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Commit fffcad08 authored by Andreas Marek's avatar Andreas Marek
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Merge branch 'master_pre_stage' of https://gitlab.mpcdf.mpg.de/elpa/elpa into master_pre_stage

parents a490a3f4 ec8bc696
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src/elpa2/elpa2_bandred_template.F90
View file @ fffcad08
......@@ -111,42 +111,19 @@
use precision
use elpa_abstract_impl
implicit none
#include "../general/precision_kinds.F90"
class(elpa_abstract_impl_t), intent(inout) :: obj
integer(kind=ik) :: na, lda, nblk, nbw, matrixCols, numBlocks, mpi_comm_rows, mpi_comm_cols
#if REALCASE == 1
#ifdef USE_ASSUMED_SIZE
real(kind=REAL_DATATYPE) :: a(lda,*), tmat(nbw,nbw,*)
#else
real(kind=REAL_DATATYPE) :: a(lda,matrixCols), tmat(nbw,nbw,numBlocks)
#endif
#endif
#if COMPLEXCASE == 1
#ifdef USE_ASSUMED_SIZE
complex(kind=COMPLEX_DATATYPE) :: a(lda,*), tmat(nbw,nbw,*)
MATH_DATATYPE(kind=rck) :: a(lda,*), tmat(nbw,nbw,*)
#else
complex(kind=COMPLEX_DATATYPE) :: a(lda,matrixCols), tmat(nbw,nbw,numBlocks)
MATH_DATATYPE(kind=rck) :: a(lda,matrixCols), tmat(nbw,nbw,numBlocks)
#endif
#endif /* COMPLEXCASE */
#if REALCASE == 1
#ifdef DOUBLE_PRECISION_REAL
real(kind=REAL_DATATYPE), parameter :: ZERO = 0.0_rk8, ONE = 1.0_rk8
#else
real(kind=REAL_DATATYPE), parameter :: ZERO = 0.0_rk4, ONE = 1.0_rk4
#endif
#endif
#if COMPLEXCASE == 1
#ifdef DOUBLE_PRECISION_COMPLEX
complex(kind=COMPLEX_DATATYPE), parameter :: ZERO = (0.0_rk8, 0.0_rk8), ONE = (1.0_rk8, 0.0_rk8)
#else
complex(kind=COMPLEX_DATATYPE), parameter :: ZERO = (0.0_rk4, 0.0_rk4), ONE = (1.0_rk4, 0.0_rk4)
real(kind=rk) :: eps
#endif
#endif /* COMPLEXCASE == 1 */
logical, intent(in) :: useGPU
integer(kind=ik) :: my_prow, my_pcol, np_rows, np_cols, mpierr
......@@ -161,32 +138,19 @@
integer(kind=ik) :: istep, ncol, lch, lcx, nlc
integer(kind=ik) :: tile_size, l_rows_tile, l_cols_tile
real(kind=REAL_DATATYPE) :: vnorm2
#if REALCASE == 1
real(kind=REAL_DATATYPE) :: xf, aux1(nbw), aux2(nbw), vrl, tau, vav(nbw,nbw)
#endif
#if COMPLEXCASE == 1
complex(kind=COMPLEX_DATATYPE) :: xf, aux1(nbw), aux2(nbw), vrl, tau, vav(nbw,nbw)
#endif
real(kind=rk) :: vnorm2
MATH_DATATYPE(kind=rck) :: xf, aux1(nbw), aux2(nbw), vrl, tau, vav(nbw,nbw)
#if COMPLEXCASE == 1
! complex(kind=COMPLEX_DATATYPE), allocatable :: tmpCUDA(:,:), vmrCUDA(:,:), umcCUDA(:,:) ! note the different dimension in real case
complex(kind=COMPLEX_DATATYPE), allocatable :: tmpCUDA(:), vmrCUDA(:), umcCUDA(:)
complex(kind=COMPLEX_DATATYPE), allocatable :: tmpCPU(:,:), vmrCPU(:,:), umcCPU(:,:)
complex(kind=COMPLEX_DATATYPE), allocatable :: vr(:)
#endif
#if REALCASE == 1
real(kind=REAL_DATATYPE), allocatable :: tmpCUDA(:), vmrCUDA(:), umcCUDA(:)
real(kind=REAL_DATATYPE), allocatable :: tmpCPU(:,:), vmrCPU(:,:), umcCPU(:,:)
real(kind=REAL_DATATYPE), allocatable :: vr(:)
#endif
MATH_DATATYPE(kind=rck), allocatable :: tmpCUDA(:), vmrCUDA(:), umcCUDA(:)
MATH_DATATYPE(kind=rck), allocatable :: tmpCPU(:,:), vmrCPU(:,:), umcCPU(:,:)
MATH_DATATYPE(kind=rck), allocatable :: vr(:)
#if REALCASE == 1
! needed for blocked QR decomposition
integer(kind=ik) :: PQRPARAM(11), work_size
real(kind=REAL_DATATYPE) :: dwork_size(1)
real(kind=REAL_DATATYPE), allocatable :: work_blocked(:), tauvector(:), blockheuristic(:)
real(kind=rk) :: dwork_size(1)
real(kind=rk), allocatable :: work_blocked(:), tauvector(:), blockheuristic(:)
#endif
! a_dev is passed from bandred_real to trans_ev_band
integer(kind=C_intptr_T) :: a_dev, vmr_dev, umc_dev, tmat_dev, vav_dev
......
src/elpa2/elpa2_compute_real_template.F90
View file @ fffcad08
......@@ -103,17 +103,17 @@
use elpa2_workload
use precision
implicit none
#include "../general/precision_kinds.F90"
class(elpa_abstract_impl_t), intent(inout) :: obj
integer(kind=ik), intent(in) :: na, nb, nbCol, nb2, nb2Col, communicator
real(kind=REAL_DATATYPE), intent(inout) :: ab(2*nb,nbCol) ! removed assumed size
real(kind=REAL_DATATYPE), intent(inout) :: ab2(2*nb2,nb2Col) ! removed assumed size
real(kind=REAL_DATATYPE), intent(out) :: d(na), e(na) ! set only on PE 0
integer(kind=ik), intent(in) :: na, nb, nbCol, nb2, nb2Col, communicator
real(kind=rk), intent(inout) :: ab(2*nb,nbCol) ! removed assumed size
real(kind=rk), intent(inout) :: ab2(2*nb2,nb2Col) ! removed assumed size
real(kind=rk), intent(out) :: d(na), e(na) ! set only on PE 0
real(kind=REAL_DATATYPE) :: hv(nb,nb2), w(nb,nb2), w_new(nb,nb2), tau(nb2), hv_new(nb,nb2), &
real(kind=rk) :: hv(nb,nb2), w(nb,nb2), w_new(nb,nb2), tau(nb2), hv_new(nb,nb2), &
tau_new(nb2), ab_s(1+nb,nb2), ab_r(1+nb,nb2), ab_s2(2*nb2,nb2), hv_s(nb,nb2)
real(kind=REAL_DATATYPE) :: work(nb*nb2), work2(nb2*nb2)
real(kind=rk) :: work(nb*nb2), work2(nb2*nb2)
integer(kind=ik) :: lwork, info
integer(kind=ik) :: istep, i, n, dest
......@@ -223,8 +223,8 @@
if (my_pe==0) then
n = MIN(na-na_s-nb2+1,nb) ! number of rows to be reduced
hv(:,:) = CONST_0_0
tau(:) = CONST_0_0
hv(:,:) = 0.0_rk
tau(:) = 0.0_rk
! The last step (istep=na-1) is only needed for sending the last HH vectors.
! We don't want the sign of the last element flipped (analogous to the other sweeps)
......@@ -236,9 +236,9 @@
call obj%timer%stop("blas")
do i=1,nb2
hv(i,i) = CONST_1_0
hv(i,i) = 1.0_rk
hv(i+1:n,i) = ab(1+nb2+1:1+nb2+n-i,na_s-n_off+i-1)
ab(1+nb2+1:2*nb,na_s-n_off+i-1) = CONST_0_0
ab(1+nb2+1:2*nb,na_s-n_off+i-1) = 0.0_rk
enddo
endif
......@@ -247,10 +247,10 @@
d(istep) = ab(1,na_s-n_off)
e(istep) = ab(2,na_s-n_off)
if (istep == na) then
e(na) = CONST_0_0
e(na) = 0.0_rk
endif
else
ab_s2 = CONST_0_0
ab_s2 = 0.0_rk
ab_s2(:,:) = ab(1:nb2+1,na_s-n_off:na_s-n_off+nb2-1)
if (block_limits2(dest+1)<istep) then
dest = dest+1
......@@ -285,7 +285,7 @@
do i=1,nb2
tau(i) = hv(i,i)
hv(i,i) = CONST_1_0
hv(i,i) = 1.0_rk
enddo
endif
endif
......@@ -293,7 +293,7 @@
na_s = na_s+nb2
if (na_s-n_off > nb) then
ab(:,1:nblocks*nb) = ab(:,nb+1:(nblocks+1)*nb)
ab(:,nblocks*nb+1:(nblocks+1)*nb) = CONST_0_0
ab(:,nblocks*nb+1:(nblocks+1)*nb) = 0.0_rk
n_off = n_off + nb
endif
......@@ -324,8 +324,8 @@
ab(1:nb+1,ne+i-1) = ab_r(:,i)
enddo
endif
hv_new(:,:) = CONST_0_0 ! Needed, last rows must be 0 for nr < nb
tau_new(:) = CONST_0_0
hv_new(:,:) = 0.0_rk ! Needed, last rows must be 0 for nr < nb
tau_new(:) = 0.0_rk
if (nr>0) then
call wy_right_&
......@@ -335,9 +335,9 @@
call PRECISION_GEQRF(nr, nb2, ab(nb+1,ns), 2*nb-1, tau_new, work, lwork, info)
call obj%timer%stop("blas")
do i=1,nb2
hv_new(i,i) = CONST_1_0
hv_new(i,i) = 1.0_rk
hv_new(i+1:,i) = ab(nb+2:2*nb-i+1,ns+i-1)
ab(nb+2:,ns+i-1) = CONST_0_0
ab(nb+2:,ns+i-1) = 0.0_rk
enddo
!send hh-Vector
......@@ -458,16 +458,17 @@
use elpa_abstract_impl
use precision
implicit none
#include "../general/precision_kinds.F90"
class(elpa_abstract_impl_t), intent(inout) :: obj
integer(kind=ik), intent(in) :: n !length of householder-vectors
integer(kind=ik), intent(in) :: nb !number of householder-vectors
integer(kind=ik), intent(in) :: lda !leading dimension of Y and W
real(kind=REAL_DATATYPE), intent(in) :: Y(lda,nb) !matrix containing nb householder-vectors of length b
real(kind=REAL_DATATYPE), intent(in) :: tau(nb) !tau values
real(kind=REAL_DATATYPE), intent(out) :: W(lda,nb) !output matrix W
real(kind=REAL_DATATYPE), intent(in) :: mem(nb) !memory for a temporary matrix of size nb
real(kind=rk), intent(in) :: Y(lda,nb) !matrix containing nb householder-vectors of length b
real(kind=rk), intent(in) :: tau(nb) !tau values
real(kind=rk), intent(out) :: W(lda,nb) !output matrix W
real(kind=rk), intent(in) :: mem(nb) !memory for a temporary matrix of size nb
integer(kind=ik) :: i
integer(kind=ik) :: i
call obj%timer%start("wy_gen" // PRECISION_SUFFIX)
......@@ -475,8 +476,8 @@
do i=2,nb
W(1:n,i) = tau(i)*Y(1:n,i)
call obj%timer%start("blas")
call PRECISION_GEMV('T', n, i-1, CONST_1_0, Y, lda, W(1,i), 1, CONST_0_0, mem,1)
call PRECISION_GEMV('N', n, i-1, -CONST_1_0, W, lda, mem, 1, CONST_1_0, W(1,i),1)
call PRECISION_GEMV('T', n, i-1, 1.0_rk, Y, lda, W(1,i), 1, 0.0_rk, mem,1)
call PRECISION_GEMV('N', n, i-1, -1.0_rk, W, lda, mem, 1, 1.0_rk, W(1,i),1)
call obj%timer%stop("blas")
enddo
call obj%timer%stop("wy_gen" // PRECISION_SUFFIX)
......@@ -489,21 +490,22 @@
use precision
use elpa_abstract_impl
implicit none
#include "../general/precision_kinds.F90"
class(elpa_abstract_impl_t), intent(inout) :: obj
integer(kind=ik), intent(in) :: n !width of the matrix A
integer(kind=ik), intent(in) :: m !length of matrix W and Y
integer(kind=ik), intent(in) :: nb !width of matrix W and Y
integer(kind=ik), intent(in) :: lda !leading dimension of A
integer(kind=ik), intent(in) :: lda2 !leading dimension of W and Y
real(kind=REAL_DATATYPE), intent(inout) :: A(lda,*) !matrix to be transformed ! remove assumed size
real(kind=REAL_DATATYPE), intent(in) :: W(m,nb) !blocked transformation matrix W
real(kind=REAL_DATATYPE), intent(in) :: Y(m,nb) !blocked transformation matrix Y
real(kind=REAL_DATATYPE), intent(inout) :: mem(n,nb) !memory for a temporary matrix of size n x nb
real(kind=rk), intent(inout) :: A(lda,*) !matrix to be transformed ! remove assumed size
real(kind=rk), intent(in) :: W(m,nb) !blocked transformation matrix W
real(kind=rk), intent(in) :: Y(m,nb) !blocked transformation matrix Y
real(kind=rk), intent(inout) :: mem(n,nb) !memory for a temporary matrix of size n x nb
call obj%timer%start("wy_left" // PRECISION_SUFFIX)
call obj%timer%start("blas")
call PRECISION_GEMM('T', 'N', nb, n, m, CONST_1_0, W, lda2, A, lda, CONST_0_0, mem, nb)
call PRECISION_GEMM('N', 'N', m, n, nb, -CONST_1_0, Y, lda2, mem, nb, CONST_1_0, A, lda)
call PRECISION_GEMM('T', 'N', nb, n, m, 1.0_rk, W, lda2, A, lda, 0.0_rk, mem, nb)
call PRECISION_GEMM('N', 'N', m, n, nb, -1.0_rk, Y, lda2, mem, nb, 1.0_rk, A, lda)
call obj%timer%stop("blas")
call obj%timer%stop("wy_left" // PRECISION_SUFFIX)
end subroutine
......@@ -515,22 +517,23 @@
use precision
use elpa_abstract_impl
implicit none
#include "../general/precision_kinds.F90"
class(elpa_abstract_impl_t), intent(inout) :: obj
integer(kind=ik), intent(in) :: n !height of the matrix A
integer(kind=ik), intent(in) :: m !length of matrix W and Y
integer(kind=ik), intent(in) :: nb !width of matrix W and Y
integer(kind=ik), intent(in) :: lda !leading dimension of A
integer(kind=ik), intent(in) :: lda2 !leading dimension of W and Y
real(kind=REAL_DATATYPE), intent(inout) :: A(lda,*) !matrix to be transformed ! remove assumed size
real(kind=REAL_DATATYPE), intent(in) :: W(m,nb) !blocked transformation matrix W
real(kind=REAL_DATATYPE), intent(in) :: Y(m,nb) !blocked transformation matrix Y
real(kind=REAL_DATATYPE), intent(inout) :: mem(n,nb) !memory for a temporary matrix of size n x nb
real(kind=rk), intent(inout) :: A(lda,*) !matrix to be transformed ! remove assumed size
real(kind=rk), intent(in) :: W(m,nb) !blocked transformation matrix W
real(kind=rk), intent(in) :: Y(m,nb) !blocked transformation matrix Y
real(kind=rk), intent(inout) :: mem(n,nb) !memory for a temporary matrix of size n x nb
call obj%timer%start("wy_right" // PRECISION_SUFFIX)
call obj%timer%start("blas")
call PRECISION_GEMM('N', 'N', n, nb, m, CONST_1_0, A, lda, W, lda2, CONST_0_0, mem, n)
call PRECISION_GEMM('N', 'T', n, m, nb, -CONST_1_0, mem, n, Y, lda2, CONST_1_0, A, lda)
call PRECISION_GEMM('N', 'N', n, nb, m, 1.0_rk, A, lda, W, lda2, 0.0_rk, mem, n)
call PRECISION_GEMM('N', 'T', n, m, nb, -1.0_rk, mem, n, Y, lda2, 1.0_rk, A, lda)
call obj%timer%stop("blas")
call obj%timer%stop("wy_right" // PRECISION_SUFFIX)
......@@ -543,23 +546,24 @@
use elpa_abstract_impl
use precision
implicit none
#include "../general/precision_kinds.F90"
class(elpa_abstract_impl_t), intent(inout) :: obj
integer(kind=ik), intent(in) :: n !width/heigth of the matrix A; length of matrix W and Y
integer(kind=ik), intent(in) :: nb !width of matrix W and Y
integer(kind=ik), intent(in) :: lda !leading dimension of A
integer(kind=ik), intent(in) :: lda2 !leading dimension of W and Y
real(kind=REAL_DATATYPE), intent(inout) :: A(lda,*) !matrix to be transformed ! remove assumed size
real(kind=REAL_DATATYPE), intent(in) :: W(n,nb) !blocked transformation matrix W
real(kind=REAL_DATATYPE), intent(in) :: Y(n,nb) !blocked transformation matrix Y
real(kind=REAL_DATATYPE) :: mem(n,nb) !memory for a temporary matrix of size n x nb
real(kind=REAL_DATATYPE) :: mem2(nb,nb) !memory for a temporary matrix of size nb x nb
real(kind=rk), intent(inout) :: A(lda,*) !matrix to be transformed ! remove assumed size
real(kind=rk), intent(in) :: W(n,nb) !blocked transformation matrix W
real(kind=rk), intent(in) :: Y(n,nb) !blocked transformation matrix Y
real(kind=rk) :: mem(n,nb) !memory for a temporary matrix of size n x nb
real(kind=rk) :: mem2(nb,nb) !memory for a temporary matrix of size nb x nb
call obj%timer%start("wy_symm" // PRECISION_SUFFIX)
call obj%timer%start("blas")
call PRECISION_SYMM('L', 'L', n, nb, CONST_1_0, A, lda, W, lda2, CONST_0_0, mem, n)
call PRECISION_GEMM('T', 'N', nb, nb, n, CONST_1_0, mem, n, W, lda2, CONST_0_0, mem2, nb)
call PRECISION_GEMM('N', 'N', n, nb, nb, -CONST_0_5, Y, lda2, mem2, nb, CONST_1_0, mem, n)
call PRECISION_SYR2K('L', 'N', n, nb, -CONST_1_0, Y, lda2, mem, n, CONST_1_0, A, lda)
call PRECISION_SYMM('L', 'L', n, nb, 1.0_rk, A, lda, W, lda2, 0.0_rk, mem, n)
call PRECISION_GEMM('T', 'N', nb, nb, n, 1.0_rk, mem, n, W, lda2, 0.0_rk, mem2, nb)
call PRECISION_GEMM('N', 'N', n, nb, nb, -0.5_rk, Y, lda2, mem2, nb, 1.0_rk, mem, n)
call PRECISION_SYR2K('L', 'N', n, nb, -1.0_rk, Y, lda2, mem, n, 1.0_rk, A, lda)
call obj%timer%stop("blas")
call obj%timer%stop("wy_symm" // PRECISION_SUFFIX)
......
test/Fortran/test.F90
View file @ fffcad08
......@@ -501,15 +501,7 @@ program test
#if defined(TEST_EIGENVECTORS) || defined(TEST_QR_DECOMPOSITION)
#ifdef TEST_MATRIX_ANALYTIC
!
!#if defined(TEST_MATRIX_ANALYTIC)
status = check_correctness_analytic(na, nev, ev, z, nblk, myid, np_rows, np_cols, my_prow, my_pcol, check_all_evals)
call check_status(status, myid)
if (.true.) then
! also check residuals
status = check_correctness_evp_numeric_residuals(na, nev, as, z, ev, sc_desc, nblk, myid, np_rows,np_cols, my_prow, my_pcol)
call check_status(status, myid)
endif
#else
!#elif defined(TEST_MATRIX_FRANK)
! status = check_correctness_evp_numeric_residuals(na, nev, as, z, ev, sc_desc, nblk, myid, np_rows,np_cols, my_prow, my_pcol)
......
utils/scaling_scripts/batch_run.py 0 → 100644
View file @ fffcad08
#!/usr/bin/env python
from itertools import product
from scaling import *
output_dir = "out"
template_file = "run_template_hydra.sh"
#elpa_method = ['elpa1', 'elpa2']
elpa_method = ['elpa1', 'elpa2', 'scalapack_all', 'scalapack_part']
#elpa_method = ['scalapack_part']
math_type = ['real', 'complex']
precision = ['single', 'double']
mat_size = [5000, 20000]
proc_eigen = [10,50,100]
block_size = [16]
num_nodes = [1]
#num_nodes.extend([2**i for i in range(2,11)])
num_nodes.extend([2**i for i in range(2,7)])
#num_nodes = [2048]
#===============================================================================================
#===============================================================================================
# the rest of the script should be changed only if something changed (etc. in elpa)
#===============================================================================================
#===============================================================================================
for em, mt, pr, ms, pe, bs, nn in product(elpa_method, math_type, precision, mat_size, proc_eigen, block_size, num_nodes):
tokens = {}
tokens['_BLOCK_SIZE_'] = bs
tokens['_MAT_SIZE_'] = ms·
tokens['_NUM_EIGEN_'] = ms * pe // 100
tokens['_NUM_NODES_'] = nn
variant(output_dir, template_file, tokens, em, mt, pr)
utils/scaling_scripts/parse_elpa1 0 → 100755
View file @ fffcad08
#! /bin/bash
echo nodes total tridiag solve trans_ev
for f in *.txt
do
#echo "processing $f... "
S=`grep " node = " $f | awk '{print $5}'`
TOTAL=`grep "e%eigenvectors()" $f | awk '{print $3}'`
if [[ -z "$TOTAL" ]]; then
continue
fi
S+=" "$TOTAL
S+=" "`grep "|_ tridiag_" $f | awk '{print $3}'`
S+=" "`grep "|_ solve " $f | awk '{print $3}'`
S+=" "`grep "|_ trans_ev" $f | awk '{print $3}'`
echo $S
done
utils/scaling_scripts/parse_elpa2 0 → 100755
View file @ fffcad08
#! /bin/bash
echo nodes total bandred tridiag solve trans_ev_to_band trans_ev_to_full
for f in *.txt
do
#echo "processing $f... "
S=`grep " node = " $f | awk '{print $5}'`
TOTAL=`grep "e%eigenvectors()" $f | awk '{print $3}'`
if [[ -z "$TOTAL" ]]; then
continue
fi
S+=" "$TOTAL
S+=" "`grep "|_ bandred " $f | awk '{print $3}'`
S+=" "`grep "|_ tridiag " $f | awk '{print $3}'`
S+=" "`grep "|_ solve " $f | awk '{print $3}'`
S+=" "`grep "|_ trans_ev_to_band " $f | awk '{print $3}'`
S+=" "`grep "|_ trans_ev_to_full " $f | awk '{print $3}'`
echo $S
done
utils/scaling_scripts/parse_mkl 0 → 100755
View file @ fffcad08
#! /bin/bash
echo nodes total
for f in *.txt
do
#echo "processing $f... "
S=`grep " node = " $f | awk '{print $5}'`
TOTAL=`grep "e%eigenvectors()" $f | awk '{print $3}'`
if [[ -z "$TOTAL" ]]; then
continue
fi
S+=" "$TOTAL
echo $S
done
utils/scaling_scripts/plot.py 0 → 100755
View file @ fffcad08
#! /usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import os
print("PLOTING ...")
group_colors = [['red', 'firebrick', 'indianred', 'tomato', 'maroon', 'salmon'],
['green', 'darkgreen', 'springgreen', 'darkseagreen', 'lawngreen', 'yellowgreen'],
['blue', 'darkblue', 'cornflowerblue', 'dodgerblue', 'midnightblue', 'lightskyblue'],
['magenta', 'darkviolet', 'mediumvioletred', 'orchid', 'deeppink', 'purple'],
['orange', 'gold', 'navajowhite', 'darkorange', 'goldenrod', 'sandybrown'],
['cyan', 'darkcyan', 'lightseagreen', 'turquoise', 'darkturquoise', 'mediumturquoise']]
group_symbols = ['o', 's', '*', 'D', 'x', 'H']
elpa1_subtimes = ["tridiag", "solve", "trans_ev"]
elpa2_subtimes = ["bandred", "tridiag", "solve", "trans_ev_to_band", "trans_ev_to_full"]
cores_per_node = 20
base_paths = ["results", "results2"]
num_type = "real"
prec = "double"
mat_size = 5000
def scalapack_name(num, pr, all_ev):
if(num_type == "real"):
if(pr == "single"):
name = "pssyev"
else:
name = "pdsyev"
else:
if(pr == "single"):
name = "pcheev"
else:
name = "pzheev"
if(all_ev):
name += "d"
else:
name += "r"
return name
def line(what, mat_size, proc_evec, method, label, color, style):
data_line_res = []
nodes_res = []
for base_path in base_paths:
path = "/".join([base_path,num_type,prec,str(mat_size),str(mat_size*proc_evec//100),method,"tab.txt"])
#print(path)
if not os.path.isfile(path):
continue
data = np.genfromtxt(path, names=True)
nodes = data['nodes']
data_line = data[what]
#print("data_line", data_line, "data_line_res", data_line_res)
if(nodes_res == []):
assert(data_line_res == [])
nodes_res = nodes
data_line_res = data_line
else:
assert(all(nodes == nodes_res))
data_line_res = np.minimum(data_line_res, data_line)
cores = cores_per_node * nodes_res
#print(cores, data_line_res)
plt.plot(cores,data_line_res, style, label=label, color=color, linewidth=2)
def plot1():
line("total", mat_size, 100, "pdsyevd", "MKL 2017, " + scalapack_name(num_type, prec, True), "black", "x-")
line("total", mat_size, 100, "pdsyevr", "MKL 2017, " + scalapack_name(num_type, prec, True) + ", 100% EVs", "blue", "x-")
line("total", mat_size, 50, "pdsyevr", "MKL 2017, " + scalapack_name(num_type, prec, True) + ", 50% EVs", "green", "x-")
line("total", mat_size, 10, "pdsyevr", "MKL 2017, " + scalapack_name(num_type, prec, True) + ", 10% EVs", "red", "x-")
line("total", mat_size, 100, "elpa1", "ELPA 1, 100% EVs", "blue", "*--")
line("total", mat_size, 50, "elpa1", "ELPA 1, 50% EVs", "green", "*--")
line("total", mat_size, 10, "elpa1", "ELPA 1, 10% EVs", "red", "*--")
line("total", mat_size, 100, "elpa2", "ELPA 2, 100% EVs", "blue", "o:")
line("total", mat_size, 50, "elpa2", "ELPA 2, 50% EVs", "green", "o:")
line("total", mat_size, 10, "elpa2", "ELPA 2, 10% EVs", "red", "o:")
def details(proc_ev):
for i in range(len(elpa1_subtimes)):
line(elpa1_subtimes[i], mat_size, proc_ev, "elpa1", "ELPA1 - " + elpa1_subtimes[i], group_colors[0][i], group_symbols[2*i] + '-')
for i in range(len(elpa2_subtimes)):
line(elpa2_subtimes[i], mat_size, proc_ev, "elpa2", "ELPA2 - " + elpa2_subtimes[i], group_colors[1][i], group_symbols[i] + '-')
fig = plt.figure(figsize=(15, 10))
ax = fig.add_subplot(111)
ax.tick_params(labelright='on')
plot1()
#details(100)
#plt.title('Num CPUs ' + str(num_cpus) + ' and ' + str(eigenvectors_percent) + '% eigenvectors, ' + numtype)
#plt.title('Num CPUs ')
plt.title("Matrix " + str(mat_size//1000) + "k, " + num_type + ", " + prec)
plt.grid()
plt.legend(loc=1)
plt.xlabel('Number of cores')
plt.ylabel('Execution time [s]')
plt.xscale('log')
plt.yscale('log')
ax.xaxis.grid(b=True, which='major', color='black', linestyle=':')
ax.yaxis.grid(b=True, which='major', color='black', linestyle='--')
ax.yaxis.grid(b=True, which='minor', color='black', linestyle=':')
ticks = [20* 2**i for i in range(0,12)]
ax.xaxis.set_ticks(ticks)
ax.xaxis.set_ticklabels(ticks)
if(mat_size < 10000):
y_min = 0.1
y_max = 50
else:
y_min = 5
y_max = 500
yticks_major = [1,10,100,1000, y_min, y_max]
ax.yaxis.set_ticks(yticks_major)
ax.yaxis.set_ticklabels(yticks_major)
# yticks_minor = [2, 5, 20, 50, 200, 500]
# ax.yaxis.set_ticks(yticks_minor, minor=True)
# ax.yaxis.set_ticklabels(yticks_minor, minor=True)
plt.ylim([y_min, y_max])
plt.xlim([20, 41000])
plt.savefig('plot.pdf')
#if show:
plt.show()
#plt.close()