Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Adds move_from to PolymorphicObject #997

Merged
merged 4 commits into from
Apr 11, 2022
Merged

Adds move_from to PolymorphicObject #997

merged 4 commits into from
Apr 11, 2022

Conversation

MarcelKoch
Copy link
Member

This PR adds move_from(PolymorphicObject*) to PolymorphicObject. It enables us to use the generic copy_from mechanisms for moves even if the move-from object is not available as a unique_ptr. That situation can appear if one tries to move from an object that is stored as a shared_ptr. (I know that moving from an object inside a shared_ptr is generally not a good idea, but I currently have no other option)

@MarcelKoch MarcelKoch added this to the Ginkgo 1.5.0 milestone Mar 24, 2022
@MarcelKoch MarcelKoch self-assigned this Mar 24, 2022
@MarcelKoch
Copy link
Member Author

Perhaps to explain a bit, I'm trying to move from an object that is stored as a shared_ptr. Of course, there is no direct conversion from shared_ptr to unique_ptr, so I can't use the existing copy_from overload easily. I also can't just create a unique_ptr from the shared_ptr like std::unique_ptr<LinOp>(shared.get()), since then both objects would try to delete the underlying pointer. I've now realized, that I could get the correct behavior also with the overload

void copy_from(std::unique_ptr<PolymorphicObject, null_deleter<PolymorphicObject> other)

Perhaps that is a better choice, since you can't easily call that by accident.

@MarcelKoch MarcelKoch added mod:core This is related to the core module. 1:ST:ready-for-review This PR is ready for review mod:all This touches all Ginkgo modules. labels Mar 24, 2022
@codecov
Copy link

codecov bot commented Mar 24, 2022

Codecov Report

Merging #997 (10d038b) into develop (b49c347) will increase coverage by 0.00%.
The diff coverage is 96.15%.

@@           Coverage Diff            @@
##           develop     #997   +/-   ##
========================================
  Coverage    93.35%   93.35%           
========================================
  Files          485      485           
  Lines        40632    40708   +76     
========================================
+ Hits         37930    38004   +74     
- Misses        2702     2704    +2     
Impacted Files Coverage Δ
include/ginkgo/core/log/record.hpp 91.83% <ø> (ø)
include/ginkgo/core/log/stream.hpp 100.00% <ø> (ø)
include/ginkgo/core/base/polymorphic_object.hpp 93.61% <62.50%> (-2.90%) ⬇️
core/log/record.cpp 97.11% <100.00%> (+0.17%) ⬆️
core/log/stream.cpp 88.88% <100.00%> (+0.38%) ⬆️
core/test/base/polymorphic_object.cpp 98.21% <100.00%> (+0.59%) ⬆️
core/test/log/record.cpp 100.00% <100.00%> (ø)
core/test/log/stream.cpp 99.23% <100.00%> (+0.05%) ⬆️
include/ginkgo/core/log/logger.hpp 85.10% <100.00%> (+0.66%) ⬆️
reference/base/index_set_kernels.cpp 94.11% <0.00%> (-0.09%) ⬇️
... and 1 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update b49c347...10d038b. Read the comment docs.

@MarcelKoch MarcelKoch requested a review from a team March 25, 2022 10:04
Copy link
Member

@upsj upsj left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM!

@@ -332,6 +363,11 @@ class EnableAbstractPolymorphicObject : public PolymorphicBase {
this->copy_from_impl(std::move(other)));
}

AbstractObject* move_from(PolymorphicObject* other)
{
return static_cast<AbstractObject*>(this->move_from_impl(other));
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Is the logger being called if you call move_from/copy_from on a concrete object? Maybe we should test that behavior?

Copy link
Member Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

No, the logger is not called here. I think this is a general pattern in our Enable* mixins. I'm not fixing this here, instead I will open a new pr which addresses all instances.

Copy link
Member

@pratikvn pratikvn left a comment

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

LGTM!

include/ginkgo/core/base/polymorphic_object.hpp Outdated Show resolved Hide resolved
@yhmtsai
Copy link
Member

yhmtsai commented Mar 29, 2022

Could you also add the more desciption when you use this move_from the shared ptr?

@MarcelKoch
Copy link
Member Author

@yhmtsai this appeared in handling the convert_to/move_to for the distributed matrix with runtime local matrix types. Currently we still store the local matrices as shared pointers, but perhaps that is something to reevaluate. Still, I think having an additional (and clear) move_from would be helpful.

@upsj
Copy link
Member

upsj commented Mar 29, 2022

Putting them into a unique_ptr and taking a unique_ptr parameter would force you to write conforming code directly. But I think this code should be useful anyways.

@MarcelKoch
Copy link
Member Author

Should I also add an overload move_from(std::unique_ptr<PolymorphicObject>)? I think that might be reasonable, because I personally didn't even consider copy_from(std::unique_ptr) to do a move due to its name. Of course the documentation says otherwise, but the name made me not consider it.

include/ginkgo/core/log/logger.hpp Outdated Show resolved Hide resolved
include/ginkgo/core/log/logger.hpp Outdated Show resolved Hide resolved
@pratikvn
Copy link
Member

Just an additional note: You need to add the event to the logger.cpp file as well.

@MarcelKoch MarcelKoch force-pushed the add-move-from branch 2 times, most recently from 63bdd99 to eb77f0c Compare March 31, 2022 11:36
@MarcelKoch MarcelKoch added 1:ST:ready-to-merge This PR is ready to merge. and removed 1:ST:ready-for-review This PR is ready for review labels Apr 1, 2022
@ginkgo-bot
Copy link
Member

Note: This PR changes the Ginkgo ABI:

Functions changes summary: 0 Removed, 3086 Changed (31778 filtered out), 797 Added functions
Variables changes summary: 0 Removed, 0 Changed, 0 Added variable

For details check the full ABI diff under Artifacts here

@sonarcloud
Copy link

sonarcloud bot commented Apr 11, 2022

Kudos, SonarCloud Quality Gate passed!    Quality Gate passed

Bug A 0 Bugs
Vulnerability A 0 Vulnerabilities
Security Hotspot A 0 Security Hotspots
Code Smell A 3 Code Smells

72.7% 72.7% Coverage
6.3% 6.3% Duplication

@MarcelKoch MarcelKoch merged commit ddd580f into develop Apr 11, 2022
@MarcelKoch MarcelKoch deleted the add-move-from branch April 11, 2022 12:47
tcojean added a commit that referenced this pull request Nov 12, 2022
Advertise release 1.5.0 and last changes

+ Add changelog,
+ Update third party libraries
+ A small fix to a CMake file

See PR: #1195

The Ginkgo team is proud to announce the new Ginkgo minor release 1.5.0. This release brings many important new features such as:
- MPI-based multi-node support for all matrix formats and most solvers;
- full DPC++/SYCL support,
- functionality and interface for GPU-resident sparse direct solvers,
- an interface for wrapping solvers with scaling and reordering applied,
- a new algebraic Multigrid solver/preconditioner,
- improved mixed-precision support,
- support for device matrix assembly,

and much more.

If you face an issue, please first check our [known issues page](https://github.com/ginkgo-project/ginkgo/wiki/Known-Issues) and the [open issues list](https://github.com/ginkgo-project/ginkgo/issues) and if you do not find a solution, feel free to [open a new issue](https://github.com/ginkgo-project/ginkgo/issues/new/choose) or ask a question using the [github discussions](https://github.com/ginkgo-project/ginkgo/discussions).

Supported systems and requirements:
+ For all platforms, CMake 3.13+
+ C++14 compliant compiler
+ Linux and macOS
  + GCC: 5.5+
  + clang: 3.9+
  + Intel compiler: 2018+
  + Apple LLVM: 8.0+
  + NVHPC: 22.7+
  + Cray Compiler: 14.0.1+
  + CUDA module: CUDA 9.2+ or NVHPC 22.7+
  + HIP module: ROCm 4.0+
  + DPC++ module: Intel OneAPI 2021.3 with oneMKL and oneDPL. Set the CXX compiler to `dpcpp`.
+ Windows
  + MinGW and Cygwin: GCC 5.5+
  + Microsoft Visual Studio: VS 2019
  + CUDA module: CUDA 9.2+, Microsoft Visual Studio
  + OpenMP module: MinGW or Cygwin.


Algorithm and important feature additions:
+ Add MPI-based multi-node for all matrix formats and solvers (except GMRES and IDR). ([#676](#676), [#908](#908), [#909](#909), [#932](#932), [#951](#951), [#961](#961), [#971](#971), [#976](#976), [#985](#985), [#1007](#1007), [#1030](#1030), [#1054](#1054), [#1100](#1100), [#1148](#1148))
+ Porting the remaining algorithms (preconditioners like ISAI, Jacobi, Multigrid, ParILU(T) and ParIC(T)) to DPC++/SYCL, update to SYCL 2020, and improve support and performance ([#896](#896), [#924](#924), [#928](#928), [#929](#929), [#933](#933), [#943](#943), [#960](#960), [#1057](#1057), [#1110](#1110),  [#1142](#1142))
+ Add a Sparse Direct interface supporting GPU-resident numerical LU factorization, symbolic Cholesky factorization, improved triangular solvers, and more ([#957](#957), [#1058](#1058), [#1072](#1072), [#1082](#1082))
+ Add a ScaleReordered interface that can wrap solvers and automatically apply reorderings and scalings ([#1059](#1059))
+ Add a Multigrid solver and improve the aggregation based PGM coarsening scheme ([#542](#542), [#913](#913), [#980](#980), [#982](#982),  [#986](#986))
+ Add infrastructure for unified, lambda-based, backend agnostic, kernels and utilize it for some simple kernels ([#833](#833), [#910](#910), [#926](#926))
+ Merge different CUDA, HIP, DPC++ and OpenMP tests under a common interface ([#904](#904), [#973](#973), [#1044](#1044), [#1117](#1117))
+ Add a device_matrix_data type for device-side matrix assembly ([#886](#886), [#963](#963), [#965](#965))
+ Add support for mixed real/complex BLAS operations ([#864](#864))
+ Add a FFT LinOp for all but DPC++/SYCL ([#701](#701))
+ Add FBCSR support for NVIDIA and AMD GPUs and CPUs with OpenMP ([#775](#775))
+ Add CSR scaling ([#848](#848))
+ Add array::const_view and equivalent to create constant matrices from non-const data ([#890](#890))
+ Add a RowGatherer LinOp supporting mixed precision to gather dense matrix rows ([#901](#901))
+ Add mixed precision SparsityCsr SpMV support ([#970](#970))
+ Allow creating CSR submatrix including from (possibly discontinuous) index sets ([#885](#885), [#964](#964))
+ Add a scaled identity addition (M <- aI + bM) feature interface and impls for Csr and Dense ([#942](#942))


Deprecations and important changes:
+ Deprecate AmgxPgm in favor of the new Pgm name. ([#1149](#1149)).
+ Deprecate specialized residual norm classes in favor of a common `ResidualNorm` class ([#1101](#1101))
+ Deprecate CamelCase non-polymorphic types in favor of snake_case versions (like array, machine_topology, uninitialized_array, index_set) ([#1031](#1031), [#1052](#1052))
+ Bug fix: restrict gko::share to rvalue references (*possible interface break*) ([#1020](#1020))
+ Bug fix: when using cuSPARSE's triangular solvers, specifying the factory parameter `num_rhs` is now required when solving for more than one right-hand side, otherwise an exception is thrown ([#1184](#1184)).
+ Drop official support for old CUDA < 9.2 ([#887](#887))


Improved performance additions:
+ Reuse tmp storage in reductions in solvers and add a mutable workspace to all solvers ([#1013](#1013), [#1028](#1028))
+ Add HIP unsafe atomic option for AMD ([#1091](#1091))
+ Prefer vendor implementations for Dense dot, conj_dot and norm2 when available ([#967](#967)).
+ Tuned OpenMP SellP, COO, and ELL SpMV kernels for a small number of RHS ([#809](#809))


Fixes:
+ Fix various compilation warnings ([#1076](#1076), [#1183](#1183), [#1189](#1189))
+ Fix issues with hwloc-related tests ([#1074](#1074))
+ Fix include headers for GCC 12 ([#1071](#1071))
+ Fix for simple-solver-logging example ([#1066](#1066))
+ Fix for potential memory leak in Logger ([#1056](#1056))
+ Fix logging of mixin classes ([#1037](#1037))
+ Improve value semantics for LinOp types, like moved-from state in cross-executor copy/clones ([#753](#753))
+ Fix some matrix SpMV and conversion corner cases ([#905](#905), [#978](#978))
+ Fix uninitialized data ([#958](#958))
+ Fix CUDA version requirement for cusparseSpSM ([#953](#953))
+ Fix several issues within bash-script ([#1016](#1016))
+ Fixes for `NVHPC` compiler support ([#1194](#1194))


Other additions:
+ Simplify and properly name GMRES kernels ([#861](#861))
+ Improve pkg-config support for non-CMake libraries ([#923](#923), [#1109](#1109))
+ Improve gdb pretty printer ([#987](#987), [#1114](#1114))
+ Add a logger highlighting inefficient allocation and copy patterns ([#1035](#1035))
+ Improved and optimized test random matrix generation ([#954](#954), [#1032](#1032))
+ Better CSR strategy defaults ([#969](#969))
+ Add `move_from` to `PolymorphicObject` ([#997](#997))
+ Remove unnecessary device_guard usage ([#956](#956))
+ Improvements to the generic accessor for mixed-precision ([#727](#727))
+ Add a naive lower triangular solver implementation for CUDA ([#764](#764))
+ Add support for int64 indices from CUDA 11 onward with SpMV and SpGEMM ([#897](#897))
+ Add a L1 norm implementation ([#900](#900))
+ Add reduce_add for arrays ([#831](#831))
+ Add utility to simplify Dense View creation from an existing Dense vector ([#1136](#1136)).
+ Add a custom transpose implementation for Fbcsr and Csr transpose for unsupported vendor types ([#1123](#1123))
+ Make IDR random initilization deterministic ([#1116](#1116))
+ Move the algorithm choice for triangular solvers from Csr::strategy_type to a factory parameter ([#1088](#1088))
+ Update CUDA archCoresPerSM ([#1175](#1116))
+ Add kernels for Csr sparsity pattern lookup ([#994](#994))
+ Differentiate between structural and numerical zeros in Ell/Sellp ([#1027](#1027))
+ Add a binary IO format for matrix data ([#984](#984))
+ Add a tuple zip_iterator implementation ([#966](#966))
+ Simplify kernel stubs and declarations ([#888](#888))
+ Simplify GKO_REGISTER_OPERATION with lambdas ([#859](#859))
+ Simplify copy to device in tests and examples ([#863](#863))
+ More verbose output to array assertions ([#858](#858))
+ Allow parallel compilation for Jacobi kernels ([#871](#871))
+ Change clang-format pointer alignment to left ([#872](#872))
+ Various improvements and fixes to the benchmarking framework ([#750](#750), [#759](#759), [#870](#870), [#911](#911), [#1033](#1033), [#1137](#1137))
+ Various documentation improvements ([#892](#892), [#921](#921), [#950](#950), [#977](#977), [#1021](#1021), [#1068](#1068), [#1069](#1069), [#1080](#1080), [#1081](#1081), [#1108](#1108), [#1153](#1153), [#1154](#1154))
+ Various CI improvements ([#868](#868), [#874](#874), [#884](#884), [#889](#889), [#899](#899), [#903](#903),  [#922](#922), [#925](#925), [#930](#930), [#936](#936), [#937](#937), [#958](#958), [#882](#882), [#1011](#1011), [#1015](#1015), [#989](#989), [#1039](#1039), [#1042](#1042), [#1067](#1067), [#1073](#1073), [#1075](#1075), [#1083](#1083), [#1084](#1084), [#1085](#1085), [#1139](#1139), [#1178](#1178), [#1187](#1187))
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
1:ST:ready-to-merge This PR is ready to merge. mod:all This touches all Ginkgo modules. mod:core This is related to the core module.
Projects
None yet
Development

Successfully merging this pull request may close these issues.

None yet

6 participants