Baunsgaard opened a new pull request #1127:
URL: https://github.com/apache/systemds/pull/1127
This PR contains a simple addition to the micro benchmarks.
This time transpose of a matrix is measured.
3 basic cases:
"skinny" with 2.5mil rows 50 cols
"wide" with 50 cols and 2.5 mil rows
"full" with 20000 rows and 5000 cols
run sparse and dense.
on 3 different systems the time it takes for a transpose varies drastically,
and currently not as expected:
The one case that is very inefficient currently is a sparse wide matrix,
that takes 4-5 times longer on many core machines compared to a few cores.
Alpha:
```bash
scripts/perftest/results/transpose-wide-0.1.log
Total elapsed time: 22.405 sec.
1 r' 20.578 5
Total elapsed time: 24.200 sec.
1 r' 22.324 5
Total elapsed time: 27.786 sec.
1 r' 25.900 5
Total elapsed time: 25.258 sec.
1 r' 23.406 5
Total elapsed time: 22.654 sec.
1 r' 20.861 5
1532631.15 msec task-clock # 61.009 CPUs utilized
( +- 4.47% )
4621538496317 cycles # 3.015 GHz
( +- 4.35% ) (30.76%)
659745166202 instructions # 0.14 insn per cycle
( +- 11.77% ) (38.45%)
```
xps:
```bash
scripts/perftest/results/transpose-wide-0.1.log
Total elapsed time: 6.269 sec.
1 r' 4.907 5
Total elapsed time: 6.356 sec.
1 r' 5.004 5
Total elapsed time: 6.482 sec.
1 r' 5.108 5
Total elapsed time: 6.511 sec.
1 r' 5.022 5
Total elapsed time: 6.428 sec.
1 r' 5.061 5
60.976,97 msec task-clock # 8,790 CPUs utilized
( +- 0,75% )
187.499.949.636 cycles # 3,075 GHz
( +- 0,29% ) (30,65%)
92.529.928.550 instructions # 0,49 insn per cycle
( +- 0,36% ) (38,34%)
```
tango:
```bash
scripts/perftest/results/transpose-wide-0.1.log
Total elapsed time: 23.525 sec.
1 r' 21.169 5
Total elapsed time: 21.440 sec.
1 r' 19.291 5
Total elapsed time: 23.235 sec.
1 r' 21.014 5
Total elapsed time: 23.051 sec.
1 r' 21.037 5
Total elapsed time: 22.883 sec.
1 r' 20.551 5
454278.39 msec task-clock # 19.145 CPUs utilized
( +- 1.71% )
1203991163914 cycles # 2.650 GHz
( +- 1.64% ) (33.34%)
236261779038 instructions # 0.20 insn per cycle
```
For refference why i'm addressing this is because compression is doing a
transpose in the beginning.
On my airlines dataset, this transpose takes 16 seconds on alpha while, on
my laptop 1 second.
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