1. 09 Mar, 2020 1 commit
  2. 21 Feb, 2020 1 commit
  3. 19 Dec, 2019 3 commits
  4. 13 Dec, 2019 1 commit
  5. 10 Dec, 2019 3 commits
  6. 06 Dec, 2019 1 commit
  7. 04 Dec, 2019 3 commits
  8. 20 Nov, 2019 5 commits
    • Wenzhe Yu's avatar
      Use cuBLAS in multiply_a_b · 85782a1f
      Wenzhe Yu authored
      85782a1f
    • Wenzhe Yu's avatar
      GPU memory optimization in ELPA2 · af7bb4a0
      Wenzhe Yu authored
      * Removed redundant malloc, memset and memcpy
      * Use pinned host memory
      * Implemented blocking for GPU code path in step5
      * Removed unused code
      af7bb4a0
    • Wenzhe Yu's avatar
      Extend CUDA wrapper · 6e5c03a6
      Wenzhe Yu authored
      * cudaMallocHost
      * cudaFreeHost
      * cudaHostRegister
      * cudaHostUnregister
      6e5c03a6
    • Wenzhe Yu's avatar
      Rewrite compute_hh_trafo CUDA kernels · 6cd5a4f1
      Wenzhe Yu authored
      * Switch to a simple non-WY algorithm
      * Unify real and complex cases
      * Update reduction kernel
      * Use __shfl_xor_sync for warp reduce (CUDA 9+)
      * Support 2^n block size, n = 1,2,...,10
      * Use templates when possible
      * Clean up unused CUDA functions
      * Increase default stripe width when using GPU
      6cd5a4f1
    • Andreas Marek's avatar
      ELPA 2019.11.001.rc1 · 1afe1b76
      Andreas Marek authored
      1afe1b76
  9. 14 Nov, 2019 1 commit
  10. 11 Nov, 2019 1 commit
  11. 08 Nov, 2019 1 commit
  12. 05 Nov, 2019 1 commit
  13. 04 Nov, 2019 2 commits
  14. 31 Oct, 2019 1 commit
  15. 30 Oct, 2019 3 commits
  16. 29 Oct, 2019 1 commit
  17. 28 Oct, 2019 2 commits
    • Andreas Marek's avatar
      Merge branch 'master_pre_stage' into skew · cfa307bb
      Andreas Marek authored
      cfa307bb
    • Pavel Kus's avatar
      partially addressing issues with the GPU kernel · ec5b3bec
      Pavel Kus authored
      This commit addresses several issues. It essentially forbids the use of
      the GPU kernel, which become obsolete and caused problems. But it
      does not complete remove the related code, nor does it forbid from
      explicitly selecting the GPU kernel. However, if the user does select
      it, the warning will be issued and the GENERIC kernel would be used
      instead. In the more details:
      * Commentin out operations in the GPU kernel, which do not compile with
        CUDA 10.1. This makes the kernel deffinitely not ussable (but it was
        true even before)
      * removing the gpu_tridiag_band option, sincie the tridiag->banded routine
        is actually not ported to GPU at all. This step will thus always be
        run on the CPU
      * removing the gpu_trans_ev_tridi_to_band option, since the GPU version
        of this step cannot run without the GPU kernel and it is not usable.
        This step will thus also be performed on the CPU
      * modifying REAL_GPU_KERNEL_ONLY_WHEN_GPU_IS_ACTIVE and
        COMPLEX_GPU_KERNEL_ONLY_WHEN_GPU_IS_ACTIVE such that the GPU kernel is
        not considered during the autotuning
      
      * TODO however, the GPU kernel can still be enforced by the user. In
        this case, during the calculation, a warning is issued and the kernel
        is switched to the GENERIC one. This should be improved and there
        should not even be the possibility to choose the GPU kernel at the
        begining.
      ec5b3bec
  18. 26 Oct, 2019 2 commits
  19. 25 Oct, 2019 1 commit
  20. 24 Oct, 2019 6 commits