feat: readme

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Renge 2024-02-22 17:33:26 -05:00
parent ac91c6403f
commit 2bffb065aa
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#const n = 20. #const n = 500.
#const k = 5.
% n-Queens encoding % n-Queens encoding

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Assignment1/B/reach.lp Normal file
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#include "reachin1000".
source(3).
% Way 1
reach(X) :- source(X).
reach(Y) :- edge(X,Y), reach(X).
% Way 2
%reach(Y) :- edge(X,Y), reach(X).
%reach(X) :- source(X).
% Way 3
%reach(X) :- source(X).
%reach(Y) :- reach(X), edge(X,Y).
% Way 4
%reach(Y) :- reach(X), edge(X,Y).
%reach(X) :- source(X).

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# Assignment 1
## Part A
### Append
```shell
xsb
```
```prolog
['A/append.P'].
suffix([1,2], [1,2,3,4]).
cut([1,2,3]).
```
### Reach
generate input set
```shell
python randomgen.py [number of nodes]
```
### Transitive closure and cycle
```shell
xsb
```
```prolog
['A/cycle.P'].
path(1,2) .
cycle(1).
```
### N-queens
```shell
xsb
```
```prolog
['A/queens.P'].
timeNQueen(8).
timeOneQueen(8).
```
## Part B
### Reach
generate input set
```shell
python randomgen.py [number of nodes]
```
```shell
clingo --models 0 B/reach.lp
```
| Input size | Way 1 | Way 2 | Way 3 | Way 4 |
| ---------- | ------- | ------ | ------ | ------ |
| 10000 | 0.655s | 0.703s | 0.664s | 0.665s |
| 20000 | 1.376s | 1.446s | 1.290s | 1.292s |
| 50000 | 3.355s | 3.501s | 2.750s | 1.645s |
| 100000 | 6.778s | 5.002s | 3.375s | 3.438s |
| 200000 | 12.119s | 7.514s | 7.267s | 7.021s |
Though it looks like the Way4 is way better tha Way 1(Almost twice as fast), but if we let the computer to rest for a while and rerun them the other way(start from 4, then 3, follow by 2 and 1), we got
| Input size | Way 1 | Way 2 | Way 3 | Way 4 |
| ---------- | ------ | ------ | ------ | ------- |
| 200000 | 7.146s | 7.610s | 7.120s | 12.103s |
It is exactly the other way around! I belive it is because the input file becomes too large
(42 MByte), so it waste a lot of time to load it to memory then cache, and the following ones has much higher cache hits rate, so the first one takes way longer than the others.
### N-queens
```shell
clingo --models 0 B/nqueens.lp
```
```shell
clingo --models 1 B/nqueens.lp
```
| Number of queens | Time for 1 queen | Time for all queens |
| ---------------- | ---------------- | ------------------- |
| 8 | 0.004s | 0.006s |
| 10 | 0.003s | 0.086s |
| 12 | 0.004s | 4.909s |
| 14 | 0.006s | Too long to run |
| 20 | 0.011s | |
| 50 | 0.073s | |
| 100 | 0.463s | |
| 200 | 3.233s | |
| 500 | 35.073s | |
## Part C
### N-queens

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Assignment1/randomgen.py Normal file
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import random
import sys
if len(sys.argv) == 2: x = int(sys.argv[1])
else: x = 1000
file = open("reachin1000", "w")
for i in range(10 * x):
j = random.randint(1,x)
k = random.randint(1,x)
file.write("edge({}, {}).\n".format(i, j))
file.close()

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#include "reachin1000".
source(3).
reach(Y) :- edge(X,Y), reach(X).
reach(X) :- source(X).

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import random
x = int(input())
for i in range(10 * x):
j = random.randint(1,x)
k = random.randint(1,x)
print("edge(", j, ",", k, ").")

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reachin1000

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