SOLUTION BRIEF

TABLE OF CONTENTS
Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
Supermicro Ultra Servers and NVIDIA GPUs . . . . . . . . . . . . . . . . . . . 2
Addressing Customer Problems using Insights from Data . . . . . 2
Delivering the Infrastructure for Data Solutions . . . . . . . . . . . . . . 5
Enterprise Data Analytics / ML Applications (1) . . . . . . . . . . . . . . . 5
Data Preparation for Deep Learning Pipelines (2) . . . . . . . . . . . . . 6
Apache Spark 3.x with NVIDIA GPU Acceleration . . . . . . . . . . . . . . 6
Cloudera Data Platform Private Cloud Base 7.1.7 . . . . . . . . . . . . . 7
Red Hat Enterprise Linux . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Supermicro SuperCloud Composer . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
Supermicro Server Cluster running CDP PVC Base, Spark 3.x . 8
Conclusion, References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

SUPERMICROAs a global leader in high performance, high efficiency server
technology and innovation, we develop and provide end-toend green computing solutions to the data center, cloudcomputing, enterprise IT, big data, HPC, and embedded
markets. Our Building Block Solutions® approach allows us toprovide a broad range of SKUs, and enables us to build anddeliver application-optimized solutions based upon yourrequirements.

Executive SummaryEnterprises have embraced digital transformation to extract
insight from their data to improve business processes, increase
productivity with the same investment envelope, reduce costs,
and create a new offering to generate higher revenue and profit.
Across industry sectors, enterprises are collecting more data,
increasingly applying machine learning and deep learning toleapfrog their competition and grow faster.
Supermicro has partnered with Cloudera and NVIDIA to create aplatform consisting of Supermicro's Ultra Servers, Cloudera Data
Platform Private Cloud Base (CDP-PVC-Base), and NVIDIA RAPIDS
on GPU. Cloudera provides enterprise-level support for Apache
Spark 3.x and other open-source software. Supermicro Ultra
servers are powered by NVIDIA A30/NVIDIA A100 GPUs and NVIDIA
Networking to accelerate Apache Spark 3.x workloads
significantly – 5X faster than CPU based computing.

Supermicro, Cloudera, & NVIDIA Accelerate Enterprise Data Analytics August, 2021
©2021 Copyright Super Micro Computer, Inc. All rights reserved

1

SUPERMICRO SERVER CLUSTERSSUPPORT CLOUDERA DATA PLATFORM
PRIVATE CLOUD BASE AND SPARK 3.X
WITH NVIDIA GPU/RAPIDSACCELERATION

In addition, the platform can also prepare, cleanse, and feed data into
deep learning training pipelines. This solution brief shows the Apache
Spark 3.x cluster's benefits and critical components for deployment inenterprise hybrid data centers. The platform accelerates businessinsights from customer data to optimize the business and deliver higher
revenue.

Supermicro Ultra Servers and NVIDIA GPUs

Supermicro server cluster with NVIDIA A30/
NVIDIA A100 GPU delivers scalable machinelearning processing using Cloudera CDP Private
Cloud, NVIDIA RAPIDS, and Spark 3.x. The
Supermicro Super Cloud Composer manages
the cluster using Redfish v1.8 and IPMI.
GlossaryApache
Spark 3.x

Cloudera
CDP Private
Cloud Base
NVIDIA A30
NVIDIA A100
NVIDIARAPIDS

Supermicro
Ultra server

SuperCloud
Composer

Software to build resilient,scalable cluster for machinelearning, with programming
interface. Spark 3.x provides thelatest feature and performanceenhancement, adding GPU
acceleration
Software platform that delivers
integrated Apache Spark andother functions with enterprise
supportNVIDIA GPU for DL/ML, 3584 CUDA
cores, 24GB HBM2
NVIDIA GPU for DL/ML, 6912 CUDA
cores, 40/80GB HBM2eNVIDIA suite of software libraries,
built on CUDA-X AI, to execute
data science and analytics
pipelines using GPUs.
1U or 2U volume server
supporting GPU. Choice of 3rd Gen
Intel Xeon Scalable Processors
and 3rd Gen AMD EPYC™ CPUs.
Supermicro management
software providing a single-paneof-glass monitoring of serverclusters, in-band and out-of-bandcontrol, network OS booting.

Supermicro Ultra servers are high performance systems that support
GPUs. They support either 3rdGen Intel® Xeon® Scalable
processors or 3rd Gen AMD
EPYC™ processors, using thelatest PCI-E 4.0 interfaces andNVMe drives. Each server
SYS-220U-TNR
supports up to two NVIDIA
A30 or NVIDIA A100 GPUs,
which run NVIDIA RAPIDS to drive Apache Spark 3.x acceleration. Inaddition, high performance system memory supporting up to 8TB isavailable to support the in-memory processing for Apache Spark.
Additionally, a Supermicro 1U Ultra
server may be used as part of thecluster for tasks that are notaccelerated with the NVIDIA A30 or
NVIDIA A100 GPUs.
SYS-120U-TNR

Addressing Customer Problems using Insights from Data
Enterprises across all industries have seen the emerging power ofanalytics and machine learning from their data. For example, credit
analysts minimize loan loss provision in the finance industry using
analytics and machine learning based on customer data, macroeconomic information, and transaction data. Likewise, in media
entertainment, marketers can better maneuver through GDPR rules byapplying analytics and machine learning to the customer, location, andcountry-specific information. These examples are early indicators of
how machine learning can improve business results.

Supermicro, Cloudera, & NVIDIA Accelerate Enterprise Data Analytics August, 2021
©2021 Copyright Super Micro Computer, Inc. All rights reserved2

Table 1 shows examples of different industry sectors, their specific data, and the consequential results from applying machinelearning and deep learning to the data.
As part of their digital transformation initiatives, enterprises are collecting more data. Data come from customer interactions,industry information, databases, and even sensors. In addition, enterprises now adopt machine learning and deep learning, as
these technologies have matured for business deployment.
Cloudera has evolved its offering for machine learning pipelines in the past decade for enterprises. Cloudera Data PlatformPrivate Cloud Base's (CDP-PVC-Base) broad capability enables implementing the entire data pipeline, from data collection using
Kafka, to retention and access on unstructured and structured data, to data analytics running on Apache Spark 3.x.
CDP-PVC-Base can also provide data preprocessing to front-end the deep learning pipeline using deep neural networks runningin intensive GPU clusters. Using data processing algorithms in Apache Spark 3.x in CDP-PVC-Base, enterprises can optimallyclean and prepare data for deep learning training. The resulting deep learning inference models then process new incoming
data to make predictions or decisions. Thus, the deep learning system enhances business operations for the enterprise.
Supermicro offers Ultra server clusters running CDP-PVC-Base and NVIDIA GPUs to accelerate Apache Spark 3.x, delivered with
Cloudera software. In addition, the Cloudera Data Platform Private Cloud software has incorporated the NVIDIA RAPIDS™
libraries, which enables compute acceleration on the NVIDIA GPU for components of Spark 3.x. Supermicro's Ultra Server
Clusters support NVIDIA A30/NVIDIA A100 GPUs, and they are validated for performance, manageability, security, and scalability
backed by enterprise-grade support. This platform enables enterprises to increase revenue and productivity by gaining insightsfrom their data.

Supermicro, Cloudera, & NVIDIA Accelerate Enterprise Data Analytics August, 2021
©2021 Copyright Super Micro Computer, Inc. All rights reserved3

Industry

Selective Data

Selective Results

Finance

Asset prices, policies, call recordings, compliant
logs, claims, economics, credit, loan, regulatory
information.

Credit risk analysis, fraud detection, return onequity

Telecom

Subscribers, cells, connections

Network quality, OSS, Geospatial

Healthcare

Confidential patient records

Patient flow forecasting, nurse staffing levels

Life Sciences

Clinical trials, reports

Health diagnosis, data extraction automation

MediaEntertainment

Mobile data, search data, customer viewing
dataAdvertising fraud detection, Enforcing GDPR,
User behavior analytics

Transportation

Public transportation operation data, passenger
ride data

Efficient operation of a transportation system

TravelHotel data and pricing

Customer trip planning, Customer
recommendations

Public Sector

Intelligence data, public records data (tax,welfare claims, etc.)

Crime prevention, cyberattack prevention,
reduced fraud costs

Retail,E-commerceMerchant and user interactions

Targeted offers, enhanced customer experience

EnergySensor data, consumption data

Optimal energy generation in Smart Grid

Manufacturing

Picture and video data, equipment data

Efficient manufacturing flow

Others

Large amount of data, time-series data

Trend identification, Outlier detection, Process
improvements, cost optimization

Table 1. Example results of machine learning from selective data in different industries.

Supermicro, Cloudera, & NVIDIA Accelerate Enterprise Data Analytics August, 2021
©2021 Copyright Super Micro Computer, Inc. All rights reserved4

Delivering the Infrastructure for Data Solutions
Cloudera CDP-PVC-Base and Apache Spark 3.x deployed on a cluster of
NVIDIA GPU-accelerated servers offer a very scalable data analytics solution
for terabytes to petabytes of continuous data. Furthermore, Supermicrooffers the latest state-of-the-art Intel or AMD CPUs and NVIDIA GPUs with thebest price/performance efficiency. The server reliability with built-in
redundancies ensures minimal cluster downtime.
Supermicro's Super Cloud Composer (SCC) makes it easy to manage serverclusters and deploy them in the hybrid data center. SCC monitors the servers, network, and storage from a single pane of glass
interface. In addition, Cloudera offers a simple means to deploy the CDP-PVC-Base suite onto the servers. Overall, hardware,software, cluster setup is well organized and ensure correct cluster operations.
For enterprise level support, Supermicro offers 24x7 hardware support, while Cloudera provides enterprise class software
support.
This cluster delivers many applications to process customer data. This solution brief presents two of these applications:(1) Data analytics features in Apache Spark 3.x, delivered by Cloudera CDP Private Cloud-Base.
(2) Data preparation using Apache Spark 3.x and CDP Private Cloud-Base capabilities to process the incoming data to
feed into another AI cluster to perform Deep Learning (DL) training. The DL training produces AI models, which run inDL inference to make predictions or decisions on new incoming data.

Enterprise Data Analytics / Machine Learning Applications (1)Data analytics applies statistical and mathematical algorithms to extract insights from data. Be it linear regression on timeseries data or feature extraction from images or voice or complex data, these algorithms enable fast insights fromcontinuously available data to businesses in various industries.

Supermicro, Cloudera, & NVIDIA Accelerate Enterprise Data Analytics August, 2021
©2021 Copyright Super Micro Computer, Inc. All rights reserved5

Cloudera CDP PVC-Base includes many data analytics capabilities, including:
••
•
•
•

Regression to find trends
Classification and Clustering to put data in different buckets
Collaborative filtering to build recommender systems
Frequent pattern mining to analyze large scale dataset
Model selection and tuning to find the best model or parameters

By running data through these and additional algorithms in the Cloudera / Apache Spark cluster, customers can quickly get
great insights and make efficient business decisions.

Data Preparation, Feature Extraction for Deep Learning Pipelines (2)Deep Learning (DL), using neural network architectures, often enables deeper insight than machine learning. This does require
additional technologies, which involve a GPU-based training server cluster and inference servers.
When data scientists in an enterprise determine that neural networks or other deep learning algorithms could get even moreinsights from the available data, Cloudera/Apache Spark has mechanisms to prepare the data to pipeline into DL training
clusters. These include the following. Data scientists can combine these programmatically to perform high performance datapreparation:••••

TF-IDF for word frequency
Word2Vec for word embedding
Feature transformers to index, scale, convert data
Feature selectors to select features using statistical rules

Whether the data consist of text, images, or other forms, customers can set up data preparation and extraction to pre-processdata to pipeline into DL training, ensuring quick and efficient operations. CDP PVC-Base uses GPUs to accelerate SQL and Data
Frame API processing, enabling faster data preparation.

Apache Spark 3.x with NVIDIA GPU Acceleration
Apache Spark 3.x provides the integrated components for easy
deployment of tens to thousands of servers to run scalable in-memory
graph processing and computation. Apache Spark 3.x has improved
significantly from previous versions. Now, CDP PVC-Base with Apache
Spark 3.x supports NVIDIA GPU acceleration natively. CPD PVC-Baseuses the GPUs to accelerate SQL, Data Frame API processing. Using asingle GPU, we see five times or more performance speedup over CPUbased systems. Using multiple GPUs, we see over 43X performancespeedups. NVIDIA and Cloudera have worked together to incorporate
the NVIDIA RAPIDS libraries, using GPUs, into the CDP PVC-Basoftware stack to achieve these performance speedups.

Supermicro, Cloudera, & NVIDIA Accelerate Enterprise Data Analytics August, 2021
©2021 Copyright Super Micro Computer, Inc. All rights reserved6Supermicro delivers Ultra servers with NVIDIA A30 or NVIDIA A100 GPUs. When adding these GPU servers to a running CPUbased Cloudera cluster, CDP PVC-Base automatically incorporates the GPU systems to accelerate the Apache Spark 3.x
workloads, especially for those running Spark SQL and Data Frame APIs.

Cloudera Data Platform Private Cloud-Base 7.1.7
Cloudera Data Platform Private Cloud Base provides an integrated
platform to run data streaming, storage, and data science andmachine learning in server clusters. The software can be easily
deployed onto a cluster of servers and be managed using built-in
in-band management. In addition, both public cloud and hybrid
data center server clusters come with enterprise level support.
CDP PVC-Base 7.1.7 incorporates Apache Spark 3.x with NVIDIA
RAPIDS GPU acceleration to deliver over five times more
performance speedup over CPU based clusters.

Red Hat Enterprise LinuxRed Hat Enterprise Linux (RHEL) is the operating system supporting Cloudera Data
Platform Private Cloud Base. RHEL provides enterprise level support for the operating
environment that enables reliable and scalable operations in each Supermicro Ultra
server.

Supermicro SuperCloud Composer
Supermicro SuperCloud Composer (SCC) provides monitoring, management, andserver operating systems deployment for server clusters. Using out-of-band IPMI
and Redfish management, SCC monitors the health and operation of each serverin the cluster. While server clusters are usually set up with multiple networks tosupport out-of-band, in-band, and data networks, SCC configures the network IPaddresses on the servers. SCC can also deploy operating systems images onto one
or all the servers. This makes the management and deployment of racks of servers
much more manageable.

Supermicro, Cloudera, & NVIDIA Accelerate Enterprise Data Analytics August, 2021
©2021 Copyright Super Micro Computer, Inc. All rights reserved7Supermicro Server Cluster running Cloudera Data Platform Private Cloud Base and Spark 3.x
The starting base Cloudera Data Platform
Private Cloud Base has 10 Ultra servers(either 1U or 2U). Many more servers can be
added to scale the cluster depending on theamount of data and computing needed.
There are options for high availability anddata storage. To accelerate Spark Apache
3.x operations, we can add Supermicro Ultra
servers with NVIDIA A30 or NVIDIA A100. The
Cloudera cluster automatically incorporates
additional servers to scale the cluster
performance. Supermicro is providing areference architecture for this cluster in a
separate document.

Conclusion
In collaboration with Cloudera and NVIDIA, Supermicro is delivering high performance server clusters supporting GPUs toprovide enterprise level support to customers to turn their data into valuable insights to run their business. The GPU
acceleration provides five times and more speedup over CPU operations for Apache Spark 3.x jobs. The CPU-based servers
support the other Cloudera streaming, security, governance, and storage functions. Supermicro's SuperCloud Composermonitors the server hardware operations to provide high availability. SCC also deploys the appropriate operating systems tothe servers in the cluster, while Cloudera offers a simplified means to deploy the Cloudera applications. Together, Supermicro,NVIDIA, and Cloudera deliver high performance clusters to process customer data into valuable insights to run their business.
The entire solution comes with enterprise level support.
Contact your Supermicro Sales Team for more information.

References
1. https://developer.nvidia.com/blog/accelerating-apache-spark-3-0-with-gpus-and-rapids/
2. https://docs.cloudera.com/documentation/enterprise/6/6.3/topics/spark.html
3. https://www.infoq.com/articles/deep-learning-apache-spark-nvidia-gpu/
4. https://www.supermicro.com/solutions/Solution-Brief_SuperCloud_Composer.pdf
5. https://www.supermicro.com/en/products/ultra/
6. https://www.nvidia.com/en-us/data-center/products/a30-gpu/
7. https://www.nvidia.com/en-us/data-center/a100/

Supermicro, Cloudera, & NVIDIA Accelerate Enterprise Data Analytics August, 2021
©2021 Copyright Super Micro Computer, Inc. All rights reserved

8