Differences between revisions 1 and 51 (spanning 50 versions)

Results for Exercise Sheet 5 (q-Gram Index)

Add your row to the table below, following the examples already there. Time B is the time for the baseline. Time Q is the time using the q-gram index. #PEDs Q is the number of PED computations done with the q-gram based algorithm.

In the first column, write your first name, or name1+name2 if you work in a group.

Note: The original dataset had encoding issues. Please measure your times using the replaced dataset we uploaded (Sunday, November 22nd, 17:35h).

Name

Query: The H

Query: Terinator

Query: Figct Cl

Processor / RAM

Language

Time B

Time Q

#PEDs Q

Time B

Time Q

#PEDs Q

Time B

Time Q

#PEDs Q

Elmar

3,912ms

1,218ms

48,518

12,254ms

107ms

1,206

8,060ms

3ms

Intel i5-2520M @ 2.50GHz / 8GB

Python

Matia

3,423ms

1,259ms

49,229

11,800ms

239ms

1,240

7,792ms

8ms

Intel i5 @ 2.60GHz / 8GB

Python

Marco

257ms

62ms

31,900

521ms

92ms

31,953

336ms

14ms

5506

Intel i5 @ 2.60GHz / 8GB

Java

Raghu

45,120ms

14,155ms

49,229

154,070ms

2558ms

1,240

101,053ms

125ms

AMD A6 @ 1.80 GHz / 4GB

Python

Jay

4,168ms

919ms

34,797

13,249ms

3,379ms

41,125

8,816ms

639ms

11,783

i7-4510U @ 2.00GHz / 8GB

Python

Evgeny + Numair

4,875ms

1,834ms

49,229

10,630ms

271ms

1,240

8,298ms

19ms

Intel i5 @ 3.50 GHz - 16 GB RAM

Python

-  ⇤ ← Revision 1 as of 2015-11-17 15:20:20 → 
  Size: 748
  Editor: adpult
  Comment:
+   ← Revision 51 as of 2015-11-22 17:54:09 → ⇥
  Size: 2724
  Editor: adpult
  Comment:
-Deletions are marked like this.
+Additions are marked like this.
 Line 3:
-Add your row to the table below, following the examples already there. Please write down the ratios for both time and comparisons (comp) as floats with '''exactly two digits of precision'''. In the first column, write your first name, or name1+name2 if you work in a group.
Speedup is always measured as time_for_baseline / time_for_your_version  (<1 = slower, >1 faster).
+Add your row to the table below, following the examples already there. ''Time B'' is the time for the baseline. ''Time Q'' is the time using the q-gram index. ''#PEDs Q'' is the number of PED computations done with the q-gram based algorithm.
-Line 6:
+Line 5:
-||'''Name''' || '''The H''' time ||'''The H''' comp.|| '''Ter,inator''' time ||'''Ter,inator''' comp.|| '''Figct Cl''' time ||'''Figct Cl''' comp.||
||Elmar      ||    3.09          ||   3.44          ||    81.36              ||   136.75             ||    1905.78          ||   21196.12         ||
+In the first column, write your first name, or name1+name2 if you work in a group.

'''Note''': The original dataset had encoding issues. Please measure your times using the replaced [[http://ad-teaching.informatik.uni-freiburg.de/InformationRetrievalWS1516/movie-titles-ascii.txt|dataset]] we uploaded {{{
#!html 
<span style="color:red">(Sunday, November 22nd, 17:35h).</span>
}}}

||<tablewidth="100%" tableheight="auto" style="text-align:center" |2> '''Name''' |||||| '''Query: The H''' |||||| '''Query: Terinator''' |||||| '''Query: Figct Cl'''  ||<style="text-align:center" |2>'''Processor / RAM''' ||||<style="text-align:center" |2>'''Language''' ||
||<:>   '''Time B''' ||<style="text-align:center"> '''Time Q''' ||<:> '''#PEDs Q''' ||<:>   '''Time B''' ||<:> '''Time Q''' ||<:> '''#PEDs Q''' ||<:>   '''Time B''' ||<:> '''Time Q''' ||<:> '''#PEDs Q''' ||
||Elmar      ||<:>    3,912ms        ||<:>   1,218ms        ||<:>    48,518            ||<:>   12,254ms      ||<:>    107ms     ||<:>   1,206        ||<:>    8,060ms      ||<:>    3ms       ||<:>   5           || Intel i5-2520M @ 2.50GHz / 8GB || Python ||
||Matia      ||<:>    3,423ms        ||<:>   1,259ms        ||<:>    49,229            ||<:>   11,800ms      ||<:>    239ms     ||<:>   1,240        ||<:>    7,792ms      ||<:>    8ms       ||<:>   8           || Intel i5 @ 2.60GHz / 8GB || Python ||
||Marco      ||<:>    257ms        ||<:>   62ms        ||<:>    31,900            ||<:>   521ms      ||<:>    92ms     ||<:>   31,953        ||<:>    336ms      ||<:>    14ms       ||<:>   5506           || Intel i5 @ 2.60GHz / 8GB || Java ||
||Raghu      ||<:>    45,120ms        ||<:>   14,155ms        ||<:>    49,229            ||<:>   154,070ms      ||<:>    2558ms     ||<:>   1,240        ||<:>    101,053ms      ||<:>    125ms       ||<:>   8           || AMD A6 @ 1.80 GHz / 4GB || Python ||
||Jay      ||<:>    4,168ms        ||<:>   919ms        ||<:>    34,797            ||<:>   13,249ms      ||<:>    3,379ms     ||<:>   41,125        ||<:>    8,816ms      ||<:>    639ms       ||<:>   11,783           || i7-4510U @ 2.00GHz / 8GB || Python ||
||Evgeny + Numair||<:>    4,875ms        ||<:>   1,834ms        ||<:>    49,229            ||<:>   10,630ms      ||<:>    271ms     ||<:>   1,240        ||<:>    8,298ms      ||<:>    19ms       ||<:>   8           || Intel i5 @ 3.50 GHz - 16 GB RAM || Python ||