Simple overhead benchmarking facilities #501
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I like this! This might also be useful for debugging / performance engineering. Would it be possible to get the information on how often a runtime decision was taken? Obviously, the overhead of counting this would be much higher, so we may need two runs? |
hartwiganzt
reviewed
Apr 15, 2020
| DEFINE_string(preconditioners, "none", | ||
| "A comma-separated list of preconditioners to use. " | ||
| "Supported values are: none, jacobi, adaptive-jacobi, parilu, " | ||
| "ilu, overhead"); | ||
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Maybe add an example of how to measure the overhead.
hartwiganzt
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Apr 15, 2020
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I added an iteration logger to the solver benchmark. I put this as part of the warmup since we should pretty much always have warmup and that doing this simple logging of iteration counts is not a "detailed" run. We can maybe put this logger in the main benchmarking portion, but that would add a few extra virtual calls so I decided to not proceed with this. This revealed that indeed, the solver results were accounting for 1000 iterations of a CG solver, which changes the picture significantly (1.2 ms overhead over 1000 iterations isn't too bad). I added numbers for all solvers, and also used the strategy of doing 2000 iterations - 1000 iterations, which shows that the allocations while numerous are indeed pretty much nothing. Some solvers do have more overhead than others though, the extremes being CGS vs GMRES. |
upsj
approved these changes
Apr 15, 2020
| const gko::LinOp *, const gko::LinOp *, | ||
| const gko::LinOp *) const override | ||
| { | ||
| this->num_iters = num_iterations; |
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When we have multiple right-hand sides: Do I understand correctly that this logs the maximum number of iterations over all rhs?
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## develop #501 +/- ##
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+ Coverage 88.52% 88.55% +0.03%
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Files 262 262
Lines 16632 16632
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+ Hits 14723 14728 +5
+ Misses 1909 1904 -5
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yhmtsai
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The Ginkgo team is proud to announce the new minor release of Ginkgo version 1.2.0. This release brings full HIP support to Ginkgo, new preconditioners (ParILUT, ISAI), conversion between double and float for all LinOps, and many more features and fixes. Supported systems and requirements: + For all platforms, cmake 3.9+ + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, all versions after 8.1+ + clang: 3.9+ + Intel compiler: 2017+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + HIP module: ROCm 2.8+ + Windows + MinGW and CygWin: gcc 5.3+, 6.3+, 7.3+, all versions after 8.1+ + Microsoft Visual Studio: VS 2017 15.7+ + CUDA module: CUDA 9.0+, Microsoft Visual Studio + OpenMP module: MinGW or CygWin. The current known issues can be found in the [known issues page](https://github.com/ginkgo-project/ginkgo/wiki/Known-Issues). # Additions Here are the main additions to the Ginkgo library. Other thematic additions are listed below. + Add full HIP support to Ginkgo [#344](#344), [#357](#357), [#384](#384), [#373](#373), [#391](#391), [#396](#396), [#395](#395), [#393](#393), [#404](#404), [#439](#439), [#443](#443), [#567](#567) + Add a new ISAI preconditioner [#489](#489), [#502](#502), [#512](#512), [#508](#508), [#520](#520) + Add support for ParILUT and ParICT factorization with ILU preconditioners [#400](#400) + Add a new BiCG solver [#438](#438) + Add a new permutation matrix format [#352](#352), [#469](#469) + Add CSR SpGEMM support [#386](#386), [#398](#398), [#418](#418), [#457](#457) + Add CSR SpGEAM support [#556](#556) + Make all solvers and preconditioners transposable [#535](#535) + Add CsrBuilder and CooBuilder for intrusive access to matrix arrays [#437](#437) + Add a standard-compliant allocator based on the Executors [#504](#504) + Support conversions for all LinOp between double and float [#521](#521) + Add a new boolean to the CUDA and HIP executors to control DeviceReset (default off) [#557](#557) + Add a relaxation factor to IR to represent Richardson Relaxation [#574](#574) + Add two new stopping criteria, for relative (to `norm(b)`) and absolute residual norm [#577](#577) ### Example additions + Templatize all examples to simplify changing the precision [#513](#513) + Add a new adaptive precision block-Jacobi example [#507](#507) + Add a new IR example [#522](#522) + Add a new Mixed Precision Iterative Refinement example [#525](#525) + Add a new example on iterative trisolves in ILU preconditioning [#526](#526), [#536](#536), [#550](#550) ### Compilation and library changes + Auto-detect compilation settings based on environment [#435](#435), [#537](#537) + Add SONAME to shared libraries [#524](#524) + Add clang-cuda support [#543](#543) ### Other additions + Add sorting, searching and merging kernels for GPUs [#403](#403), [#428](#428), [#417](#417), [#455](#455) + Add `gko::as` support for smart pointers [#493](#493) + Add setters and getters for criterion factories [#527](#527) + Add a new method to check whether a solver uses `x` as an initial guess [#531](#531) + Add contribution guidelines [#549](#549) # Fixes ### Algorithms + Improve the classical CSR strategy's performance [#401](#401) + Improve the CSR automatical strategy [#407](#407), [#559](#559) + Memory, speed improvements to the ELL kernel [#411](#411) + Multiple improvements and fixes to ParILU [#419](#419), [#427](#427), [#429](#429), [#456](#456), [#544](#544) + Fix multiple issues with GMRES [#481](#481), [#523](#523), [#575](#575) + Optimize OpenMP matrix conversions [#505](#505) + Ensure the linearity of the ILU preconditioner [#506](#506) + Fix IR's use of the advanced apply [#522](#522) + Fix empty matrices conversions and add tests [#560](#560) ### Other core functionalities + Fix complex number support in our math header [#410](#410) + Fix CUDA compatibility of the main ginkgo header [#450](#450) + Fix isfinite issues [#465](#465) + Fix the Array::view memory leak and the array/view copy/move [#485](#485) + Fix typos preventing use of some interface functions [#496](#496) + Fix the `gko::dim` to abide to the C++ standard [#498](#498) + Simplify the executor copy interface [#516](#516) + Optimize intermediate storage for Composition [#540](#540) + Provide an initial guess for relevant Compositions [#561](#561) + Better management of nullptr as criterion [#562](#562) + Fix the norm calculations for complex support [#564](#564) ### CUDA and HIP specific + Use the return value of the atomic operations in our wrappers [#405](#405) + Improve the portability of warp lane masks [#422](#422) + Extract thread ID computation into a separate function [#464](#464) + Reorder kernel parameters for consistency [#474](#474) + Fix the use of `pragma unroll` in HIP [#492](#492) ### Other + Fix the Ginkgo CMake installation files [#414](#414), [#553](#553) + Fix the Windows compilation [#415](#415) + Always use demangled types in error messages [#434](#434), [#486](#486) + Add CUDA header dependency to appropriate tests [#452](#452) + Fix several sonarqube or compilation warnings [#453](#453), [#463](#463), [#532](#532), [#569](#569) + Add shuffle tests [#460](#460) + Fix MSVC C2398 error [#490](#490) + Fix missing interface tests in test install [#558](#558) # Tools and ecosystem ### Benchmarks + Add better norm support in the benchmarks [#377](#377) + Add CUDA 10.1 generic SpMV support in benchmarks [#468](#468), [#473](#473) + Add sparse library ILU in benchmarks [#487](#487) + Add overhead benchmarking capacities [#501](#501) + Allow benchmarking from a matrix list file [#503](#503) + Fix benchmarking issue with JSON and non-finite numbers [#514](#514) + Fix benchmark logger crashers with OpenMP [#565](#565) ### CI related + Improvements to the CI setup with HIP compilation [#421](#421), [#466](#466) + Add MacOSX CI support [#470](#470), [#488](#488) + Add Windows CI support [#471](#471), [#488](#488), [#510](#510), [#566](#566) + Use sanitizers instead of valgrind [#476](#476) + Add automatic container generation and update facilities [#499](#499) + Fix the CI parallelism settings [#517](#517), [#538](#538), [#539](#539) + Make the codecov patch check informational [#519](#519) + Add support for LLVM sanitizers with improved thread sanitizer support [#578](#578) ### Test suite + Add an assertion for sparsity pattern equality [#416](#416) + Add core and reference multiprecision tests support [#448](#448) + Speed up GPU tests by avoiding device reset [#467](#467) + Change test matrix location string [#494](#494) ### Other + Add Ginkgo badges from our tools [#413](#413) + Update the `create_new_algorithm.sh` script [#420](#420) + Bump copyright and improve license management [#436](#436), [#433](#433) + Set clang-format minimum requirement [#441](#441), [#484](#484) + Update git-cmake-format [#446](#446), [#484](#484) + Disable the development tools by default [#442](#442) + Add a script for automatic header formatting [#447](#447) + Add GDB pretty printer for `gko::Array` [#509](#509) + Improve compilation speed [#533](#533) + Add editorconfig support [#546](#546) + Add a compile-time check for header self-sufficiency [#552](#552) # Related PR: #583
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This is done by modifying the
solverbenchmarks with:overheadboolean parameter to ask whether or not an overhead benchmark should be done. This will use a simple matrix with a single1.0value,0.0asx, andnanasb(same setup as theginkgo_overheadexample).OverheadLinOP which does a normal solver setup in terms of Factory parameters and generation, except that it has anapply_implmethod which calls four empty kernels. We have multiple runtime polymorphism calls which come into play here. I am most likely forgetting many of them:run()functions), ...OverheadLinOp can be also be used as a preconditioner.This allows the following:
We get the following results currently, benchmarked on BW Unicluster with 10.000 iterations:
0.829 us,1277.557 us.1200.118 us0.814 us,1259.751 us.1239.370 us0.837 us,1447.981 us.1410.630 us0.849 us,1001.975 us.881.990 us0.836 us,1510.327 us.1485.361 us0.788 us,0.912 us.1.479 us,2.610 us.