49%
02.08.2021
.06 0.00 30.83 0.26 0.00 9.78 0.67 0.60
nvme0n1 2769.50 2682.00 29592.00 10723.25 241.00 0.00 8.01 0.00 0.11 0.02 0.01 10.68 4.00 0.14 77.60
sdb
49%
16.05.2013
,1000);
06
07 // Set host data on the Device (GPU)
08 dA = gpuSetData(A);
09 dC = gpuSetData(C);
10
11 d1 = gpuMult(A,B);
12 d2 = gpuMult(dA,dC);
13 d3 = gpuMult(d1,d2);
14 result = gpuGetData(d3); // Get
49%
25.03.2020
GVzLmlvL3NlcnZpY2VhY2NvdW50L3NlcnZpY2UtYWNjb3VudC51aWQiOiJiNDVhMDhjMi1kMzg1LTQxMmItOTUwNS02YmRmODdiNjRhN2EiLCJzdWIiOiJzeXN0ZW06c2VydmljZWFjY291bnQ6ZGVmYXVsdDp0ZXN0c2VydmljZWFjY291bnQifQ.SO9XwM3zgiW6sOfEaJx1P6
49%
05.12.2019
).
Figure 1: Flattening a 2D array in C or C++.
Listing 3
inspect.c
#include
**
int a[4][5] = { // array of 4 arrays of 5 ints each, a 4x5 matrix
{ 1, 2, 3
49%
27.08.2014
was the random read and write test with small record sizes and a smaller total file size (a kind of random IOPS run):
./iozone -i 2 -w -r 4k -I -O -w -+n -s 4g -t 2 -+n > iozone_random_1.out
The total file size
48%
16.01.2013
$ starcluster start -s 1 foocluster -n ami-999d49f0
$ starcluster get foocluster /opt/sge6-fresh .
$ starcluster terminate foocluster
$ starcluster start -o -s 1 -i t1.micro -n ami-e2a0058b imagehost
48%
09.01.2019
of the loop, n
, is large enough, some processing hardware can greatly speed up the computation.
What happens if z(i)
depends on a previous value, as in the following:
do i = 2,n
z(i) = z(i-1)*2
enddo
48%
22.12.2017
in cs us sy id wa st
04 1 0 0 5279852 2256 668972 0 0 1724 25 965 1042 17 9 71 2 0
05 1 0 0 5269008 2256 669004 0 0 0 0 2667 1679 28 3 69 0 0
06 1 0
48%
07.03.2019
; you should collapse two or more loops.
Table 4: Collapsing Loops
Fortran
C
!$acc parallel loop collapse(2)
do i=1,n
...
do j=1,m
...
enddo
48%
02.02.2021
from 1.00 with one processor to 1.67 with two processors. Although not quite a doubling in performance (a
would have to be 2), about one-third of the possible performance was lost because of the serial
