Trying to convert this code to run on GPU using CUDA(pycuda)

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Trying to convert this code to run on GPU using CUDA(pycuda)

 

Please help convert the following code to run on OPU using pycuda.

import pandas as pd

import matp1otlibpypot as pit

import numpy as np

from time import time

un = (Thttps://archiveics.ucLedu/mi/machine-leaming-databases/abalone/abalone.data)

abalone = pd.read_csv(url. header=None)

abalone.headO

abalone.columns = rSexLength ameterHeighr,Whole weightShocked weight’’Viscera

weightShelI weghtRingsJ

abalone = abalonedropÇSex”, axisl)

abalone[Rings9.hist(bins=15)

plt.showO

correlation_matrix = abalone.cord)

pnnt(correlation_matrixRings9)

X = abaIone.&opÇRings axis=1)

X = X.values

y = abalonerPingsj

y = y.values

new_data_point =

np.array([O.569552.O.4464O7,O.154437.1.O16849O.439O5i,O.222526.O.29i2O8,])

ti = time()

*This next line should be parallelized in CUDA

distances = np.linalg.norm(X - new_data_point. axis=i)

k=3

nearest_neighbor_ids = distances.argsortú[:kJ

print(nearest_neighbor_ids)

nearest_neighbor_rings = y(nearest_neighbor_ids)

pnnt(nearest_nesghbor_nings)

prediction = nearest_neighbor_nings.mean()

print(pœdiction)

t2 = timeû-ti

pnnt(t2)

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