Comments (4)
Hi,
We have some initial support for Nvidia GPUs, using cuBLAS/cuSOLVER and SLATE for one of the solver algorithms (for the direct solver, not for the preconditioners or the iterative solvers).
In an older branch, we also used MAGMA (instead of cuBLAS/cuSOLVER), because they provide variable sized batched GEMM.
There are currently no CUDA kernels in the code, since we can get most of the performance from BLAS/LAPACK.
However, I'm planning to add a few small CUDA kernels to avoid CPU<->GPU data movement, which would also make it easier to remove our use of CUDA managed memory (cudaMallocManaged). That will then make it easier to 'hipify' the code.
To test the current cuBLAS/cuSOLVER support, add
-DTPL_ENABLE_CUBLAS=ON -DCUDAToolkit_ROOT=/some/path
to your cmake command, and
-DTPL_ENABLE_SLATE=ON
for SLATE support for distributed memory (ScaLAPACK alternative).
I'd be happy to discuss more.
from strumpack.
Are you working on some application or are you thinking about RAJA?
from strumpack.
I was just thinking about it from a user point of view. If my application assembles a matrix how does the hand off to STRUMPACK work? For example, can I provide device pointers? or would it do the host-device copy for me?
from strumpack.
We don't have an interface that takes device pointers.
There are several steps in the algorithms that we cannot do on the GPU yet, such as reordering of the (sparse) matrix to reduce the fill-in during the factorization, or reordering for numerical stability, and the symbolic analysis phase. For the ordering we call external libraries such as METIS, Scotch and MC64.
from strumpack.
Related Issues (20)
- Fortran Interface for Finite Element nonlinear solver HOT 4
- Windows 10 support HOT 6
- Iterate Cluster Tree HOT 5
- mpi_type for std::pair leads to memory leaks HOT 3
- MSVC: Cannot convert from strumpack::EliminationTreeMPIDist<scalar_t,integer_t> *' to 'const strumpack::EliminationTree<scalar_t,integer_t> *' HOT 1
- Including ButterflyPACK HOT 2
- Segmentation fault during forward solve with CUDA HOT 4
- STRUMPACK with > 1 GPU per node HOT 11
- Crash with updated PETSc interface using version 7.1.3 HOT 2
- Does STRUMPACK support the 'long double' data type? HOT 1
- Symmetric support HOT 1
- Access elements in HODLRMatrix HOT 2
- Inconsistant diagonal entries for dense matrix and corresponding HODLR matrix HOT 7
- namespace "thrust" has no member "stable_sort_by_key" HOT 1
- Input matrix NAN in ComputeRange HOT 8
- HODLR OpenMP support HOT 1
- std::length_error', when total nonzeros is higher than maximum of integer4, Fortran use of STRUMPACK_MPIdist HOT 23
- HSSMatrix HSSMatrix log determinant HOT 2
- construct_partially_matrix_free for MPI HOT 2
- [error] Cmake based build with intel mkl library HOT 35
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from strumpack.