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#### 4.2 GPU example

The code discussed here shows how to set up a program exploiting the combined GPU capabilities of PSBLAS and AMG4PSBLAS. The code example is available in the source distribution directory amg4psblas/examples/gpu.

First of all, we need to include the appropriate modules and declare some auxiliary variables:

    program amg_dexample_gpu
      use psb_base_mod
      use amg_prec_mod
      use psb_krylov_mod
      use psb_util_mod
      use psb_gpu_mod
      use data_input
      use amg_d_pde_mod
      implicit none
      .......
      ! GPU variables
      type(psb_d_hlg_sparse_mat) :: agmold
      type(psb_d_vect_gpu)       :: vgmold
      type(psb_i_vect_gpu)       :: igmold

Listing 5: setup of a GPU-enabled test program part one.

In this particular example we are choosing to employ a HLG data structure for sparse matrices on GPUs; for more information please refer to the PSBLAS-EXT users’ guide.

We then have to initialize the GPU environment, and pass the appropriate MOLD variables to the build methods (see also the PSBLAS and PSBLAS-EXT users’ guides).

      call psb_init(ctxt)
      call psb_info(ctxt,iam,np)
      !
      ! BEWARE: if you have NGPUS  per node, the default is to
      ! attach to mod(IAM,NGPUS)
      !
      call psb_gpu_init(ictxt)
      ......
      t1 = psb_wtime()
      call prec%smoothers_build(a,desc_a,info, amold=agmold, vmold=vgmold, imold=igmold)

Listing 6: setup of a GPU-enabled test program part two.

Finally, we convert the input matrix, the descriptor and the vectors to use a GPU-enabled internal storage format. We then preallocate the preconditioner workspace before entering the Krylov method. At the end of the code, we close the GPU environment

      call desc_a%cnv(mold=igmold)
      call a%cscnv(info,mold=agmold)
      call psb_geasb(x,desc_a,info,mold=vgmold)
      call psb_geasb(b,desc_a,info,mold=vgmold)
      !
      ! iterative method parameters
      !
      call psb_barrier(ctxt)
      call prec%allocate_wrk(info)
      t1 = psb_wtime()
      call psb_krylov(s_choice%kmethd,a,prec,b,x,s_choice%eps,&
           & desc_a,info,itmax=s_choice%itmax,iter=iter,err=err,itrace=s_choice%itrace,&
           & istop=s_choice%istopc,irst=s_choice%irst)
      call prec%deallocate_wrk(info)
      call psb_barrier(ctxt)
      tslv = psb_wtime() - t1
      ......
      call psb_gpu_exit()
      call psb_exit(ctxt)
      stop

Listing 7: setup of a GPU-enabled test program part three.

It is very important to employ smoothers and coarsest solvers that are suited to the GPU, i.e. methods that do NOT employ triangular system solve kernels. Methods that satisfy this constraint include:

- JACOBI
- BJAC with the following methods on the local blocks:
  - INVK
  - INVT
  - AINV

and their ℓ1 variants.

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