Add new Intel CI support #736

tcojean · 2021-04-07T14:43:30Z

Make DPC++ tests work with the new system.

The new Intel CI system adds two new checks: the integrated and discrete GPU.
Some changes to the DPC++ tests are required:

Make the DPCPP executor tests work with GPUs.
Allow compiling and running the DPC++ tests for float only (double is not supported in either GPU).

yhmtsai · 2021-04-07T16:48:52Z

short comment:
when enabling DPCPP_SINGLE_MODE, it will also remove the double related kernels of omp/reference.
Maybe dpcpp always uses DPCPP_related_arg? we can still have double support on the other module

tcojean · 2021-04-07T16:53:19Z

No it does not, double is properly ran for omp/reference. Note that this works when passing
target_compile_definitions(target PRIVATE GINKGO_DPCPP_SINGLE_MODE=1). This is done only:

For the Dpcpp module (target ginkgo_dpcpp)
ginkgo_create_test which are part of the dpcpp folder or tests made using ginkgo_create_dpcpp_test.

yhmtsai · 2021-04-07T16:57:56Z

@tcojean thanks for explanation. You are right, it only affect the DPCPP part.
I do not need the part for changing the macro of script now.

yhmtsai

LGTM in general. some concerns are in the comments

.gitlab-ci.yml

dpcpp/CMakeLists.txt

dpcpp/test/base/executor.dp.cpp

upsj

LGTM! The DPCPP_SINGLE_MODE integration is surprisingly smooth, I like it!

tcojean · 2021-04-12T15:57:48Z

format!

codecov · 2021-04-12T21:40:28Z

Codecov Report

Merging #736 (6ba02a6) into develop (59202f1) will decrease coverage by 0.00%.
The diff coverage is 100.00%.

❗ Current head 6ba02a6 differs from pull request most recent head ceb124a. Consider uploading reports for the commit ceb124a to get more accurate results

@@             Coverage Diff             @@
##           develop     #736      +/-   ##
===========================================
- Coverage    92.78%   92.78%   -0.01%     
===========================================
  Files          392      392              
  Lines        30514    30514              
===========================================
- Hits         28312    28311       -1     
- Misses        2202     2203       +1

Impacted Files	Coverage Δ
core/test/multigrid/amgx_pgm.cpp	`84.61% <ø> (ø)`
core/test/solver/cb_gmres.cpp	`99.02% <ø> (ø)`
core/test/solver/idr.cpp	`98.05% <ø> (ø)`
core/test/utils.hpp	`100.00% <ø> (ø)`
include/ginkgo/core/base/math.hpp	`100.00% <ø> (ø)`
include/ginkgo/core/base/types.hpp	`92.59% <ø> (ø)`
reference/test/solver/cb_gmres_kernels.cpp	`99.06% <ø> (ø)`
reference/test/solver/idr_kernels.cpp	`98.17% <ø> (ø)`
core/test/log/logger.cpp	`100.00% <100.00%> (ø)`
omp/reorder/rcm_kernels.cpp	`97.53% <0.00%> (-0.61%)`	⬇️

Continue to review full report at Codecov.

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CMakeLists.txt

tcojean · 2021-04-28T17:55:14Z

This is now fully working and ready for review again. It also fixes a few bugs in the CMake setup.

yhmtsai

LGTM

.gitlab/image.yml

yhmtsai · 2021-04-29T12:18:45Z

dpcpp/CMakeLists.txt

 set(GINKGO_DPCPP_FLAGS ${GINKGO_DPCPP_FLAGS} PARENT_SCOPE)
 target_compile_options(ginkgo_dpcpp PRIVATE "${GINKGO_DPCPP_FLAGS}")
 target_compile_features(ginkgo_dpcpp PRIVATE cxx_std_17)
+target_link_options(ginkgo_dpcpp PRIVATE -fsycl-device-lib=all)
+target_link_options(ginkgo_dpcpp PRIVATE -fsycl-device-code-split=per_kernel)


Yes, It should need more changes. the current version is enough for our usage.
AOT may be helpful to detect error for those devices we do not have or eliminate the JIT time in the future

yhmtsai · 2021-04-29T12:27:11Z

hip/CMakeLists.txt

@@ -1,5 +1,5 @@
 if (GINKGO_HIP_PLATFORM MATCHES "${HIP_PLATFORM_NVIDIA_REGEX}"
-    AND CMAKE_CUDA_COMPILER_VERSION VERSION_LESS 9.2)
+    AND GINKGO_BUILD_CUDA AND CMAKE_CUDA_COMPILER_VERSION VERSION_LESS 9.2)


could we have method to check nvcc version from hip? it will skip the check when disabling the GINKGO_BUILD_CUDA

In that case, we already do that:
find_package(CUDA 9.2 REQUIRED)

yhmtsai · 2021-04-29T12:38:40Z

include/ginkgo/core/base/math.hpp

-    // FIXME: This implementation is due to a DPC++ issue:
-    // plain `sqrt` call evaluates to `std::sqrt` which fails on GPUs
-    return cl::sycl::sqrt(squared_norm(x));
-#else
    return sqrt(squared_norm(x));


I am not sure absolute array will call this or not due to namespace issue from dpcpp (sycl).
Also, if the sqrt is not the std::sqrt from kernels::dpcpp, it will give type error.
I write the above only as note because absolute_array test seems to be passed correctly

Yes that's a good point, my expectation is now things are fixed and the sqrt is actually the std::sqrt we specified above. If you have any issue in practice it's good to keep in mind that this may have to change.

Co-authored-by: Yuhsiang Tsai <yhmtsai@gmail.com>

tcojean · 2021-04-30T09:30:35Z

The recent logger merge is creating a lot of failures everywhere, I will try to fix this.

+ Make HIP on CUDA platform not do the CMAKE_CUDA_COMPILER_VERSION check. + Fix an important bug affecting the CMAKE_REQUIRED_LIBRARIES management of build_type_helpers.cmake. Co-authored-by: Yuhsiang Tsai <yhmtsai@gmail.com> Co-authored-by: Tobias Ribizel <ribizel@kit.edu>

tcojean · 2021-04-30T11:03:45Z

format!

include/ginkgo/core/log/logger.hpp

Co-authored-by: Terry Cojean <tcojean@users.noreply.github.com>

sonarcloud · 2021-05-01T21:54:33Z

Kudos, SonarCloud Quality Gate passed!

0 Bugs
0 Vulnerabilities
0 Security Hotspots
0 Code Smells

No Coverage information
No Duplication information

Ginkgo release 1.4.0 The Ginkgo team is proud to announce the new Ginkgo minor release 1.4.0. This release brings most of the Ginkgo functionality to the Intel DPC++ ecosystem which enables Intel-GPU and CPU execution. The only Ginkgo features which have not been ported yet are some preconditioners. Ginkgo's mixed-precision support is greatly enhanced thanks to: 1. The new Accessor concept, which allows writing kernels featuring on-the-fly memory compression, among other features. The accessor can be used as header-only, see the [accessor BLAS benchmarks repository](https://github.com/ginkgo-project/accessor-BLAS/tree/develop) as a usage example. 2. All LinOps now transparently support mixed-precision execution. By default, this is done through a temporary copy which may have a performance impact but already allows mixed-precision research. Native mixed-precision ELL kernels are implemented which do not see this cost. The accessor is also leveraged in a new CB-GMRES solver which allows for performance improvements by compressing the Krylov basis vectors. Many other features have been added to Ginkgo, such as reordering support, a new IDR solver, Incomplete Cholesky preconditioner, matrix assembly support (only CPU for now), machine topology information, and more! Supported systems and requirements: + For all platforms, cmake 3.13+ + C++14 compliant compiler + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, all versions after 8.1+ + clang: 3.9+ + Intel compiler: 2018+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + HIP module: ROCm 3.5+ + DPC++ module: Intel OneAPI 2021.3. Set the CXX compiler to `dpcpp`. + Windows + MinGW and Cygwin: gcc 5.3+, 6.3+, 7.3+, all versions after 8.1+ + Microsoft Visual Studio: VS 2019 + CUDA module: CUDA 9.0+, Microsoft Visual Studio + OpenMP module: MinGW or Cygwin. Algorithm and important feature additions: + Add a new DPC++ Executor for SYCL execution and other base utilities [#648](#648), [#661](#661), [#757](#757), [#832](#832) + Port matrix formats, solvers and related kernels to DPC++. For some kernels, also make use of a shared kernel implementation for all executors (except Reference). [#710](#710), [#799](#799), [#779](#779), [#733](#733), [#844](#844), [#843](#843), [#789](#789), [#845](#845), [#849](#849), [#855](#855), [#856](#856) + Add accessors which allow multi-precision kernels, among other things. [#643](#643), [#708](#708) + Add support for mixed precision operations through apply in all LinOps. [#677](#677) + Add incomplete Cholesky factorizations and preconditioners as well as some improvements to ILU. [#672](#672), [#837](#837), [#846](#846) + Add an AMGX implementation and kernels on all devices but DPC++. [#528](#528), [#695](#695), [#860](#860) + Add a new mixed-precision capability solver, Compressed Basis GMRES (CB-GMRES). [#693](#693), [#763](#763) + Add the IDR(s) solver. [#620](#620) + Add a new fixed-size block CSR matrix format (for the Reference executor). [#671](#671), [#730](#730) + Add native mixed-precision support to the ELL format. [#717](#717), [#780](#780) + Add Reverse Cuthill-McKee reordering [#500](#500), [#649](#649) + Add matrix assembly support on CPUs. [#644](#644) + Extends ISAI from triangular to general and spd matrices. [#690](#690) Other additions: + Add the possibility to apply real matrices to complex vectors. [#655](#655), [#658](#658) + Add functions to compute the absolute of a matrix format. [#636](#636) + Add symmetric permutation and improve existing permutations. [#684](#684), [#657](#657), [#663](#663) + Add a MachineTopology class with HWLOC support [#554](#554), [#697](#697) + Add an implicit residual norm criterion. [#702](#702), [#818](#818), [#850](#850) + Row-major accessor is generalized to more than 2 dimensions and a new "block column-major" accessor has been added. [#707](#707) + Add an heat equation example. [#698](#698), [#706](#706) + Add ccache support in CMake and CI. [#725](#725), [#739](#739) + Allow tuning and benchmarking variables non intrusively. [#692](#692) + Add triangular solver benchmark [#664](#664) + Add benchmarks for BLAS operations [#772](#772), [#829](#829) + Add support for different precisions and consistent index types in benchmarks. [#675](#675), [#828](#828) + Add a Github bot system to facilitate development and PR management. [#667](#667), [#674](#674), [#689](#689), [#853](#853) + Add Intel (DPC++) CI support and enable CI on HPC systems. [#736](#736), [#751](#751), [#781](#781) + Add ssh debugging for Github Actions CI. [#749](#749) + Add pipeline segmentation for better CI speed. [#737](#737) Changes: + Add a Scalar Jacobi specialization and kernels. [#808](#808), [#834](#834), [#854](#854) + Add implicit residual log for solvers and benchmarks. [#714](#714) + Change handling of the conjugate in the dense dot product. [#755](#755) + Improved Dense stride handling. [#774](#774) + Multiple improvements to the OpenMP kernels performance, including COO, an exclusive prefix sum, and more. [#703](#703), [#765](#765), [#740](#740) + Allow specialization of submatrix and other dense creation functions in solvers. [#718](#718) + Improved Identity constructor and treatment of rectangular matrices. [#646](#646) + Allow CUDA/HIP executors to select allocation mode. [#758](#758) + Check if executors share the same memory. [#670](#670) + Improve test install and smoke testing support. [#721](#721) + Update the JOSS paper citation and add publications in the documentation. [#629](#629), [#724](#724) + Improve the version output. [#806](#806) + Add some utilities for dim and span. [#821](#821) + Improved solver and preconditioner benchmarks. [#660](#660) + Improve benchmark timing and output. [#669](#669), [#791](#791), [#801](#801), [#812](#812) Fixes: + Sorting fix for the Jacobi preconditioner. [#659](#659) + Also log the first residual norm in CGS [#735](#735) + Fix BiCG and HIP CSR to work with complex matrices. [#651](#651) + Fix Coo SpMV on strided vectors. [#807](#807) + Fix segfault of extract_diagonal, add short-and-fat test. [#769](#769) + Fix device_reset issue by moving counter/mutex to device. [#810](#810) + Fix `EnableLogging` superclass. [#841](#841) + Support ROCm 4.1.x and breaking HIP_PLATFORM changes. [#726](#726) + Decreased test size for a few device tests. [#742](#742) + Fix multiple issues with our CMake HIP and RPATH setup. [#712](#712), [#745](#745), [#709](#709) + Cleanup our CMake installation step. [#713](#713) + Various simplification and fixes to the Windows CMake setup. [#720](#720), [#785](#785) + Simplify third-party integration. [#786](#786) + Improve Ginkgo device arch flags management. [#696](#696) + Other fixes and improvements to the CMake setup. [#685](#685), [#792](#792), [#705](#705), [#836](#836) + Clarification of dense norm documentation [#784](#784) + Various development tools fixes and improvements [#738](#738), [#830](#830), [#840](#840) + Make multiple operators/constructors explicit. [#650](#650), [#761](#761) + Fix some issues, memory leaks and warnings found by MSVC. [#666](#666), [#731](#731) + Improved solver memory estimates and consistent iteration counts [#691](#691) + Various logger improvements and fixes [#728](#728), [#743](#743), [#754](#754) + Fix for ForwardIterator requirements in iterator_factory. [#665](#665) + Various benchmark fixes. [#647](#647), [#673](#673), [#722](#722) + Various CI fixes and improvements. [#642](#642), [#641](#641), [#795](#795), [#783](#783), [#793](#793), [#852](#852) Related PR: #857

Release 1.4.0 to master The Ginkgo team is proud to announce the new Ginkgo minor release 1.4.0. This release brings most of the Ginkgo functionality to the Intel DPC++ ecosystem which enables Intel-GPU and CPU execution. The only Ginkgo features which have not been ported yet are some preconditioners. Ginkgo's mixed-precision support is greatly enhanced thanks to: 1. The new Accessor concept, which allows writing kernels featuring on-the-fly memory compression, among other features. The accessor can be used as header-only, see the [accessor BLAS benchmarks repository](https://github.com/ginkgo-project/accessor-BLAS/tree/develop) as a usage example. 2. All LinOps now transparently support mixed-precision execution. By default, this is done through a temporary copy which may have a performance impact but already allows mixed-precision research. Native mixed-precision ELL kernels are implemented which do not see this cost. The accessor is also leveraged in a new CB-GMRES solver which allows for performance improvements by compressing the Krylov basis vectors. Many other features have been added to Ginkgo, such as reordering support, a new IDR solver, Incomplete Cholesky preconditioner, matrix assembly support (only CPU for now), machine topology information, and more! Supported systems and requirements: + For all platforms, cmake 3.13+ + C++14 compliant compiler + Linux and MacOS + gcc: 5.3+, 6.3+, 7.3+, all versions after 8.1+ + clang: 3.9+ + Intel compiler: 2018+ + Apple LLVM: 8.0+ + CUDA module: CUDA 9.0+ + HIP module: ROCm 3.5+ + DPC++ module: Intel OneAPI 2021.3. Set the CXX compiler to `dpcpp`. + Windows + MinGW and Cygwin: gcc 5.3+, 6.3+, 7.3+, all versions after 8.1+ + Microsoft Visual Studio: VS 2019 + CUDA module: CUDA 9.0+, Microsoft Visual Studio + OpenMP module: MinGW or Cygwin. Algorithm and important feature additions: + Add a new DPC++ Executor for SYCL execution and other base utilities [#648](#648), [#661](#661), [#757](#757), [#832](#832) + Port matrix formats, solvers and related kernels to DPC++. For some kernels, also make use of a shared kernel implementation for all executors (except Reference). [#710](#710), [#799](#799), [#779](#779), [#733](#733), [#844](#844), [#843](#843), [#789](#789), [#845](#845), [#849](#849), [#855](#855), [#856](#856) + Add accessors which allow multi-precision kernels, among other things. [#643](#643), [#708](#708) + Add support for mixed precision operations through apply in all LinOps. [#677](#677) + Add incomplete Cholesky factorizations and preconditioners as well as some improvements to ILU. [#672](#672), [#837](#837), [#846](#846) + Add an AMGX implementation and kernels on all devices but DPC++. [#528](#528), [#695](#695), [#860](#860) + Add a new mixed-precision capability solver, Compressed Basis GMRES (CB-GMRES). [#693](#693), [#763](#763) + Add the IDR(s) solver. [#620](#620) + Add a new fixed-size block CSR matrix format (for the Reference executor). [#671](#671), [#730](#730) + Add native mixed-precision support to the ELL format. [#717](#717), [#780](#780) + Add Reverse Cuthill-McKee reordering [#500](#500), [#649](#649) + Add matrix assembly support on CPUs. [#644](#644) + Extends ISAI from triangular to general and spd matrices. [#690](#690) Other additions: + Add the possibility to apply real matrices to complex vectors. [#655](#655), [#658](#658) + Add functions to compute the absolute of a matrix format. [#636](#636) + Add symmetric permutation and improve existing permutations. [#684](#684), [#657](#657), [#663](#663) + Add a MachineTopology class with HWLOC support [#554](#554), [#697](#697) + Add an implicit residual norm criterion. [#702](#702), [#818](#818), [#850](#850) + Row-major accessor is generalized to more than 2 dimensions and a new "block column-major" accessor has been added. [#707](#707) + Add an heat equation example. [#698](#698), [#706](#706) + Add ccache support in CMake and CI. [#725](#725), [#739](#739) + Allow tuning and benchmarking variables non intrusively. [#692](#692) + Add triangular solver benchmark [#664](#664) + Add benchmarks for BLAS operations [#772](#772), [#829](#829) + Add support for different precisions and consistent index types in benchmarks. [#675](#675), [#828](#828) + Add a Github bot system to facilitate development and PR management. [#667](#667), [#674](#674), [#689](#689), [#853](#853) + Add Intel (DPC++) CI support and enable CI on HPC systems. [#736](#736), [#751](#751), [#781](#781) + Add ssh debugging for Github Actions CI. [#749](#749) + Add pipeline segmentation for better CI speed. [#737](#737) Changes: + Add a Scalar Jacobi specialization and kernels. [#808](#808), [#834](#834), [#854](#854) + Add implicit residual log for solvers and benchmarks. [#714](#714) + Change handling of the conjugate in the dense dot product. [#755](#755) + Improved Dense stride handling. [#774](#774) + Multiple improvements to the OpenMP kernels performance, including COO, an exclusive prefix sum, and more. [#703](#703), [#765](#765), [#740](#740) + Allow specialization of submatrix and other dense creation functions in solvers. [#718](#718) + Improved Identity constructor and treatment of rectangular matrices. [#646](#646) + Allow CUDA/HIP executors to select allocation mode. [#758](#758) + Check if executors share the same memory. [#670](#670) + Improve test install and smoke testing support. [#721](#721) + Update the JOSS paper citation and add publications in the documentation. [#629](#629), [#724](#724) + Improve the version output. [#806](#806) + Add some utilities for dim and span. [#821](#821) + Improved solver and preconditioner benchmarks. [#660](#660) + Improve benchmark timing and output. [#669](#669), [#791](#791), [#801](#801), [#812](#812) Fixes: + Sorting fix for the Jacobi preconditioner. [#659](#659) + Also log the first residual norm in CGS [#735](#735) + Fix BiCG and HIP CSR to work with complex matrices. [#651](#651) + Fix Coo SpMV on strided vectors. [#807](#807) + Fix segfault of extract_diagonal, add short-and-fat test. [#769](#769) + Fix device_reset issue by moving counter/mutex to device. [#810](#810) + Fix `EnableLogging` superclass. [#841](#841) + Support ROCm 4.1.x and breaking HIP_PLATFORM changes. [#726](#726) + Decreased test size for a few device tests. [#742](#742) + Fix multiple issues with our CMake HIP and RPATH setup. [#712](#712), [#745](#745), [#709](#709) + Cleanup our CMake installation step. [#713](#713) + Various simplification and fixes to the Windows CMake setup. [#720](#720), [#785](#785) + Simplify third-party integration. [#786](#786) + Improve Ginkgo device arch flags management. [#696](#696) + Other fixes and improvements to the CMake setup. [#685](#685), [#792](#792), [#705](#705), [#836](#836) + Clarification of dense norm documentation [#784](#784) + Various development tools fixes and improvements [#738](#738), [#830](#830), [#840](#840) + Make multiple operators/constructors explicit. [#650](#650), [#761](#761) + Fix some issues, memory leaks and warnings found by MSVC. [#666](#666), [#731](#731) + Improved solver memory estimates and consistent iteration counts [#691](#691) + Various logger improvements and fixes [#728](#728), [#743](#743), [#754](#754) + Fix for ForwardIterator requirements in iterator_factory. [#665](#665) + Various benchmark fixes. [#647](#647), [#673](#673), [#722](#722) + Various CI fixes and improvements. [#642](#642), [#641](#641), [#795](#795), [#783](#783), [#793](#793), [#852](#852) Related PR: #866

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Add CCACHE support in CI #739

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Run the CUDA jobs on the CI controllers. #751

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tcojean and others added 2 commits April 29, 2021 18:51

Make DPC++ tests work with the new system.

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Review update.

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Co-authored-by: Yuhsiang Tsai <yhmtsai@gmail.com>

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Use CMake property LOCATION for the HIP fallback.

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Fix bugs with logger and conj_dot.

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Co-authored-by: Terry Cojean <tcojean@users.noreply.github.com>

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