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| ||ll190 || 98ms || 49910 || 49077 || 60ms || 27204 || 266 || 80ms || 2170 || 1 || ped_c || AMD Ryzen R5 1600 @ 3.7GHz 16GB RAM @ 3000MHz (pypy3, best of 5) || | ||ll190 || 98ms || 49910 || 49077 || 60ms || 27204 || 266 || 80ms || 2170 || 1 || ped_python (ped_python is faster with pypy3) || AMD Ryzen R5 1600 @ 3.7GHz 16GB RAM @ 3000MHz (pypy3, best of 5) || |
| Line 38: | Line 38: |
---- /!\ '''Edit conflict - other version:''' ---- ||ta93 || 845ms || 52341 || 144 || 1163 || 27204|| 44 || 20080ms || 85716 || 0 || ped_python || Intel I7 4720HQ @2.60 GHz, 8GB RAM || ---- /!\ '''Edit conflict - your version:''' ---- ||ks496 || 15ms || 200 || 48 || 22ms || 104|| 4 || 8ms || 200 || 0 || ped_c || Intel Core i7-4720HQ @ 2.60GHz, 8 GB RAM, (small data) || ---- /!\ '''End of edit conflict''' ---- |
Results for Exercise Sheet 5 (q-Gram Index)
Add your row to the table below, following the examples already there. In the first column, write your account name, or name1+name2 if you work in a group.
For each query, write down the total query time (Time), the number of needed PED computations (#PED) and the number of returned results (#RES). In the last two columns, give details about the provided PED module you are using (either ped_c or ped_python) and your local machine.
Name |
Query: the |
Query: breib |
Query: the BIG lebauski |
PED Module |
Processor / RAM |
|||||||
Time |
#PED |
#RES |
Time |
#PED |
#RES |
Time |
#PED |
#RES |
||||
pb1042 |
478ms |
49910 |
49077 |
235ms |
27204 |
266 |
542ms |
2170 |
1 |
ped_c |
Intel Core i5-5 @ 2.00GHz, 32 GB RAM |
|
pb1042 |
1151ms |
49910 |
49077 |
1169ms |
27204 |
266 |
1094ms |
2170 |
1 |
ped_python |
Intel Core i5-5 @ 2.00GHz, 32 GB RAM |
|
sw540 |
233ms |
49910 |
49077 |
132ms |
27204 |
266 |
274ms |
2170 |
1 |
ped_c |
Intel Core i7-9750H @ 2.60GHz, 32 GB RAM |
|
fm213 |
723ms |
49910 |
49077 |
859ms |
27204 |
266 |
4033ms |
2170 |
1 |
ped_c |
Intel Core i5-4300U @ 1.90GHz, 8 GB RAM |
|
jr74+tw246 |
439ms |
49910 |
49077 |
473ms |
27204 |
266 |
2035ms |
2170 |
1 |
ped_c |
Intel(R) Core i7-8565U @ 1.80GHz, 8 GB RAM (VM) |
|
ak904 |
584ms |
49910 |
49077 |
362ms |
27204 |
266 |
791ms |
2170 |
1 |
ped_c |
2.7 GHz Dual-Core Intel Core i5, 8 GB RAM |
|
aw221 |
1052ms |
49688 |
49077 |
1167ms |
27136 |
266 |
2228ms |
1265 |
1 |
ped_python |
2,6 GHz 6-Core Intel Core i7, 16 GB RAM |
|
hc63 |
560ms |
49688 |
49077 |
601ms |
27136 |
266 |
2621ms |
1265 |
1 |
ped_c |
Intel Core i5-3320M @ 2.60GHz, 8 GB RAM |
|
ck76-td87 |
1092ms |
49910 |
49077 |
1358ms |
27204 |
266 |
2671ms |
2170 |
1 |
ped_python |
AMD Ryzen 5 1600 @ 4.00 GHz, 16 GB |
|
mr427 |
650ms |
49910 |
49077 |
677ms |
27204 |
266 |
2708ms |
2170 |
1 |
ped_c |
Intel Core i5-5 @ 2.90GHz, 8 GB RAM |
|
ar479-ss1736 |
1186ms |
49910 |
49077 |
1241ms |
27204 |
266 |
900ms |
2170 |
1 |
ped_python |
Intel Core i7-7700HQ CPU @ 2.80GHz (8 CPUs), 8 GB RAM |
|
ek247 |
1342ms |
49910 |
49077 |
779ms |
27204 |
266 |
1153ms |
2170 |
1 |
ped_c |
Intel Core i5-4690 CPU @ 3.50GHz, 16 GB RAM (VM) |
|
rt53 |
433ms |
49910 |
49077 |
466ms |
27204 |
266 |
351ms |
2170 |
1 |
ped_python |
AMD Ryzen 5 3600 @ 3.6GHz, 16GB DDR4-3600 (WSL 1, minimum of 5 tries) |
|
rt53 |
150ms |
49910 |
49077 |
88ms |
27204 |
266 |
172ms |
2170 |
1 |
ped_c |
AMD Ryzen 5 3600 @ 3.6GHz, 16GB DDR4-3600 (WSL 1, minimum of 5 tries) |
|
rk268-ss1731 |
1547ms |
49910 |
49077 |
1672ms |
27204 |
266 |
5016ms |
2170 |
1 |
ped_python |
Intel(R) Core(TM) i5-8265U CPU @ 1.60Ghz 1.80 Ghz 8GB Ram |
|
tl109 |
115ms |
2693 |
2650 |
145ms |
107497 |
215 |
148ms |
6078 |
0 |
ped_c |
Intel(R) Xeon(R) CPU E3-1275 v5 @ 3.60GHz 6GB Ram |
|
mt40 |
1317ms |
49688 |
49077 |
1225ms |
27136 |
266 |
2902ms |
1265 |
1 |
ped_python |
Intel(R) Core(TM) i5-6500 CPU @ 3.20GHz 16 GB RAM |
|
mt40 |
386ms |
49688 |
49077 |
511ms |
27136 |
266 |
2260ms |
1265 |
1 |
ped_c |
Intel(R) Core(TM) i5-6500 CPU @ 3.20GHz 16 GB RAM |
|
jo120-tb350 |
984ms |
49910 |
49077 |
1297ms |
27204 |
266 |
2922ms |
2170 |
1 |
ped_python |
Intel(R) Core(TM) i7-6700K CPU @ 4.00GHz, 16GB Ram |
|
jo120-tb350 |
570ms |
49910 |
49077 |
751ms |
27204 |
266 |
3298ms |
2170 |
1 |
ped_c |
Intel© Core™ i3-3120M CPU @ 2.50GHz × 2, 11.3 GiB RAM |
|
wy8-zl36 |
1250ms |
49910 |
49044 |
1220ms |
77114 |
244 |
1002ms |
79284 |
0 |
ped_python |
Dual-Core Intel Core i5-5275U 2.7 GHz |
|
ka98 |
902ms |
49910 |
49044 |
464ms |
27204 |
244 |
1110ms |
2170 |
0 |
ped_c |
Intel Core 2 Duo 2.8 GHz 8 GB RAM |
|
jm408-ms946 |
1059ms |
49910 |
49077 |
1215ms |
27204 |
266 |
2417ms |
2170 |
1 |
ped_python |
Intel(R) Xeon(R) CPU @ 3.30GHz × 4, 16 GiB RAM |
|
ms873 |
265ms |
49688 |
49077 |
156ms |
27136 |
266 |
234ms |
1265 |
1 |
ped_c modified for msvc |
Intel(R) Core(TM) i7-6900K CPU @ 3.20GHz, 32 GiB RAM |
|
ls720 |
406ms |
49910 |
139 |
271ms |
27204 |
44 |
762ms |
2170 |
0 |
ped_c |
Intel(R) Core(TM) i5-7200U CPU @ 2.50GHz, 8 GB RAM |
|
ll190 |
240ms |
49910 |
49077 |
121ms |
27204 |
266 |
199ms |
2170 |
1 |
ped_c |
AMD Ryzen R5 1600 @ 3.7GHz 16GB RAM @ 3000MHz |
|
ll190 |
98ms |
49910 |
49077 |
60ms |
27204 |
266 |
80ms |
2170 |
1 |
ped_python (ped_python is faster with pypy3) |
AMD Ryzen R5 1600 @ 3.7GHz 16GB RAM @ 3000MHz (pypy3, best of 5) |
|
fs81 |
459ms |
50972 |
49814 |
576ms |
27300 |
268 |
2620ms |
2241 |
1 |
ped_c |
Intel Core i5-6200U @2.30GHz 8 GB RAM |
|
aa382 |
1202ms |
49910 |
49077 |
1225ms |
27122 |
266 |
2561ms |
2150 |
1 |
ped_python |
Intel Core i7 @3.0GHz 16 GB RAM |
|
ew98 |
1969ms |
49910 |
44 |
1765ms |
27204 |
44 |
1405ms |
2170 |
0 |
ped_python |
AMD Ryzen R5 1600 @ 3.2GHz 8 GB RAM |
|
![/!\](/wiki_static/memodump_ad_new/img/alert.png "/!\"){kind=small}
Edit conflict - other version:
ta93 |
845ms |
52341 |
144 |
1163 |
27204 |
44 |
20080ms |
85716 |
0 |
ped_python |
Intel I7 4720HQ @2.60 GHz, 8GB RAM |
Edit conflict - your version:
ks496 |
15ms |
200 |
48 |
22ms |
104 |
4 |
8ms |
200 |
0 |
ped_c |
Intel Core i7-4720HQ @ 2.60GHz, 8 GB RAM, (small data) |
End of edit conflict