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Research Outline
Prepared for Max R. | Delivered December 3, 2019
Neural Machine Translation
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Goals
Determine information on Neural Machine Translation components. The information will be used for an article.
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Early Findings
Neural Machine Translation n (NMT)
Nodes in NMT
Machine translation
involves capturing text in one language and producing text in another language.
When
neural networks
are employed for this process, this is referred to as neural machine translation.
The
encoder-decoder configuration
is a popular recurrent neural network (RNN) component.
The setup is composed of an
encoder network
and a decoder network.
T
h
e
encoder portion
processes the input text
and the decoder part provides the translated text as its output.
For massive translation requirements like the ones that the Google neural machine translation (GNMT) system is handling, it is necessary to distribute the complete workload into
multiple processors and compute nodes
.
The system is also optimized by extending the bucketing logic for combining similar length sentences into
several nodes
to attain load
There are several available platforms for
data science programming
.
One example is the "
Deep Learning Keras Integration
."
The platform can be used to handle
neural machine translation
processes.
Due to its graphical interface setup, the computing units in the platform are "
small colorful blocks called nodes
."
Arranging nodes
in a pipeline in a specific sequence will produce a data processing application.
The pipeline is referred to as the "
workflow
."
The platform is made up of a
software base
and several extensions and integration from the developer community.
These
extensions and integration programs
can improve the base software features and can produce complex AI algorithms such as deep learning related applications.
As an example, the "
Deep Learning" extension
combines several functionalities from the Keras libraries.
These libraries then consolidate the
functionalities from TensorFlow
in Python programming.
Within the Keras integration, there are
several nodes on-hand
to develop specific network layers.
There are also
several nodes that are on-hand
to "train networks in Keras, Tensorflow, and Python."
The benefit of using the Keras integration include the massive
lowering of the amount of code
to generate.
There are several Keras library functions that have been
integrated into the nodes
.
Most of these functional nodes provide a
graphic dialog window
.
Some nodes also lets the
combination of more Keras/TensorFlow
libraries through Python code.
There are
other nodes
that are available in the Keras platform.
A massive amount of nodes execute neural layers such as "
input and dropout layers in Core
, LSTM layers in Recurrent, and Embedding layers in the Embedding sub-category."
Furthermore, the "Learner, Reader and Writer nodes" can be used to "respectively
train, retrieve and store
a network."
The main nodes are the "
DL Python Network Executor
and DL Python Network Editor."
These two nodes correspondingly enable "
custom execution and custom editing
" of a "Python compatible Deep Learning network via Python script, including Jupyter notebook."
T
h
e
s
e two nodes "
effectively bridge Keras nodes
with all other not yet integrated Keras/TensorFlow library functions."
Cost of Computing Nodes
Argon Phase 3
Next generation Argon nodes
with the following configurations are available for purchase at the indicated price:
Non-GPU Compute Nodes
-
80 Compute Slots, Intel Xeon Gold 6230@2.1GHz (Turbo up to 3.9GHz), DDR4-2933, 1TB SSD, 100Gbps InfiniBand EDR, 10Gb Ethernet
Standard Memory
-
192GB
-
$5,553
Mid-Memory
-
384GB
-
$6,338
High Memory
-
768GB
-
$8,368
Very High Memory
-
1.5TB
-
$12,982
GPU Capable Compute Nodes (Up to 8
G
P
U
s
per Node)
-
80 Compute Slots, Intel Xeon Gold 6230@2.1GHz (Turbo up to 3.9GHz), DDR4-2933, 1TB SSD, 100Gbps InfiniBand EDR, 10Gb Ethernet
Low Memory
-
96GB
-
$7,423
Standard Memory
-
192GB
-
$7,768
Mid-Memory
-
384GB
-
$8,553
High Memory
-
768GB
-
$10,583
Very High Memory
-
1.5TB
-
$14,298
GPU Cards
-
The configurations above do not include GPU cards.
GPU Cards
Nvidia V100 32GB
-
$5,166
Nvidia 2080 Ti
-
$1,076
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