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||Zhiwei||<:> 831ms||<:> 289390ms||<:> 5||<:> 92255ms||<:> 335391ms||<:> 16||<:> 90409ms||<:> 21251ms||<:> 0||2.6 GHz Intel Core i7||C++|| | ||Zhiwei||<:> 831ms||<:> 289390ms||<:> 5||<:> 96900ms||<:> 335391ms||<:> 16||<:> 94525ms||<:> 21251ms||<:> 11153||2.6 GHz Intel Core i7||C++|| ||Robin ||<:> 767ms ||<:> 253ms ||<:> 48,489 ||<:> 1,700ms ||<:> 33ms ||<:> 1,179 ||<:> 1,251ms ||<:> 2ms ||<:> 5 || Intel i7 @ 2.00GHz / 16GB || C++ || |
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 corrected 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 |
48,521 |
12,254ms |
107ms |
1,206 |
8,060ms |
3ms |
5 |
Intel i5-2520M @ 2.50GHz / 8GB |
Python |
|
Matia |
3,239ms |
1,261ms |
48,521 |
11,217ms |
265ms |
1,206 |
7,343ms |
17ms |
5 |
Intel i5 @ 2.60GHz / 8GB |
Python |
|
Marco |
265ms |
57ms |
31,466 |
501ms |
81ms |
31,518 |
264ms |
15ms |
5301 |
Intel i5 @ 2.60GHz / 8GB |
Java |
|
Raghu |
45,120ms |
14,155ms |
48,521 |
154,070ms |
2,558ms |
1,206 |
101,053ms |
125ms |
5 |
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 |
|
Frank |
2,879ms |
1,096ms |
48,521 |
10,862ms |
280ms |
1,206 |
6,781ms |
18ms |
5 |
i5-4690 @ 3.50GHz / 8GB |
Python |
|
Elke |
5,816ms |
1,040ms |
48,521 |
11,752ms |
99ms |
1,206 |
9,662ms |
3ms |
5 |
Intel i5 @ 2.20GHz / 8GB |
Python |
|
Elias + Max |
9,072ms |
3,320ms |
50,918 |
18,569ms |
408ms |
2,595 |
14,731ms |
111ms |
1,172 |
Intel i7 @ 2.90GHz / 8GB |
Python |
|
/'fræŋk/ |
425ms |
222ms |
48,521 |
738ms |
53ms |
1,206 |
550ms |
14ms |
5 |
Intel i7 @ 2.50GHz / 16GB |
Python (pypy) |
|
HuiHui |
42,823ms |
15,120ms |
48,521 |
86,142ms |
5,068ms |
5,335 |
68,242ms |
2,381ms |
5,799 |
Intel Core i5 @ 1.7 GHz - 8GB RAM |
Python |
|
Erik |
9,275ms |
3,653ms |
48,521 |
19,176ms |
448ms |
1,206 |
14,924ms |
5.7ms |
4 |
Intel® Core™ i5-2520M CPU @ 2.50GHz / 4GB |
Python |
|
Il |
17,908ms |
2,924ms |
48,521 |
33,701ms |
957ms |
1,206 |
27,116ms |
101ms |
5 |
Intel Core i5-2435M CPU @ 2.40GHz / 8GB |
Python |
|
Daniel |
9,888ms |
3,644ms |
48,521 |
26,517ms |
504ms |
1,206 |
19,804ms |
64ms |
5 |
Intel Pentium T4500 @ 2.3GHz / 4GB |
Python |
|
Sam |
8,273ms |
2,101ms |
50,875 |
18,099ms |
5,490ms |
52,763 |
15.414ms |
978ms |
11,757 |
Intel Core i5-2520M CPU @ 2.50GHz / 8GB |
Python |
|
David |
4,396ms |
1,389ms |
48,521 |
13,319ms |
156ms |
1,206 |
9,072ms |
13ms |
5 |
Intel Core i5 @ 2.2 GHz - 8GB RAM |
Python |
|
Zhiwei |
831ms |
289390ms |
5 |
96900ms |
335391ms |
16 |
94525ms |
21251ms |
11153 |
2.6 GHz Intel Core i7 |
C++ |
|
Robin |
767ms |
253ms |
48,489 |
1,700ms |
33ms |
1,179 |
1,251ms |
2ms |
5 |
Intel i7 @ 2.00GHz / 16GB |
C++ |