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Is your IT Infrastructure Ready for Machine Learning & Artificial Intelligence?
Hoseb Dermanilian, EMEA BDM, NetApp
Arnaud BASSALER, CSE, Cisco Systems
BRKPAR-2955
• Introduction
• AI, Machine Learning and Big Data
• What Makes your IT Infrastructure AI Ready?
• The Data Management Challenge
• The Compute Power Challenge
• Why NetApp & Cisco
• Conclusion
Agenda
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
A Very Quick Overview: AI, ML and Deep Learning
• The explosion of AI due to:
• Infinite storage, flood of data and flexible data management features
• Availability of GPUs for parallel processing
• Artificial Intelligence: Machine exhibited human intelligence
• Machine Learning: State of the art AI
• Deep Learning: Enabling advanced ML
BRKPAR-2955 5
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Big Data and the Rise of Deep Learning
• The convergence of big data with AI
• The availability of large datasets provide meaningful learning and results
• Three critical ways in which big data is now empowering AI:
• Big Data Technology: processing and storing large quantities of data efficiently
• Availability of large data sets
• Scale up algorithms (deep learning)
BRKPAR-2955 6
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
What Makes your IT Infrastructure AI Ready?
• Different stages with different infrastructure requirements:
• Flexible and Agile
• Able to Manage Data Efficiently
• Accommodate large and varying volumes and types of Data
• Processing Power / Time
• Accept data from different data sources
• Manage data lifecycle (Cloud and On-Premise)
• Scale non-disruptively
BRKPAR-2955 8
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
The Flow of Data in a Deep Learning Pipeline
BRKPAR-2955 10
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Step1: Eliminate Challenges at the Edge
• Large number of ingestion points
• Amount of data generated
• Apply edge level analytics and pass on selective data
• To do this:
• We require high-performance, ultra-low-latency storage at the edge
• Deploy NetApp ONTAP Select near the edge to:
• Edge analytics and reduce the amount of data needs to be sent to core
• Replicate data efficiently reducing bandwidth
• Utilize Storage Efficiency features to further reduce amount of data sent over
BRKPAR-2955 11
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Step2: Eliminate Challenges at the Core
• Data Lakes
• Performance, number of copies, small-file workloads
• Training Cluster:
• Feeding data from the lake to the training cluster
• Deployment:
• Ultra-low latency
• Overall:
• Separate clusters for each stage
• Copy data from one stage to another
BRKPAR-2955 12
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Step3: Eliminate Challenges in the Cloud
BRKPAR-2955 13
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
One More Look into The Data Lake
• On-demand analytics with hybrid cloud and multi-cloud deployments
• Rapid provisioning of clusters for test/dev environments
• Efficient backup and replication of Hadoop data
• Automated data tiering to the cloud
BRKPAR-2955 14
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
AI Sweeping Across Industries
Internet Services Healthcare Media & Entertainment Security & Defense Retail
➢ Cancer cell detection
➢ Diabetic grading
➢ Drug discovery
➢ Medical research
➢ Theft detection
➢ Auto checkout
➢ Targeted marketing
➢ Face recognition
➢ Video surveillance
➢ Cyber security
➢ Video captioning
➢ Content based search
➢ Natural language processing
➢ Virtual and augmented reality
➢ Image/Video classification
➢ Speech recognition
➢ Virtual and augmented reality
BRKPAR-2955 16
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
AI : Consumption vs Enablement
UCS
C240 M5
S
X
NVME SSD
800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
XX
NVME SSD
800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
821 76543
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
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SATA HDD
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2 TBHD2T7KL6GN
SATA HDD
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SATA HDD
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SATA HDD
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SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
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2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
14131211109 201918171615 24232221
BRKPAR-2955 17
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Cisco GPU Accelerated Data Center
Accelerated Analytics & Databases
Artificial Intelligence
GPU-Accelerated DV
Real-Time and Location AnalyticsWindows 10
Virtual Workstations
Deep Learning
Machine Learning
Unified Computing Systems
Virtualization Accelerated Compute
BRKPAR-2955 18
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
What is Accelerated Compute?
GPU-accelerated computing is the use of a graphics processing unit (GPU) together with a CPU to accelerate deep learning, analytics, and engineering applications. ... They play a huge role in accelerating applications in platforms ranging from artificial intelligence to cars, drones, and robots.
For Cisco it encompasses two categories:
1. Artificial Intelligence - Deep Learning
2. Accelerated Analytics - Databases
BRKPAR-2955 19
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Cisco GPUs for AI
BRKPAR-2955 20
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Training and Inference
BRKPAR-2955 21
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Cisco UCS AI Offerings
Training
InferencingUCS
C220 M5
2 TB
HD2T7KL6GN
SATA HDD
X
2 TB
HD2T7KL6GN
SATA HDD
X
1
6
S
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3
9
4
10
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800 GB
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XNVME SSD
800 GB
NVMEHWH800
UCS
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S
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800 GBNVMEHWH800
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SATA HDD
XX
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800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
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2 TBHD2T7KL6GN
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821 76543
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SATA HDD
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SATA HDD
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SATA HDD
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SATA HDD
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SATA HDD
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SATA HDD
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SATA HDD
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2 TBHD2T7KL6GN
SATA HDD
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2 TBHD2T7KL6GN
SATA HDD
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SATA HDD
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X
14131211109 201918171615 24232221
C220 + 2xP4• UCS Inferencing appliance
for Edge
C240 + 4xP4 or 2xP40• More inferencing GPU with
more storage (DC)
UCS
C480 M5
X
NVME SSD
800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
XX
NVME SSD
800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X X
NVME SSD
800 GBNVMEHWH800
X
NVME SSD
800 GBNVMEHWH800
X
NVME SSD
800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
XX
NVME SSD
800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X X
NVME SSD
800 GBNVMEHWH800
X
NVME SSD
800 GBNVMEHWH800
ReW ritabl eRECORDERM U L T I
DVD+ReWritable
S
X
X
UCS C480 M5 (PCIe)• 6 x P100/V100 GPU’s
C240 M5 + OSS
EB3600 (PCIe)• 9 x P100/V100 GPU’s
UCS
C240 M5
S
X
NVME SSD
800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
XX
NVME SSD
800 GBNVMEHWH800
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
821 76543
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
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2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
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2 TBHD2T7KL6GN
SATA HDD
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2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
2 TBHD2T7KL6GN
SATA HDD
X
14131211109 201918171615 24232221
BRKPAR-2955 22
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
Because of Flexpod!
A pre-validated, flexible platform that features:
• Cisco Unified Computing System
• Cisco Nexus Networking
• NetApp Storage
• Centralized Management with Automation
© 2018 Cisco and/or its affiliates. All rights reserved. Cisco Public
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BRKPAR-2955 26