EuclideanDistanceWithGPU.py

import numpy as np
from timeit import default_timer as timer
from numba import vectorize
import pandas as pd

@vectorize(['float32(float32, float32,float32, float32)'], target='cuda')
def get_length(x1, y1, x2, y2):
    return ((x1 - x2) ** 2 + (y1 - y2) ** 2) ** (1 / 2)


def build_graph(data):
    graph = {}
    for this in range(len(data)):
        for another_point in range(len(data)):
            if this != another_point:
                if this not in graph:
                    graph[this] = {}

                graph[this][another_point] = get_length(data[this][0], data[this][1], data[another_point][0],
                                                        data[another_point][1])

    return graph

def main():
    
    data = pd.read_csv("mona.csv",header=None).values.tolist()
    start = timer()
    graph = build_graph(data)
    duration = timer() - start

    print(duration)

if __name__ == '__main__':
    main()

EuclideanDistanceWithoutGPU.py

import numpy as np
from timeit import default_timer as timer

def get_length(x1, y1, x2, y2):
    return ((x1 - x2) ** 2 + (y1 - y2) ** 2) ** (1 / 2)

def build_graph(data):
    graph = {}
    for this in range(len(data)):
        for another_point in range(len(data)):
            if this != another_point:
                if this not in graph:
                    graph[this] = {}

                graph[this][another_point] = get_length(data[this][0], data[this][1], data[another_point][0],
                                                        data[another_point][1])

def main():

    data = pd.read_csv("mona.csv",header=None).values.tolist()
    start = timer()
    graph = build_graph(data)
    duration = timer() - start

    print(duration)

if __name__ == '__main__':
    main()