066537569 passed LTC: LLR: 2.97 (-2.94,2.94) {0.25,1.75} Total: 8824 W: 609 L: 502 D: 7713 Ptnml(0-2): 8, 430, 3438, 519, 17 https://tests.stockfishchess.org/tests/view/5f31c87b908167206653757c closes https://github.com/official-stockfish/Stockfish/pull/2931 fixes https://github.com/official-stockfish/Stockfish/issues/2907 requires fishtest updates before commit Bench: 4290577
2020-08-07 09:07:46 -06:00
- if [ -x "$(command -v valgrind )" ]; then make clean && make -j2 ARCH=x86-64-modern debug=yes optimize=no build > /dev/null && ../tests/instrumented.sh --valgrind; fi
Multi-threaded search testing with valgrind Also check with valgrind the multi-threaded search. On top of the fix for issue #1227 (PR #1235). No functional change.
2017-08-31 14:11:09 -06:00
- if [ -x "$(command -v valgrind )" ]; then ../tests/instrumented.sh --valgrind-thread; fi
Add NNUE evaluation This patch ports the efficiently updatable neural network (NNUE) evaluation to Stockfish. Both the NNUE and the classical evaluations are available, and can be used to assign a value to a position that is later used in alpha-beta (PVS) search to find the best move. The classical evaluation computes this value as a function of various chess concepts, handcrafted by experts, tested and tuned using fishtest. The NNUE evaluation computes this value with a neural network based on basic inputs. The network is optimized and trained on the evalutions of millions of positions at moderate search depth. The NNUE evaluation was first introduced in shogi, and ported to Stockfish afterward. It can be evaluated efficiently on CPUs, and exploits the fact that only parts of the neural network need to be updated after a typical chess move. [The nodchip repository](https://github.com/nodchip/Stockfish) provides additional tools to train and develop the NNUE networks. This patch is the result of contributions of various authors, from various communities, including: nodchip, ynasu87, yaneurao (initial port and NNUE authors), domschl, FireFather, rqs, xXH4CKST3RXx, tttak, zz4032, joergoster, mstembera, nguyenpham, erbsenzaehler, dorzechowski, and vondele. This new evaluation needed various changes to fishtest and the corresponding infrastructure, for which tomtor, ppigazzini, noobpwnftw, daylen, and vondele are gratefully acknowledged. The first networks have been provided by gekkehenker and sergiovieri, with the latter net (nn-97f742aaefcd.nnue) being the current default. The evaluation function can be selected at run time with the `Use NNUE` (true/false) UCI option, provided the `EvalFile` option points the the network file (depending on the GUI, with full path). The performance of the NNUE evaluation relative to the classical evaluation depends somewhat on the hardware, and is expected to improve quickly, but is currently on > 80 Elo on fishtest: 60000 @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f28fe6ea5abc164f05e4c4c ELO: 92.77 +-2.1 (95%) LOS: 100.0% Total: 60000 W: 24193 L: 8543 D: 27264 Ptnml(0-2): 609, 3850, 9708, 10948, 4885 40000 @ 20+0.2 th 8 https://tests.stockfishchess.org/tests/view/5f290229a5abc164f05e4c58 ELO: 89.47 +-2.0 (95%) LOS: 100.0% Total: 40000 W: 12756 L: 2677 D: 24567 Ptnml(0-2): 74, 1583, 8550, 7776, 2017 At the same time, the impact on the classical evaluation remains minimal, causing no significant regression: sprt @ 10+0.1 th 1 https://tests.stockfishchess.org/tests/view/5f2906a2a5abc164f05e4c5b LLR: 2.94 (-2.94,2.94) {-6.00,-4.00} Total: 34936 W: 6502 L: 6825 D: 21609 Ptnml(0-2): 571, 4082, 8434, 3861, 520 sprt @ 60+0.6 th 1 https://tests.stockfishchess.org/tests/view/5f2906cfa5abc164f05e4c5d LLR: 2.93 (-2.94,2.94) {-6.00,-4.00} Total: 10088 W: 1232 L: 1265 D: 7591 Ptnml(0-2): 49, 914, 3170, 843, 68 The needed networks can be found at https://tests.stockfishchess.org/nns It is recommended to use the default one as indicated by the `EvalFile` UCI option. Guidelines for testing new nets can be found at https://github.com/glinscott/fishtest/wiki/Creating-my-first-test#nnue-net-tests Integration has been discussed in various issues: https://github.com/official-stockfish/Stockfish/issues/2823 https://github.com/official-stockfish/Stockfish/issues/2728 The integration branch will be closed after the merge: https://github.com/official-stockfish/Stockfish/pull/2825 https://github.com/official-stockfish/Stockfish/tree/nnue-player-wip closes https://github.com/official-stockfish/Stockfish/pull/2912 This will be an exciting time for computer chess, looking forward to seeing the evolution of this approach. Bench: 4746616
2020-08-05 09:11:15 -06:00
New shell scripts for testing, used for travis CI (#957) Perform more complex verification and validation. - signature.sh : extract and optionally compare Bench/Signature/Node count. - perft.sh : verify perft counts for a number of positions. - instrumented.sh : run a few commands or uci sequences through valgrind/sanitizer instrumented binaries. - reprosearch.sh : verify reproducibility of search. These script can be used from directly from the command line in the src directory. Update travis script to use these shell scripts. No functional change.
2017-01-09 02:30:57 -07:00
#
Speed up Trevis CI Avoid a couple of redundant rebuilds and compile with 2 threads since travis gives 2vCPUs. Also enable -O1 optimization for valgrind and sanitizers, it should be safe withouth false positives and it gives a very sensible speed up, especially with valgrind. The spee dup allow us to increase testing to depth 10, useful for thread sanitizer. No functional change.
2017-08-16 03:28:54 -06:00
# Sanitizer
New shell scripts for testing, used for travis CI (#957) Perform more complex verification and validation. - signature.sh : extract and optionally compare Bench/Signature/Node count. - perft.sh : verify perft counts for a number of positions. - instrumented.sh : run a few commands or uci sequences through valgrind/sanitizer instrumented binaries. - reprosearch.sh : verify reproducibility of search. These script can be used from directly from the command line in the src directory. Update travis script to use these shell scripts. No functional change.
2017-01-09 02:30:57 -07:00
#
This commit enables a mixed bench, to improve CI and allow for PGO (profile-build) of the NNUE part of the code. Joint work gvreuls / vondele * Download the default NNUE net in AppVeyor * Download net in travis CI `make net` * Adjust tests to cover more archs, speedup instrumented testing * Introduce 'mixed' bench as default, with further options: classical, NNUE, mixed. mixed (default) and NNUE require the default net to be present, which can be obtained with ``` make net ``` Further examples (first is equivalent to `./stockfish bench`): ``` ./stockfish bench 16 1 13 default depth mixed ./stockfish bench 16 1 13 default depth classical ./stockfish bench 16 1 13 default depth NNUE ``` The net is now downloaded automatically if needed for `profile-build` (usual `build` works fine without net present) PGO gives a nice speedup on fishtest: passed STC: LLR: 2.93 (-2.94,2.94) {-0.50,1.50} Total: 3360 W: 469 L: 343 D: 2548 Ptnml(0-2): 20, 246, 1030, 356, 28 https://tests.stockfishchess.org/tests/view/5f31b5499081672066537569 passed LTC: LLR: 2.97 (-2.94,2.94) {0.25,1.75} Total: 8824 W: 609 L: 502 D: 7713 Ptnml(0-2): 8, 430, 3438, 519, 17 https://tests.stockfishchess.org/tests/view/5f31c87b908167206653757c closes https://github.com/official-stockfish/Stockfish/pull/2931 fixes https://github.com/official-stockfish/Stockfish/issues/2907 requires fishtest updates before commit Bench: 4290577
2020-08-07 09:07:46 -06:00
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-64-modern sanitize=undefined optimize=no debug=yes build > /dev/null && ../tests/instrumented.sh --sanitizer-undefined; fi
- if [[ "$TRAVIS_OS_NAME" == "linux" ]]; then make clean && make -j2 ARCH=x86-64-modern sanitize=thread optimize=no debug=yes build > /dev/null && ../tests/instrumented.sh --sanitizer-thread; fi