Split compilation of large files automatically #1378

upsj · 2023-07-31T20:10:00Z

As an alternative to #1375, here I automatically generate files that instantiate a subset of the templates in a source file each. Due to the format of the instantiation source file, it can be included both in its original form and split into different files.

codecov · 2023-08-01T05:59:02Z

Codecov Report

Patch coverage has no change and project coverage change: -0.37% ⚠️

Comparison is base (945a4d8) 91.18% compared to head (8d17609) 90.82%.
Report is 4 commits behind head on develop.

❗ Current head 8d17609 differs from pull request most recent head 0a2b008. Consider uploading reports for the commit 0a2b008 to get more accurate results

Additional details and impacted files

@@             Coverage Diff             @@
##           develop    #1378      +/-   ##
===========================================
- Coverage    91.18%   90.82%   -0.37%     
===========================================
  Files          600      600              
  Lines        50695    50716      +21     
===========================================
- Hits         46228    46062     -166     
- Misses        4467     4654     +187

Files Changed	Coverage Δ
common/unified/matrix/dense_kernels.template.cpp	`100.00% <ø> (ø)`

... and 6 files with indirect coverage changes

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upsj · 2023-08-01T09:09:23Z

To put some number on these changes: time ninja ginkgo gives the following output (256 threads)


rocm45 before
real    2m44.885s
user    34m59.771s
sys     10m28.850s

rocm45 after
real    1m48.505s
user    18m8.664s
sys     2m23.337s

rocm502 before
real    3m55.766s
user    19m59.029s
sys     2m21.003s

rocm502 after
real    2m37.208s
user    49m14.886s
sys     11m57.626s

NVHPC23 before
real    4m24.576s
user    119m53.211s
sys     24m25.492s

NVHPC23 after
real    3m22.483s
user    8m36.878s
sys     2m18.913s

CMakeLists.txt

yhmtsai

LGTM. some nit and wrong variable

CMakeLists.txt

cmake/template_instantiation.cmake

yhmtsai · 2023-08-01T14:21:46Z

cmake/template_instantiation.cmake

+    file(READ "${source_path}" file_contents)
+    # escape semicolons and use them for line separation
+    string(REPLACE ";" "<semicolon>" file_contents "${file_contents}")
+    string(REGEX REPLACE "[\r\n]" ";" file_contents "${file_contents}")


From \r\n settings in windows, it will turn to \n\n in the resulting file, right?
just a note. I do not think it is important to adapt it.

that depends on how git checks out the files, but essentially yes.

yhmtsai · 2023-08-01T14:31:52Z

cmake/template_instantiation.cmake

+function(add_instantiation_files source_dir source_file output_files_var)
+    # read full file into variable
+    set(source_path "${source_dir}/${source_file}")
+    file(READ "${source_path}" file_contents)


if the \r\n is not critical, you can also use file(STRINGS ...) which ignores \r

~~It seems like STRINGS does not properly escape semicolons, thus we lose them in the output.~~ Escaped semicolons don't play nice with string(REPLACE, so I need to handle the escaping myself.

yhmtsai · 2023-08-01T14:39:12Z

cmake/template_instantiation.cmake

+        file(WRITE "${target_path}.tmp" "${content}")
+        add_custom_command(
+            OUTPUT "${target_path}"
+            COMMAND ${CMAKE_COMMAND} -E copy "${target_path}.tmp" "${target_path}"


Suggested change

COMMAND ${CMAKE_COMMAND} -E copy "${target_path}.tmp" "${target_path}"

COMMAND ${CMAKE_COMMAND} -E copy_if_different "${target_path}.tmp" "${target_path}"

reduce a little more.

I think since checking for build updates usually relies on the timestamp of the two files, it may actually be necessary to write to target_path to make sure the copy command isn't executed every time we call ninja.

I think it still do the same thing if you keep the main_dependecy.

I figure out it does not change anything.
although the source file is not change, it still compiles the codes due to changed header.
Thus, it does not reduce the compilation work unless the compiler can know the all corresponding components of the instantiation part are not changed.

So my understanding of the dependencies is as follows:

changing the .instantiate.cpp file causes both cmake to be called (which leads to the .tmp files being regenerated) as well as the .instantiate.*.cpp files to be regenerated by copying them from the .tmp files.

changing the .template.cpp files causes all .instantiate.*.cpp files to be recompiled

calling cmake does not cause recompilation, because changes to the .tmp files do not lead to the .instantiate.*.cpp files being recompiled.

Does this match your understanding of the code?

yhmtsai · 2023-08-01T14:40:44Z

common/CMakeLists.txt

-list(TRANSFORM UNIFIED_SOURCES PREPEND ${CMAKE_CURRENT_SOURCE_DIR}/unified/)
-set(GKO_UNIFIED_COMMON_SOURCES ${UNIFIED_SOURCES} PARENT_SCOPE)
+add_subdirectory(unified)
+set(GKO_UNIFIED_COMMON_SOURCES ${GKO_UNIFIED_COMMON_SOURCES} PARENT_SCOPE)


do you need to set that to PARENT_SCOPE again? it is set in the common/unified/CMakeLists.txt

yes, we need to propagate it up two levels. BTW, this change is not strictly necessary, I removed the code that required it.

common/unified/CMakeLists.txt

yhmtsai · 2023-08-01T14:42:56Z

cuda/CMakeLists.txt

+# we don't split up the dense kernels into distinct compilations
+list(APPEND GKO_UNIFIED_COMMON_SOURCES ${PROJECT_SOURCE_DIR}/common/unified/matrix/dense_kernels.instantiate.cpp)


the flexibility of tuning on/off is nice. I wonder whether it affects the dpcpp per_source situation.

you mean the size of the binaries?

dpcpp/CMakeLists.txt

dev_tools/scripts/config

MarcelKoch

Thanks for working on this. Anything that brings down compile time is appreciated. Since the comment came up, maybe it makes sense to add a CMake option to disable the splitting completely.

cmake/template_instantiation.cmake

MarcelKoch · 2023-08-02T07:13:58Z

cmake/template_instantiation.cmake

@@ -0,0 +1,68 @@
+function(add_instantiation_files source_dir source_file output_files_var)


maybe instead of an output variable, we could pass in the target the sources should be added to. Then we would not need to add them manually.

That wouldn't be sufficient for HIP and CUDA, where we need to set some properties on the files on top of adding them to a target.

What do you mean by that? At least I can't find another place where the output variable is used except for target_sources.

ginkgo/cuda/CMakeLists.txt

Line 60 in dbd43cf

set_source_files_properties(${source_file} PROPERTIES LANGUAGE CUDA)

ginkgo/hip/CMakeLists.txt

Line 94 in dbd43cf

set_source_files_properties(${GINKGO_HIP_SOURCES} PROPERTIES HIP_SOURCE_PROPERTY_FORMAT TRUE)

At least for cuda the new sources are not part of that, so it would work for those. But you are right, until we update the hip cmake set-up it won't work for hip.

Good point on CUDA, the files already have the .cu extension. It will also be necessary afterwards, because HIP doesn't have a dedicated file extension afaik, so we always need to set a property on all source files.

I guess we could get the files from the target's SOURCES property. But maybe that is not worth the trouble.

Yes, with native HIP support we could consider it

- remove unused variables - warn on incorrect instantiation file format - allow disabling the template split - simpler format_header config entries Co-authored-by: Yuhsiang M. Tsai <yhmtsai@gmail.com> Co-authored-by: Marcel Koch <marcel.koch@kit.edu>

upsj · 2023-08-02T08:39:53Z

I added a switch to enable and disable the split: GINKGO_SPLIT_TEMPLATE_INSTANTIATIONS

MarcelKoch · 2023-08-02T08:59:41Z

@upsj could you mark the variable as advanced? Somehow, the change is not displayed in the file changed tab...

sonarqubecloud · 2023-08-02T20:03:43Z

SonarCloud Quality Gate failed.

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0 Vulnerabilities
0 Security Hotspots
72 Code Smells

58.0% Coverage
37.3% Duplication

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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

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

upsj added the 1:ST:ready-for-review This PR is ready for review label Jul 31, 2023

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upsj force-pushed the tmp_split_large_files_automatically branch from c2a0c0a to ee21178 Compare July 31, 2023 21:05

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Split compilation of dense kernels #1375

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upsj and others added 6 commits August 2, 2023 10:01

messy approach to splitting up files

f27f840

clean up dependency structure

579f016

split CUDA and HIP (fb)csr_kernels compilation

e830d89

improve formatting

81e6657

fix typos

8c8b9c1

review updates

1db51cc

- remove unused variables - warn on incorrect instantiation file format - allow disabling the template split - simpler format_header config entries Co-authored-by: Yuhsiang M. Tsai <yhmtsai@gmail.com> Co-authored-by: Marcel Koch <marcel.koch@kit.edu>

upsj force-pushed the tmp_split_large_files_automatically branch from 8d17609 to 1db51cc Compare August 2, 2023 08:31

upsj 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 1:ST:run-full-test labels Aug 2, 2023

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0a2b008

upsj merged commit afd52ea into develop Aug 2, 2023

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Split compilation of large files automatically #1378

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	COMMAND ${CMAKE_COMMAND} -E copy "${target_path}.tmp" "${target_path}"
	COMMAND ${CMAKE_COMMAND} -E copy_if_different "${target_path}.tmp" "${target_path}"

		# we don't split up the dense kernels into distinct compilations
		list(APPEND GKO_UNIFIED_COMMON_SOURCES ${PROJECT_SOURCE_DIR}/common/unified/matrix/dense_kernels.instantiate.cpp)

		@@ -0,0 +1,68 @@
		function(add_instantiation_files source_dir source_file output_files_var)

Split compilation of large files automatically #1378

Split compilation of large files automatically #1378

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upsj Aug 2, 2023 •

edited

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