The speed difference of CPU and GPU can be significant in deep learning. But how much? Let’s do a test.

**The computer:**

The computer I use is a Amazon AWS instance g2.2xlarge (https://aws.amazon.com/ec2/instance-types/). The cost is $0.65/hour, or $15.6/day, or $468/mo. It has one GPU (High-performance NVIDIA GPUs, each with 1,536 CUDA cores and 4GB of video memory), and 8 vCPU (High Frequency Intel Xeon E5-2670 (Sandy Bridge) Processors). Memory is 15G.

**The script:**

I borrowed Erik Hallstrom’s code from https://medium.com/@erikhallstrm/hello-world-tensorflow-649b15aed18c

The code runs matrix multiplication and calculate the time when using CPU vs GPU.

from __future__ import print_function import matplotlib import matplotlib.pyplot as plt import tensorflow as tf import time def get_times(maximum_time): device_times = { "/gpu:0":[], "/cpu:0":[] } matrix_sizes = range(500,50000,50) for size in matrix_sizes: for device_name in device_times.keys(): print("####### Calculating on the " + device_name + " #######") shape = (size,size) data_type = tf.float16 with tf.device(device_name): r1 = tf.random_uniform(shape=shape, minval=0, maxval=1, dtype=data_type) r2 = tf.random_uniform(shape=shape, minval=0, maxval=1, dtype=data_type) dot_operation = tf.matmul(r2, r1) with tf.Session(config=tf.ConfigProto(log_device_placement=True)) as session: start_time = time.time() result = session.run(dot_operation) time_taken = time.time() - start_time print(result) device_times[device_name].append(time_taken) print(device_times) if time_taken > maximum_time: return device_times, matrix_sizes device_times, matrix_sizes = get_times(1.5) gpu_times = device_times["/gpu:0"] cpu_times = device_times["/cpu:0"] plt.plot(matrix_sizes[:len(gpu_times)], gpu_times, 'o-') plt.plot(matrix_sizes[:len(cpu_times)], cpu_times, 'o-') plt.ylabel('Time') plt.xlabel('Matrix size') plt.show() plt.plot(matrix_sizes[:len(cpu_times)], [a/b for a,b in zip(cpu_times,gpu_times)], 'o-') plt.ylabel('CPU Time / GPU Time') plt.xlabel('Matrix size') plt.show()

**Result:**

Similar to Erik’s original finding, we found huge difference between CPU and GPU. In this test, GPU is 40 – 80 times faster than CPU.

Receive email notification via email

Don't want to miss new papers in your field? Check out Stork we developed: |
专注医学生物类的论文润色 联系他们请用优惠码 STORK4，他们会给你折扣。 |