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AWS DL (Deep Learning) Containers: Rapidly Deploy Custom Machine Learning Environments

Published

2 years ago

April 11, 2019

AWS recently released a service called AWS DL Containers aimed at deep learning researchers. The service involves pre-configuring and validating Docker images and then pre-installing them with deep learning frameworks that can be used to deploy custom ML environments in a rapid manner.

AWS DL Containers currently support Apache MXNet and TensorFlow, but will keep adding more frameworks like Facebook’s PyTorch. Unveiled at the Santa Clara AWS Summit in March 2019, DL Containers can be used for inferencing and training purposes. They’re the company’s response to EKS and ECS users’ call to AWS to create a simple way to deploy TensorFlow workloads to the cloud.

Support for more services will follow, per AWS Chief Evangelist Jeff Barr. He also said that the images would be made available for free, and can be used pre-configured, or customized to suit the needs of the workload by adding packages and libraries.

There are several types of AWS DL Containers available, all of which are based on combinations of the following criteria:

Framework – TensorFlow or MXNet.
Mode – Training or Inference. You can train on a single node or on a multi-node cluster.
Environment – CPU or GPU.
Python Version – 2.7 or 3.6.
Distributed Training – Availability of the Horovod framework.
Operating System – Ubuntu 16.04.

How to Use Amazon Deep Learning Containers

The setup part is fairly simple. In the example shown by Barr, the user creates an ECS cluster with an instance like p2.8xlarge, as shown below:

$ aws ec2 run-instances –image-id ami-0ebf2c738e66321e6
–count 1 –instance-type p2.8xlarge
–key-name keys-jbarr-us-east …

Next check that the cluster is running and that the ECS Container Agent is active, and create a text file for task definition:

{
“requiresCompatibilities”: [
“EC2”
],
“containerDefinitions”: [
{
“command”: [
“tensorflow_model_server –port=8500 –rest_api_port=8501 –model_name=saved_model_half_plus_two_gpu –model_base_path=/models/saved_model_half_plus_two_gpu”
],
“entryPoint”: [
“sh”,
“-c”
],
“name”: “EC2TFInference”,
“image”: “841569659894.dkr.ecr.us-east-1.amazonaws.com/sample_tf_inference_images:gpu_with_half_plus_two_model”,
“memory”: 8111,
“cpu”: 256,
“resourceRequirements”: [
{
“type”: “GPU”,
“value”: “1”
}
],
“essential”: true,
“portMappings”: [
{
“hostPort”: 8500,
“protocol”: “tcp”,
“containerPort”: 8500
},
{
“hostPort”: 8501,
“protocol”: “tcp”,
“containerPort”: 8501
},
{
“containerPort”: 80,
“protocol”: “tcp”
}
],
“logConfiguration”: {
“logDriver”: “awslogs”,
“options”: {
“awslogs-group”: “/ecs/TFInference”,
“awslogs-region”: “us-east-1”,
“awslogs-stream-prefix”: “ecs”
}
}
}
],
“volumes”: [],
“networkMode”: “bridge”,
“placementConstraints”: [],
“family”: “Ec2TFInference”
}

The task definition is then registered using container specs like Mode and Environment, and the revision number is captured. In this case, 3:

The task definition and revision number are then used to create a service, after which you can navigate to the task in the console and find the external binding for port 8501.

After training the model on the function y=ax+b, with a being 0.5 and b being 2, inferences can be run for 1.0, 2.0 and 5.0 as inputs, and the predicted values will be 2.5, 3.0 and 4.5.

$ curl -d ‘{“instances”: [1.0, 2.0, 5.0]}’
-X POST http://xx.xxx.xx.xx:8501/v1/models/saved_model_half_plus_two_gpu:predict
{
“predictions”: [2.5, 3.0, 4.5
]
}

The example Barr gave was intended to show users how easy it is to perform inferencing using the new DL Containers service and a pre-trained model. The flexible nature of the service allows users to launch a training model, do the training and then run inferences.

The big cloud players are now introducing ready-to-deploy frameworks and hardware acceleration. Google announced TensorFlow 2.0 alpha for its GCP, and Microsoft and NVIDIA recently announced some key integrations:

“By integrating NVIDIA TensorRT with ONNX Runtime and RAPIDS with Azure Machine Learning service, we’ve made it easier for machine learning practitioners to leverage NVIDIA GPUs across their data science workflows,” according to Kari Briski, Senior Director of Product Management for Accelerated Computing Software at NVIDIA.

AWS Deep Learning Containers is the latest addition to the broad and deep list of services aimed at data scientists and deep learning researchers. They’re available through Amazon ECR at no cost, as is the case with most of their free services that only charge you for resource usage.

Source: https://1reddrop.com/2019/04/11/aws-dl-deep-learning-containers-rapidly-deploy-custom-machine-learning-environments/?utm_source=rss&utm_medium=rss&utm_campaign=aws-dl-deep-learning-containers-rapidly-deploy-custom-machine-learning-environments

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Blockchain

ETH Could Restart Its Rally As It Calmed Down At $1280: Price Analysis

Published

1 day ago

January 21, 2021

Republished by Plato

ETH could restart its rally as it was able to calm down at the $1280 level and tested the $1250 support zone against the US Dollar with the price consolidating and looking for a fresh increase in the near-term so let’s read more in the ethereum price news analysis today.

The price is now correcting lower from the $1385 but it is also above the 100 hourly simple moving average with a crucial contracting triangle forming with the support close to the $1275 on the hourly charts of ETH/USD. The pair will likely correct again but it is likely to remain bid above the $1250 support level. We already saw a downside correction in ETH below the $1350 and the $1300 support levels with the price spiking below the $1280 support level and the 100 hourly simple moving average. The pair tested the $1250 support zone and recovered above $1300 with a break above the $1350 resistance and close above the 100 hourly simple moving average but the price failed to surpass the $1400 resistance zone.

eth usd — Source ETHUSD on TradingView.com

The new high formed close to the $1388 level and the price is now correcting lower and it is testing the 50% fib retracement level from the upwards wave at $1251 low to $1388 high and there’s also a crucial contracting triangle that is forming with the support at the $1275 on the hourly charts of the pair. The triangle support is now close to the 76.4% fib retracement level from the upward wave from the $1251 swing low to the $1388 high and the triangle resistance is now near the $1360 and the $1365 level. The main resistance is now clear the $1385 and the $1400 level so a break above these levels could open the doors for a fresh new surge to the $1450 and the $1480 levels.

Image Courtesy of Resolute. Source ETHBTC on TradingView.

If ethereum struggles to remain stable above the $1300 it could correct further so the initial support on the downside is close to the $1280 level and the triangle trend line. The main support is forming close to the $1250 level and if the coin fails to stay above these levels, it could decline towards the $1180 and $1165 support levels. The MACD for the pair is moving into the bullish zone while the hourly RSI is now closing up on the 50 level. ETH could restart the rally soon, if it manages to go straight into the bullish zone.

DC Forecasts is a leader in many crypto news categories, striving for the highest journalistic standards and abiding by a strict set of editorial policies. If you are interested to offer your expertise or contribute to our news website, feel free to contact us at [email protected]

Source: https://www.dcforecasts.com/ethereum-news/eth-could-restart-its-rally-as-it-calmed-down-at-1280-price-analysis/

Blockchain

More Institutions Accumulate BTC Due To Fear Of Dollar-Linked Inflation

Published

1 day ago

January 21, 2021

Republished by Plato

More institutions accumulate BTC because of the fear of dollar-linked inflation which is why there’s a strong chance that BTC will hit $50,000 in the upcoming sessions. BTC could even shoot higher if more institutions start accumulating it again so let’s read more in today’s Bitcoin news.

The number one cryptocurrency that has a market capitalization above the one of Tesla or Facebook dropped lower from the record high of $42,000 but the drop prompted the richer traders and institutions to buy it at cheaper rates which led to further liquidity crunch against the limited supply of 21 million tokens. As a result, the BTC price is consolidating sideways and is now forming a structure that looks like a symmetrical triangle, and this pattern in the past formed when the price was forming higher lows and lower highs. In the meantime, the trading volume dropped and the price broke out of the direction of the trend no matter being downward or upward.

bitcoin liquidity — Bitcoins’s Liquidity Supply change. Source Glassnode

BTC’s previous trend was quite bullish so the crypto’s possibility of going through another bull run is higher on the breakout move out of the Triangle pattern which should lead the coin above $50,000. This is again because of this symmetrical triangle that we described above. The asset breaks out by about the maximum height between the upper and lowers trendlines of the pattern and in Bitcoin’s case, the height is around $14,000 which is a move that could take the BTC price above $50,000.

The price target looks like it could be achieved according to analysts that determine their market bias on the on-chain indicators. For example, the data analyst at Glassnode outlined BTC’s biggest liquidity depletion to date in the past weeks hinting that this is quite bullish for the cryptocurrency:

“Not only are funds being withdrawn from exchanges, but coins are continuously moving to strong hands,” they stated. “In the past 30 days, around 270,000 BTC moved to entities considered HODLers.”

btc breakout — Bitcoin eyes breakout from its Symmetrical Triangle pattern. Source BTCUSD on TradingView.com

The Glassnode charts are much more important than the price charts as BTC’s supply is now being withdrawn from all exchanges at a fast pace as Luke Martin added:

“Historically, bull cycles have ended AFTER liquid supply change flips positive. That flip has not happened yet.”

Part of the reason is a comparatively higher demand for the benchmark cryptocurrency amid the ongoing anti-inflation narrative. With Joe Bide’s inauguration, the prospects of more government spending are increasing in order to fight against the COVID-19 Pandemic. These fears of inflation pushed companies like Square and Microstrategy to exchange a portion of the dollar reserve for BTC but investors like Paul Tudor Jones and Stan Druckenmiller also invested a little in the cryptocurrency.

Source: https://www.dcforecasts.com/bitcoin-news/more-institutions-accumulate-btc-due-to-fear-of-dollar-linked-inflation/

Blockchain

Is Bitcoin’s Rise Written in the Stars?

Published

1 day ago

January 21, 2021

Republished by Plato

Just over 12 years ago, the Bitcoin revolution began. It was the 11th of January, 2009,
when Satoshi Nakamoto sent the first Bitcoin transaction to Hal Finney. Fast-forwarding to today, the cryptocurrency markets have exploded over the end of
2020 and beginning of 2021 and there have also been some crazy stories doing the
rounds. From theories put forward by internet-famous astrologists, to popular
trading exchanges’ Bitcoin supply running dry, we wonder where Bitcoin and Altcoins
are headed in 2021.

In less than one month, Bitcoin’s market value doubled from a new all-time high
above 18k to an even higher record at $40k on the 8th of January, 2021. For HODLers
and Bitcoin investors, this news was long-awaited and very, very welcome. Following
a 28% crash after reaching the new high, Bitcoin has been steadily recovering and
reached the $38k mark once again just a week later.

Naturally, crypto-sceptics did not see this coming. Could anyone have predicted just
how far this bull run would go? Even the exchange platform eToro could not keep up
with the exponential burst in demand for cryptocurrencies by traders looking to buy
Bitcoin over the weekend! Sadly, this also meant wider spreads for eToro’s 17 million
newly registered users. If this bull run persists, other crypto exchanges might even
follow suit.

Is now a good time to buy crypto?

The serious surge in crypto investors has understandably caused some concern
around its supply. But there is another way to go about it. By trading CFDs on
cryptocurrency pairs such as BTC/USD, traders can benefit from price movements by
going short or long on the asset. Plus, trading CFDs allows users to apply a good
amount of leverage to their trades in order to make the most of even the slightest
price movement.

The Word on the Web

As Bitcoin continued its impressive rise, there have been some wild theories
circulating the internet. Firstly, a self-described astrologer Maren Altman has been
explaining to her followers across Youtube, TikTok and Twitter that the price
movements of cryptos are written in the stars, providing them with astrology-based
advice on when to purchase BTC and other coins.

Speaking of altcoins, there are a few of them that always seem to make headlines
whenever Bitcoin turns bullish. One example is Dogecoin – you may have read Elon
Musk tweeting about it – which has risen 163% over the past month and has been
listed on two new exchanges. And as for celebrities riding the crypto bandwagon,
Lindsey Lohan has even appeared in a video promo for cryptocurrencies telling
viewers to drive their “Lambos to the moon”.

Say no to FOMO

From your next-door neighbour to the millionaires you see on TV, everyone is
becoming more interested in Bitcoin. According to Google trends data, web searches
for Bitcoin increased rapidly throughout the past month as the asset’s price rose.
Retail investment has also surged in recent weeks, as more investors turned towards
crypto.

Are you experiencing FOMO over Bitcoin’s recent bull run? Start trading CFDs at
Cedarfx.com today! With up to 1:100 leverage and a 0% Commission Account option,
CedarFX helps traders make the most of their funds.
Sign up at www.cedarfx.com.

Source: https://coinjournal.net/news/is-bitcoins-rise-written-in-the-stars/