shreyash14s

==9626== Profiling application: ./a.out
==9626== Profiling result:
Time(%)      Time     Calls       Avg       Min       Max  Name
 24.78%  3.7241ms        53  70.266us  64.898us  118.66us  block_sum(float const *, float*, unsigned long)
 19.86%  2.9851ms        17  175.60us  164.23us  265.61us  calculatePR_part1(float*, float*, int*, int*, unsigned long, unsigned long, float*, float)
 18.42%  2.7685ms        17  162.85us  154.82us  249.29us  calculatePR_part3(float*, float*, unsigned long)
 11.22%  1.6866ms        17  99.211us  92.164us  151.01us  calculatePR_part2(float*, unsigned long, float*, float)
 11.06%  1.6623ms        17  97.782us  91.459us  148.36us  calculatePR_part4(float*, unsigned long, float)
 11.05%  1.6610ms        17  97.703us  92.323us  145.86us  calculatePR_part0(float*, float*)
  3.12%  469.49us       174  2.6980us  2.0480us  10.593us  [CUDA memcpy DtoH]

shreyash14s

import numpy as np
from skimage import data,io
import matplotlib.pyplot as plt

def get(im, i, j):
    if 0 <= i < im.shape[0] and 0 <= j < im.shape[1]:
        return im[i, j]
    return 0

def GAP(im, i, j):

shreyash14s

# Source: https://www.tensorflow.org/get_started/mnist/pros
# Modified to reduce memory usage by removing a hidden layer.
import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data
# input
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

#helper
def weight_variable(shape):

shreyash14s

# Source: https://www.tensorflow.org/get_started/mnist/beginners
import tensorflow as tf

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

x = tf.placeholder(tf.float32, [None, 784])

W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))

shreyash14s

import multiprocessing

def square(n, l):
	for i in range(n):
		l.append(i * i)

n = 10000000
pcount = 4
processes = []
for i in range(pcount):

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import threading

def square(n, l):
	for i in range(n):
		l.append(i * i)

n = 10000000
tcount = 4
threads = []
for i in range(tcount):