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Enable an ensemble build #1333

Merged
merged 4 commits into from
Jul 6, 2023
Merged

Enable an ensemble build #1333

merged 4 commits into from
Jul 6, 2023

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upsj
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@upsj upsj commented May 5, 2023

With these fixes, it's possible to build Ginkgo for all backends simultaneously on the ginkgodev/unified container image. Includes a few test fixes.

Corresponding CMake invocation:

cmake -GNinja -DCMAKE_CXX_COMPILER=dpcpp -DOpenMP_CXX_FLAGS=-qopenmp -DOpenMP_CXX_LIB_NAMES=libiomp5 -DOpenMP_libiomp5_LIBRARY=/opt/intel/oneapi/compiler/latest/linux/compiler/lib/intel64_lin/libiomp5.so ..

TODO:

@upsj upsj added the 1:ST:WIP This PR is a work in progress. Not ready for review. label May 5, 2023
@upsj upsj self-assigned this May 5, 2023
@upsj upsj changed the title Enable a unified build Enable an ensemble build May 5, 2023
@ginkgo-bot ginkgo-bot added reg:build This is related to the build system. mod:core This is related to the core module. mod:cuda This is related to the CUDA module. type:solver This is related to the solvers type:preconditioner This is related to the preconditioners type:matrix-format This is related to the Matrix formats labels May 5, 2023
@upsj upsj added 1:ST:ready-for-review This PR is ready for review and removed 1:ST:WIP This PR is a work in progress. Not ready for review. labels Jul 2, 2023
@upsj upsj requested a review from a team July 2, 2023 18:15
@MarcelKoch MarcelKoch mentioned this pull request Jul 3, 2023
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upsj commented Jul 4, 2023

rebase!

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LGTM, except for the test folder structure.

test/mpi/distributed/solver/solver.cpp Outdated Show resolved Hide resolved
test/mpi/distributed/CMakeLists.txt Outdated Show resolved Hide resolved
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LGTM

Comment on lines +43 to +45
#ifdef GKO_COMPILING_DPCPP
#include <CL/sycl.hpp>
#endif
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What is in this header?
It seems you are moving this include from include/ginkgo/core/base/math.hpp to this file.

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@upsj upsj Jul 5, 2023

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The queue is an incomplete class in executor.hpp

if (exec->get_queue()->get_device().is_gpu()) {
    GTEST_SKIP() << "skip the test because oneMKL GEMM on gpu may give NaN "
                    "(under investigation)";
}

Comment on lines +166 to +168
#if defined(GKO_COMPILING_HIP) && GINKGO_HIP_PLATFORM_HCC
GTEST_SKIP() << "rocFFT has a bug related to strided 1D FFT";
#endif
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is something related to this ROCm/rocFFT#353 ?
but it should pass all in the current CI setup

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No, this is a different bug (causing incorrect results, not an error) I didn't bother creating a reproducer for yet.

@upsj upsj added 1:ST:ready-to-merge This PR is ready to merge. 1:ST:no-changelog-entry Skip the wiki check for changelog update and removed 1:ST:ready-for-review This PR is ready for review 1:ST:no-changelog-entry Skip the wiki check for changelog update labels Jul 5, 2023
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upsj commented Jul 5, 2023

rebase!

upsj added 4 commits July 6, 2023 15:08
- remove SYCL-specific headers from general builds
- disable failing tests for rocFFT
- disable DPC++ distributed tests
@upsj upsj merged commit d60b02c into develop Jul 6, 2023
11 checks passed
@upsj upsj deleted the unified_build_fixes branch July 6, 2023 18:14
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sonarcloud bot commented Jul 7, 2023

Kudos, SonarCloud Quality Gate passed!    Quality Gate passed

Bug A 0 Bugs
Vulnerability A 0 Vulnerabilities
Security Hotspot E 1 Security Hotspot
Code Smell A 45 Code Smells

99.1% 99.1% Coverage
2.9% 2.9% Duplication

@tcojean tcojean mentioned this pull request Nov 6, 2023
tcojean added a commit that referenced this pull request Nov 10, 2023
Release 1.7.0 to master

The Ginkgo team is proud to announce the new Ginkgo minor release 1.7.0. This release brings new features such as:
- Complete GPU-resident sparse direct solvers feature set and interfaces,
- Improved Cholesky factorization performance,
- A new MC64 reordering,
- Batched iterative solver support with the BiCGSTAB solver with batched Dense and ELL matrix types,
- MPI support for the SYCL backend,
- Improved ParILU(T)/ParIC(T) preconditioner convergence,
and 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 3.16+
+ C++14 compliant compiler
+ Linux and macOS
  + GCC: 5.5+
  + clang: 3.9+
  + Intel compiler: 2019+
  + Apple Clang: 14.0 is tested. Earlier versions might also work.
  + NVHPC: 22.7+
  + Cray Compiler: 14.0.1+
  + CUDA module: CMake 3.18+, and CUDA 10.1+ or NVHPC 22.7+
  + HIP module: ROCm 4.5+
  + DPC++ module: Intel oneAPI 2022.1+ with oneMKL and oneDPL. Set the CXX compiler to `dpcpp` or `icpx`.
  + MPI: standard version 3.1+, ideally GPU Aware, for best performance
+ Windows
  + MinGW: GCC 5.5+
  + Microsoft Visual Studio: VS 2019+
  + CUDA module: CUDA 10.1+, Microsoft Visual Studio
  + OpenMP module: MinGW.

### Version support changes

+ CUDA 9.2 is no longer supported and 10.0 is untested [#1382](#1382)
+ Ginkgo now requires CMake version 3.16 (and 3.18 for CUDA) [#1368](#1368)

### Interface changes

+ `const` Factory parameters can no longer be modified through `with_*` functions, as this breaks const-correctness [#1336](#1336) [#1439](#1439)

### New Deprecations

+ The `device_reset` parameter of CUDA and HIP executors no longer has an effect, and its `allocation_mode` parameters have been deprecated in favor of the `Allocator` interface. [#1315](#1315)
+ The CMake parameter `GINKGO_BUILD_DPCPP` has been deprecated in favor of `GINKGO_BUILD_SYCL`. [#1350](#1350)
+ The `gko::reorder::Rcm` interface has been deprecated in favor of `gko::experimental::reorder::Rcm` based on `Permutation`. [#1418](#1418)
+ The Permutation class' `permute_mask` functionality. [#1415](#1415)
+ Multiple functions with typos (`set_complex_subpsace()`, range functions such as `conj_operaton` etc). [#1348](#1348)

### Summary of previous deprecations
+ `gko::lend()` is not necessary anymore.
+ The classes `RelativeResidualNorm` and `AbsoluteResidualNorm` are deprecated in favor of `ResidualNorm`.
+ The class `AmgxPgm` is deprecated in favor of `Pgm`.
+ Default constructors for the CSR `load_balance` and `automatical` strategies
+ The PolymorphicObject's move-semantic `copy_from` variant
+ The templated `SolverBase` class.
+ The class `MachineTopology` is deprecated in favor of `machine_topology`.
+ Logger constructors and create functions with the `executor` parameter.
+ The virtual, protected, Dense functions `compute_norm1_impl`, `add_scaled_impl`, etc.
+ Logger events for solvers and criterion without the additional `implicit_tau_sq` parameter.
+ The global `gko::solver::default_krylov_dim`, use instead `gko::solver::gmres_default_krylov_dim`.

### Added features

+ Adds a batch::BatchLinOp class that forms a base class for batched linear operators such as batched matrix formats, solver and preconditioners [#1379](#1379)
+ Adds a batch::MultiVector class that enables operations such as dot, norm, scale on batched vectors [#1371](#1371)
+ Adds a batch::Dense matrix format that stores batched dense matrices and provides gemv operations for these dense matrices. [#1413](#1413)
+ Adds a batch::Ell matrix format that stores batched Ell matrices and provides spmv operations for these batched Ell matrices. [#1416](#1416) [#1437](#1437)
+ Add a batch::Bicgstab solver (class, core, and reference kernels) that enables iterative solution of batched linear systems [#1438](#1438).
+ Add device kernels (CUDA, HIP, and DPCPP) for batch::Bicgstab solver. [#1443](#1443).
+ New MC64 reordering algorithm which optimizes the diagonal product or sum of a matrix by permuting the rows, and computes additional scaling factors for equilibriation [#1120](#1120)
+ New interface for (non-symmetric) permutation and scaled permutation of Dense and Csr matrices [#1415](#1415)
+ LU and Cholesky Factorizations can now be separated into their factors [#1432](#1432)
+ New symbolic LU factorization algorithm that is optimized for matrices with an almost-symmetric sparsity pattern [#1445](#1445)
+ Sorting kernels for SparsityCsr on all backends [#1343](#1343)
+ Allow passing pre-generated local solver as factory parameter for the distributed Schwarz preconditioner [#1426](#1426)
+ Add DPCPP kernels for Partition [#1034](#1034), and CSR's `check_diagonal_entries` and `add_scaled_identity` functionality [#1436](#1436)
+ Adds a helper function to create a partition based on either local sizes, or local ranges [#1227](#1227)
+ Add function to compute arithmetic mean of dense and distributed vectors [#1275](#1275)
+ Adds `icpx` compiler supports [#1350](#1350)
+ All backends can be built simultaneously [#1333](#1333)
+ Emits a CMake warning in downstream projects that use different compilers than the installed Ginkgo [#1372](#1372)
+ Reordering algorithms in sparse_blas benchmark [#1354](#1354)
+ Benchmarks gained an `-allocator` parameter to specify device allocators [#1385](#1385)
+ Benchmarks gained an `-input_matrix` parameter that initializes the input JSON based on the filename [#1387](#1387)
+ Benchmark inputs can now be reordered as a preprocessing step [#1408](#1408)


### Improvements

+ Significantly improve Cholesky factorization performance [#1366](#1366)
+ Improve parallel build performance [#1378](#1378)
+ Allow constrained parallel test execution using CTest resources [#1373](#1373)
+ Use arithmetic type more inside mixed precision ELL [#1414](#1414)
+ Most factory parameters of factory type no longer need to be constructed explicitly via `.on(exec)` [#1336](#1336) [#1439](#1439)
+ Improve ParILU(T)/ParIC(T) convergence by using more appropriate atomic operations [#1434](#1434)

### Fixes

+ Fix an over-allocation for OpenMP reductions [#1369](#1369)
+ Fix DPCPP's common-kernel reduction for empty input sizes [#1362](#1362)
+ Fix several typos in the API and documentation [#1348](#1348)
+ Fix inconsistent `Threads` between generations [#1388](#1388)
+ Fix benchmark median condition [#1398](#1398)
+ Fix HIP 5.6.0 compilation [#1411](#1411)
+ Fix missing destruction of rand_generator from cuda/hip [#1417](#1417)
+ Fix PAPI logger destruction order [#1419](#1419)
+ Fix TAU logger compilation [#1422](#1422)
+ Fix relative criterion to not iterate if the residual is already zero [#1079](#1079)
+ Fix memory_order invocations with C++20 changes [#1402](#1402)
+ Fix `check_diagonal_entries_exist` report correctly when only missing diagonal value in the last rows. [#1440](#1440)
+ Fix checking OpenMPI version in cross-compilation settings [#1446](#1446)
+ Fix false-positive deprecation warnings in Ginkgo, especially for the old Rcm (it doesn't emit deprecation warnings anymore as a result but is still considered deprecated) [#1444](#1444)


### Related PR: #1451
tcojean added a commit that referenced this pull request Nov 10, 2023
Release 1.7.0 to develop

The Ginkgo team is proud to announce the new Ginkgo minor release 1.7.0. This release brings new features such as:
- Complete GPU-resident sparse direct solvers feature set and interfaces,
- Improved Cholesky factorization performance,
- A new MC64 reordering,
- Batched iterative solver support with the BiCGSTAB solver with batched Dense and ELL matrix types,
- MPI support for the SYCL backend,
- Improved ParILU(T)/ParIC(T) preconditioner convergence,
and 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 3.16+
+ C++14 compliant compiler
+ Linux and macOS
  + GCC: 5.5+
  + clang: 3.9+
  + Intel compiler: 2019+
  + Apple Clang: 14.0 is tested. Earlier versions might also work.
  + NVHPC: 22.7+
  + Cray Compiler: 14.0.1+
  + CUDA module: CMake 3.18+, and CUDA 10.1+ or NVHPC 22.7+
  + HIP module: ROCm 4.5+
  + DPC++ module: Intel oneAPI 2022.1+ with oneMKL and oneDPL. Set the CXX compiler to `dpcpp` or `icpx`.
  + MPI: standard version 3.1+, ideally GPU Aware, for best performance
+ Windows
  + MinGW: GCC 5.5+
  + Microsoft Visual Studio: VS 2019+
  + CUDA module: CUDA 10.1+, Microsoft Visual Studio
  + OpenMP module: MinGW.

### Version support changes

+ CUDA 9.2 is no longer supported and 10.0 is untested [#1382](#1382)
+ Ginkgo now requires CMake version 3.16 (and 3.18 for CUDA) [#1368](#1368)

### Interface changes

+ `const` Factory parameters can no longer be modified through `with_*` functions, as this breaks const-correctness [#1336](#1336) [#1439](#1439)

### New Deprecations

+ The `device_reset` parameter of CUDA and HIP executors no longer has an effect, and its `allocation_mode` parameters have been deprecated in favor of the `Allocator` interface. [#1315](#1315)
+ The CMake parameter `GINKGO_BUILD_DPCPP` has been deprecated in favor of `GINKGO_BUILD_SYCL`. [#1350](#1350)
+ The `gko::reorder::Rcm` interface has been deprecated in favor of `gko::experimental::reorder::Rcm` based on `Permutation`. [#1418](#1418)
+ The Permutation class' `permute_mask` functionality. [#1415](#1415)
+ Multiple functions with typos (`set_complex_subpsace()`, range functions such as `conj_operaton` etc). [#1348](#1348)

### Summary of previous deprecations
+ `gko::lend()` is not necessary anymore.
+ The classes `RelativeResidualNorm` and `AbsoluteResidualNorm` are deprecated in favor of `ResidualNorm`.
+ The class `AmgxPgm` is deprecated in favor of `Pgm`.
+ Default constructors for the CSR `load_balance` and `automatical` strategies
+ The PolymorphicObject's move-semantic `copy_from` variant
+ The templated `SolverBase` class.
+ The class `MachineTopology` is deprecated in favor of `machine_topology`.
+ Logger constructors and create functions with the `executor` parameter.
+ The virtual, protected, Dense functions `compute_norm1_impl`, `add_scaled_impl`, etc.
+ Logger events for solvers and criterion without the additional `implicit_tau_sq` parameter.
+ The global `gko::solver::default_krylov_dim`, use instead `gko::solver::gmres_default_krylov_dim`.

### Added features

+ Adds a batch::BatchLinOp class that forms a base class for batched linear operators such as batched matrix formats, solver and preconditioners [#1379](#1379)
+ Adds a batch::MultiVector class that enables operations such as dot, norm, scale on batched vectors [#1371](#1371)
+ Adds a batch::Dense matrix format that stores batched dense matrices and provides gemv operations for these dense matrices. [#1413](#1413)
+ Adds a batch::Ell matrix format that stores batched Ell matrices and provides spmv operations for these batched Ell matrices. [#1416](#1416) [#1437](#1437)
+ Add a batch::Bicgstab solver (class, core, and reference kernels) that enables iterative solution of batched linear systems [#1438](#1438).
+ Add device kernels (CUDA, HIP, and DPCPP) for batch::Bicgstab solver. [#1443](#1443).
+ New MC64 reordering algorithm which optimizes the diagonal product or sum of a matrix by permuting the rows, and computes additional scaling factors for equilibriation [#1120](#1120)
+ New interface for (non-symmetric) permutation and scaled permutation of Dense and Csr matrices [#1415](#1415)
+ LU and Cholesky Factorizations can now be separated into their factors [#1432](#1432)
+ New symbolic LU factorization algorithm that is optimized for matrices with an almost-symmetric sparsity pattern [#1445](#1445)
+ Sorting kernels for SparsityCsr on all backends [#1343](#1343)
+ Allow passing pre-generated local solver as factory parameter for the distributed Schwarz preconditioner [#1426](#1426)
+ Add DPCPP kernels for Partition [#1034](#1034), and CSR's `check_diagonal_entries` and `add_scaled_identity` functionality [#1436](#1436)
+ Adds a helper function to create a partition based on either local sizes, or local ranges [#1227](#1227)
+ Add function to compute arithmetic mean of dense and distributed vectors [#1275](#1275)
+ Adds `icpx` compiler supports [#1350](#1350)
+ All backends can be built simultaneously [#1333](#1333)
+ Emits a CMake warning in downstream projects that use different compilers than the installed Ginkgo [#1372](#1372)
+ Reordering algorithms in sparse_blas benchmark [#1354](#1354)
+ Benchmarks gained an `-allocator` parameter to specify device allocators [#1385](#1385)
+ Benchmarks gained an `-input_matrix` parameter that initializes the input JSON based on the filename [#1387](#1387)
+ Benchmark inputs can now be reordered as a preprocessing step [#1408](#1408)


### Improvements

+ Significantly improve Cholesky factorization performance [#1366](#1366)
+ Improve parallel build performance [#1378](#1378)
+ Allow constrained parallel test execution using CTest resources [#1373](#1373)
+ Use arithmetic type more inside mixed precision ELL [#1414](#1414)
+ Most factory parameters of factory type no longer need to be constructed explicitly via `.on(exec)` [#1336](#1336) [#1439](#1439)
+ Improve ParILU(T)/ParIC(T) convergence by using more appropriate atomic operations [#1434](#1434)

### Fixes

+ Fix an over-allocation for OpenMP reductions [#1369](#1369)
+ Fix DPCPP's common-kernel reduction for empty input sizes [#1362](#1362)
+ Fix several typos in the API and documentation [#1348](#1348)
+ Fix inconsistent `Threads` between generations [#1388](#1388)
+ Fix benchmark median condition [#1398](#1398)
+ Fix HIP 5.6.0 compilation [#1411](#1411)
+ Fix missing destruction of rand_generator from cuda/hip [#1417](#1417)
+ Fix PAPI logger destruction order [#1419](#1419)
+ Fix TAU logger compilation [#1422](#1422)
+ Fix relative criterion to not iterate if the residual is already zero [#1079](#1079)
+ Fix memory_order invocations with C++20 changes [#1402](#1402)
+ Fix `check_diagonal_entries_exist` report correctly when only missing diagonal value in the last rows. [#1440](#1440)
+ Fix checking OpenMPI version in cross-compilation settings [#1446](#1446)
+ Fix false-positive deprecation warnings in Ginkgo, especially for the old Rcm (it doesn't emit deprecation warnings anymore as a result but is still considered deprecated) [#1444](#1444)

### Related PR: #1454
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