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#!/usr/bin/env python | |
# Benchmark transferring data, part of troubleshooting https://github.com/tensorflow/tensorflow/issues/6116 | |
# | |
# Take a independent workers communicating with b parameter shards | |
# Each worker tries to add to variables stored on parameter server as fast as | |
# possible. | |
# | |
# macbook | |
# ps=1: 1.6 GB/s | |
# ps=2: 2.6 GB/s |
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"""Benchmark tensorflow distributed by adding vector of ones on worker2 | |
to variable on worker1 as fast as possible. | |
On 2014 macbook, TensorFlow 0.10 this shows | |
Local rate: 2175.28 MB per second | |
Distributed rate: 107.13 MB per second | |
""" |
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""" | |
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy) | |
BSD License | |
""" | |
import numpy as np | |
# data I/O | |
data = open('input.txt', 'r').read() # should be simple plain text file | |
chars = list(set(data)) | |
data_size, vocab_size = len(data), len(chars) |
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Latency Comparison Numbers (~2012) | |
---------------------------------- | |
L1 cache reference 0.5 ns | |
Branch mispredict 5 ns | |
L2 cache reference 7 ns 14x L1 cache | |
Mutex lock/unlock 25 ns | |
Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
Compress 1K bytes with Zippy 3,000 ns 3 us | |
Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |