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add hip unsafe atomic option #1091

Merged
merged 3 commits into from
Aug 19, 2022
Merged

add hip unsafe atomic option #1091

merged 3 commits into from
Aug 19, 2022

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yhmtsai
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@yhmtsai yhmtsai commented Aug 15, 2022

AMD introduced the unsafe-fp-atomics options to make atomicAdd faster.
unsafe atomicAdd is correct when the memory is on coarse grain.
hipMalloc always allocates memory on coarse grain, so we can use it by default.
although unsafe-fp-atomics should be added in clang-12, it is not always true when hip uses clang on their own repo.
llvm: llvm/llvm-project@6054a45
amd llvm: ROCm/llvm-project@189310a
but amd shows the rocm >= 5 should use the llvm with unsafe atomic support.

Another note: only 5.2 requires compiler to use unsafe, but the rocm < 5.2 only suggests compiler such that it may not really use unsafe.

@yhmtsai yhmtsai added the 1:ST:ready-for-review This PR is ready for review label Aug 15, 2022
@yhmtsai yhmtsai requested review from a team August 15, 2022 17:58
@yhmtsai yhmtsai self-assigned this Aug 15, 2022
@ginkgo-bot ginkgo-bot added mod:cuda This is related to the CUDA module. mod:hip This is related to the HIP module. reg:build This is related to the build system. labels Aug 15, 2022
upsj
upsj approved these changes Aug 15, 2022
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common/cuda_hip/components/atomic.hpp.inc Outdated
Comment on lines 150 to 160
#if defined(__HIPCC__) && defined(__HIP_DEVICE_COMPILE__) && \
GINKGO_HIP_PLATFORM_HCC


// the double atomicAdd is added after 4.3
GKO_BIND_ATOMIC_ADD(double);


#endif // defined(__HIPCC__) && defined(__HIP_DEVICE_COMPILE__) &&
// GINKGO_HIP_PLATFORM_HCC

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Can we merge this with the CUDA condition, so we have only a single place where we control access to double atomics?

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@yhmtsai yhmtsai Aug 18, 2022 •
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yes in practice with considering __HIP_DEVICE_COMPILE__ is always true in atomic_add.hpp.inc when compiled by HIPCC.
otherwise, it will not reduce the condition.

cmake/hip.cmake Outdated
set(GINKGO_HIPCC_OPTIONS ${GINKGO_HIP_COMPILER_FLAGS} "-std=c++14 -DGKO_COMPILING_HIP")
set(GINKGO_HIP_NVCC_OPTIONS ${GINKGO_HIP_NVCC_COMPILER_FLAGS} ${GINKGO_HIP_NVCC_ARCH} ${GINKGO_HIP_NVCC_ADDITIONAL_FLAGS})
set(GINKGO_HIP_CLANG_OPTIONS ${GINKGO_HIP_CLANG_COMPILER_FLAGS} ${GINKGO_AMD_ARCH_FLAGS})
if(GINKGO_HIP_AMD_UNSAFE_ATOMIC AND HIP_VERSION VERSION_GREATER_EQUAL 5)
set(GINKGO_HIP_CLANG_OPTIONS ${GINKGO_HIP_CLANG_OPTIONS} "-munsafe-fp-atomics")
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nit: indentation + CMake stuff

Suggested change
set(GINKGO_HIP_CLANG_OPTIONS ${GINKGO_HIP_CLANG_OPTIONS} "-munsafe-fp-atomics")
list(APPEND GINKGO_HIP_CLANG_OPTIONS -munsafe-fp-atomics)

CMakeLists.txt
@@ -67,6 +67,7 @@ set(GINKGO_CUDA_COMPILER_FLAGS "" CACHE STRING
set(GINKGO_CUDA_ARCHITECTURES "Auto" CACHE STRING
"A list of target NVIDIA GPU achitectures. See README.md for more detail.")
option(GINKGO_CUDA_DEFAULT_HOST_COMPILER "Tell Ginkgo to not automatically set the CUDA host compiler" OFF)
option(GINKGO_HIP_AMD_UNSAFE_ATOMIC "Compiler uses unsafe floating point atomic (only for AMD GPU and ROCM >= 5). Default is ON because we use hipMalloc, which is always on coarse grain. Must turn off when allocating memory on fine grain" ON)
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We are lacking an explanation what coarse grain and fine grain allocations are somewhere in the documentation. Are those the terms AMD uses somewhere? Maybe link to that

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So basically hipMalloc is fine, only hipMallocHost causes issues? We don't use it, so that's fine :) I think the documentation should mainly refer to the consequences of this choice.

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yes, I add the ref in the comment

tcojean
tcojean approved these changes Aug 17, 2022
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LGTM. I'm curious about documentation on these unsafe atomic and "fine-grained" vs "coarse-grained" memory allocations, because I could not easily find something clear on that topic.

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yhmtsai commented Aug 17, 2022

I only found the reference here.
https://docs.olcf.ornl.gov/systems/crusher_quick_start_guide.html#floating-point-fp-atomic-operations-and-coarse-fine-grained-memory-allocations

@yhmtsai yhmtsai 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 Aug 18, 2022
@yhmtsai yhmtsai merged commit 0da2b0c into develop Aug 19, 2022
@yhmtsai yhmtsai deleted the hip_unsafe_atomic branch August 19, 2022 19:20
@yhmtsai yhmtsai mentioned this pull request Nov 6, 2022
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tcojean added a commit that referenced this pull request Nov 12, 2022
@tcojean
Merge Release 1.5.0 to develop
7c9f530 
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))
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