© 2014 IBM Corporation
Platform Computing
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IBM Platform Computing Cloud Service Ready to use Platform LSF & Symphony clusters in the SoftLayer cloud February 25, 2014
© 2014 IBM Corporation
Platform Computing
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Agenda
v Mapping clients needs to cloud technologies
v Addressing your pain points
v Introducing IBM Platform Computing Cloud Service
v Product features and benefits
v Use cases
v Performance benchmarks
© 2014 IBM Corporation
Platform Computing
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HPC cloud characteristics and economics are different than general-purpose computing
• High-end hardware and special purpose devices (e.g. GPUs) are typically used to supply the needed processing, memory, network, and storage capabilities
• The performance requirements of technical computing and service-oriented workloads means that performance may be impacted in a virtualized cloud environment, especially when latency or I/O is a constraint
• HPC cluster/grid utilization is usually in the 70-90% range, removing a major potential advantage of a public cloud service provider for stable workload volumes
HPC Workloads Recommended for Private Cloud
HPC Workloads with Best Potential for Virtualized Public & Hybrid Cloud
Primary HPC Workloads
© 2014 IBM Corporation
Platform Computing
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IBM’s HPC cloud strategy provides a flexible approach to address a variety of client needs
Evolve existing infrastructure to
HPC Cloud to enhance responsiveness,
flexibility, and cost effectiveness.
Enable integrated approach to improve
HPC cost and capability 60%
Access additional HPC capacity with
variable cost model
Private Clouds
Hybrid Clouds
Public Clouds
Based on HPC Cloud’s potential impact, organizations are evolving their infrastructures to enable private cloud deployments, exploring hybrid clouds, and considering public clouds.
© 2014 IBM Corporation
Platform Computing
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Are you experiencing any of these pain points?
• Unable to meet business objectives (delay to market, etc.) • Existing resources insufficient to meet peek compute demand
– Long run times on existing cluster or grid – No access to local technical computing resources (workstation users)
• Technical resources expensive and time consuming to acquire • The skills/staff to architect and manage a technical computing infrastructure can
be difficult to acquire
-
10,000
20,000
30,000
40,000
50,000
1 4 7 10 13 16 19 22
Planned Daily Cycle (24 x 365)
Financial Services
0 200 400 600 800
1000 1200 1400 1600
April May June
Planned Project
Life Sciences
© 2014 IBM Corporation
Platform Computing
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IBM Platform Computing Cloud Service Making the cloud work for you
Build • Complete, ready to run
clusters in the cloud • Add additional capacity
in hours instead of months
Manage • Seamless workload
management, on-premise and in the cloud
• Transparent user experience
Support • 24X7 cloud operation
support • Access to technical
computing expertise when you need it
Protect • Data encryption,
dedicated physical machines and network
• Security through physical isolation
Complete, end to end dynamic cloud solution
© 2014 IBM Corporation
Platform Computing
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Ready to use Platform LSF & Platform Symphony clusters in the cloud
IBM Platform Computing Cloud Service (SaaS)
IBM Platform LSF IBM Platform Symphony
SoftLayer, an IBM Company Infrastructure
24X7 CloudOps Support
Client and ISV Applications
© 2014 IBM Corporation
Platform Computing
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Dedicated physical and virtual machine infrastructure as a service
• 13+ data centers • 17 network PoPs • Global private network • Bare metal and virtual machines
190,000+ SERVERS
21,000+ CUSTOMERS
22,000,000+ DOMAINS
© 2014 IBM Corporation
Platform Computing
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Workload I/O intensity
• SoftLayer’s architecture outperforms by >50% equivalent AWS instances for high I/O workloads
Control (APIs, hardware / network configurability)
• SoftLayer offers hundreds of hardware configurations vs. 14 for AWS • ~2,000 APIs for SoftLayer vs. ~60
for AWS and none for RAX
Integrated platform of multiple architectures
• Unified integration & control panel for multiple cloud architectures • RAX requires paid bridge,
different control interfaces
Ready to use Platform LSF & Platform Symphony clusters in the cloud
Low intensity
workloads
Low degree of control and
customization
AWS IBM
High intensity
workloads
High degree of control and
customization
Single platform Seamless integration
DIFFERENTIATOR RATING IBM ADVANTAGES
RAX
© 2014 IBM Corporation
Platform Computing
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Non-shared physical machines for added security and performance
• Dedicated and isolated compute environment
• All machine instances are dedicated to the client
• Each cluster is isolated on a VLAN
• Only the VPN gateway has an addressable interface
• All customer data at rest is encrypted on shared file systems
• When machines instances are decommissioned the disks are scrubbed using DoD approved methods
© 2014 IBM Corporation
Platform Computing
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Optimal performance for technical computing apps
Industrial Manufacturing Benchmark – Structural Mechanics
EDA Benchmark (IBM-MESA)
Note: Benchmark results were obtained by IBM and have not yet been externally audited or validated.
© 2014 IBM Corporation
Platform Computing
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Run and supported by dedicated, 24X7 HPC Cloud Operations Team
CloudOps functions • Pre-provisioning: Provide guidance to client on how to enable VPN, multi-cluster settings &
security settings on the client on-premise environment • One time setup testing: Extensive testing of the cluster prior to release to the client • Extensive testing of the cluster on every event of flex-up prior to release to the client • Email alerts prior to flex-down & cluster shutdown operations • Email alerts in case of any overage (compute hours, download bandwidth) • Provide billing details of monthly usage including overage details • Provide support under IBM SLA by experts highly experienced in Platform Computing
products
Value: quality, peace of mind & minimum disruption to business • Extensive quality checks ensures minimum loss of usage hours & disruptions • Proactive alerts ensures that in-progress critical jobs are not killed in case of Flex-down &
Cluster Shutdowns and Overages • Highly trained & experienced Support ensures smooth on-boarding and minimize
disruptions
© 2014 IBM Corporation
Platform Computing
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Industry-leading workload management
• 20 years managing distributed scale-out systems with 2000+ customers in many industries
• High performance workload management combined with intelligent resource scheduling engine
• Unmatched scalability (small clusters to global grids) and production-proven reliability
• Heterogeneous – manages System x and Power plus 3rd party systems, virtual and bare metal, accelerators / GPU, cloud, etc.
• Shared services for both compute and data intensive workloads
• Integrated solutions with vertical reference architectures
23 of 30 largest
commercial enterprises
Over 5M CPUs under management
60% of top financial services
companies
© 2014 IBM Corporation
Platform Computing
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IBM Platform LSF Overview Powerful workload management for demanding, distributed and mission-critical high performance computing environments.
Key Capabilities • Powerful
- Policy and resource-aware scheduling - Resource consolidation for optimal performance - Advanced self-management
• Flexible - Heterogeneous platform support - Policy-driven automation - CLI, web services, APIs
• Scalable - Thousands of concurrent users and jobs - Virtualized pool of shared resources - Flexible control, multiple policies
Client Benefits • Optimal utilization: reduced infrastructure cost • Robust capabilities: improved productivity • High throughput: faster time to results
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© 2014 IBM Corporation
Platform Computing
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IBM Platform Symphony
Overview Low-latency grid management platform for distributed computing and analytics with sophisticated resource sharing
Key Capabilities • Accelerates service-oriented applications • Extreme app scalability and throughput with very low
latency • Compute and data-intensive applications on a single
platform • Sophisticated, hierarchical resource sharing • Open and flexible: choice of OS, frameworks and
languages
Client Benefits • Increase performance and analytic result quality • Reduces IT costs - increase utilization, simplify
application onboarding, reduce administration costs
Low Latency / High throughput Sub-millisecond, 17,000 tasks per second
Large Scale 10k cores per application, 40k cores per grid
Efficient shared services Heterogeneous & Open
Linux, Windows, AIX, C/C++, C#, Java, Excel, Python, R
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© 2014 IBM Corporation
Platform Computing
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Use case 1 – hybrid cluster
The problem • Existing resources cannot meet peak demand • Resources are expensive and time consuming to acquire • Skills to architect and manage clusters are difficult to find • Fixed or reduced budgets • On-premise constraints in space, cooling and power
The solution • Fully functioning IBM Platform LSF or Symphony clusters are
provisioned on the SoftLayer cloud and connected to the on-premise cluster, expanding capacity as needed
• Leverage MultiCluster capability for managed forwarding of jobs from on premise cluster to off premise cluster
The Value • Access to additional compute capacity on a temporary basis as needed • Near-zero wait times • Reduce costs by paying for only what is used • Pay for additional capacity as an operating expense • Fully supported, end-to-end solution, from the on-premise to the on-cloud clusters • Expected and reliable performance from running technical computing workloads on physical machines • Transparent access to cloud resources, the end user experience does not change
© 2014 IBM Corporation
Platform Computing
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Use case 2 – stand-alone cluster in the cloud
The problem • New and emerging need for technical computing • Skills to architect and manage clusters are difficult to find • Resources are expensive and time consuming to acquire • Inconsistent demand does not justify the investment
The solution • Fully functioning Platform LSF and Symphony clusters are
provisioned on the SoftLayer cloud providing resources as needed
The value § Market-leading Platform LSF and Platform Symphony software
§ Access to technical computing resources on a temporary basis without the need to acquire, install and configure the infrastructure and cluster software
§ Keep costs low by paying for only what is used
§ Pay for capacity as an operating expense
§ Fully supported solution
§ Expected and reliable performance from running workloads on physical machines
© 2014 IBM Corporation
Platform Computing
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Is IBM Platform Computing Cloud Service a good fit for you?
Business pain points • And you experiencing lost profit due to missed deadlines? • Do you experience pressure to convert your compute environment capital expense to
operational expense? • Have you ever missed a deadline or delayed a project because technical computing
resource procurement took too long ?
Technology pain points • Do your users ever scale back their analyses to lower fidelity or less accuracy in order to fit
them into the local compute environment or to a time window? • Do you regularly, occasionally, or permanently have fewer resources (CPUs, disk, memory,
etc) than you would like to have to service the user’s compute demand? • Do you experience a large variance in compute resource utilization? • Have you reached, or will you reach the capacity of your datacenter(s), and do you need a
plan to grow beyond that capacity ? • Are your customers asking you for cloud licenses for Platform LSF or Platform Symphony?
© 2014 IBM Corporation
Platform Computing
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IBM Platform Computing Cloud Service Making the Cloud Work for You
Unmatched Expertise Analytics, Technical Computing,
Software, Services and ISV Partnerships
IBM Hybrid Cloud
Consolidation Supporting heterogeneous IBM and non-IBM infrastructure
Cloud Leadership Expertise from
Client Engagements
powered by
On SmartCloud
Unmatched Capabilities Policy-driven Workload
Management
On Premise
Software & Systems
© 2014 IBM Corporation
Platform Computing
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SoftLayer and Amazon EC2 Products tested
NAME
IaaS Provider
CPU Cores Memory (GB)
Disk Space (GB)
Physical / Virtual
Hourly Rate (USD)
SL PM So'Layer 16 64 1000[1] Physical $1.85[2]
SL VM So'Layer 8 8 500[3] Virtual $0.88
SL PM (ded) So'Layer 16 64 1000[1] Physical $3.83[5]
EC2 CC2
Amazon EC2 (CC2)
32 60.5 3360 Virtual $2.40[4]
EC2 2XL
Amazon EC2 (c1.xlarge)
8 7 840 Virtual $0.58
SL Physical Machine Intel(R) Xeon(R) CPU E5-‐2650 0 @ 2.00GHz SL Physical Machine (dedicated) Intel® Xeon® CPU E5-‐2690 0 @ 2.90GHz SL Virtual Machine Intel(R) Xeon(R) CPU E5-‐2650 v2 @ 2.60GHz Amazon CCI2 Intel(R) Xeon(R) CPU E5-‐2670 0 @ 2.60GHz Amazon 2XL Intel(R) Xeon(R) CPU E5-‐2650 0 @ 2.00GHz
© 2014 IBM Corporation
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Memory Bandwidth
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
SL PM SL VM EC2 CCI2 EC2 2XL SL PM (ded)
STREAM (higher is better)
COPY
SCALE
ADD
TRIAD
0.00
500.00
1,000.00
1,500.00
2,000.00
2,500.00
3,000.00
3,500.00
4,000.00
4,500.00
SL PM SL VM EC2 CCI2 EC2 2XL SL PM (ded)
STREAM Price Performance (higher is better)
COPY
SCALE
ADD
TRIAD
© 2014 IBM Corporation
Platform Computing
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CPU Performance
0
100
200
300
400
500
600
700
800
SL PM SL VM EC2 CCI2 EC2 2XL SL PM (ded)
Elap
sed
Tim
e
SuperPI (lower is better)
0.00
2.00
4.00
6.00
8.00
10.00
SL PM SL VM EC2 CCI2 EC2 2XL SL PM (ded)
thro
ughp
ut p
er d
olla
r
SuperPI Price-Performance (higher is better)
© 2014 IBM Corporation
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Network Bandwidth
1
10
100
1000
10000
100000
1 10 100 1000 10000 100000 1000000 10000000
Ban
dwid
th (M
bits
/s)
Message Size (Bytes)
openMPI
SLVM
EC2 2XL
EC2 CCI2
SL PM
SL PM Dedicated
© 2014 IBM Corporation
Platform Computing
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Network Latency
0
20
40
60
80
100
120
SL VM MPI 2 node EC2 2XL MPI 2 node EC2 CCI2 MPI 2 node
SL PM MPI 2 node SL PM (ded) MPI 2 node
openMPI Latency (lower is better)
© 2014 IBM Corporation
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Input / Output Performance
0
50000
100000
150000
200000
250000
300000
350000
0 1 2 3 4 5
kB/s
ec
I/O file size (factor of memory size)
I/O Bandwidth - WRITE (higher is better)
SL VM Write
EC2 2XL Write
EC2 CCI2 Write
SL PM Write
SL PM Ded Write
0
50000
100000
150000
200000
250000
300000
350000
400000
0 1 2 3 4 5
kB/s
ec
I/O file size (factor of memory size)
I/O Bandwidth - READ (higher is better)
SL VM Read
EC2 CCI2 Read
EC2 2XL Read
SL PM Read
SL PM Ded Read
© 2014 IBM Corporation
Platform Computing
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Software Compilation
0
100
200
300
400
500
600
700
800
SL VM SL PM EC2 2XL EC2 CCI SL PM Ded
Elap
sed
Tim
e (s
)
Software Compile Performance (lower is better)
0.00
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
SL VM SL PM EC2 2XL EC2 CCI SL PM Ded
Run
s / $
Software Compile Price-Performance (higher is better)
© 2014 IBM Corporation
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Life Science (BWA)
SL PM (ded) SL PM SL VM EC2 CCI2 EC2 2XL Series1 20846.481 26509.368 25897.44 22442.7 37491
0
5000
10000
15000
20000
25000
30000
35000
40000
Elap
sed
time
(sec
)
Life Sciences Benchmark (BWA) (lower is better)
SL PM (ded) SL PM SL VM EC2 CCI2 EC2 2XL Series1 22.21 7.79 6.33 14.96 6.04
0.00
5.00
10.00
15.00
20.00
25.00
$ / r
un
Life Sciences Benchmark (BWA) Price Performance (lower is better)
© 2014 IBM Corporation
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EDA Benchmark (IBM-MESA)
0
500
1000
1500
2000
2500
3000
3500
SL PM (ded) SL PM SL VM EC2 2XL EC2 CCI2
Elap
sed
Tim
e (s
ec)
EDA - IBM Mesa (lower is better)
0.00
0.50
1.00
1.50
2.00
2.50
SL PM (ded) SL PM SL VM EC2 2XL EC2 CCI2
Run
s / $
EDA - IBM Mesa - Price-Performance (higher is better)
© 2014 IBM Corporation
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Provisioning Time
1
10
100
1000
10000
100000
SL PM SL VM EC2 CCI2 EC2 2XL SL PM Ded
Provisioning Time (sec) (lower is better)
© 2014 IBM Corporation
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Industrial Manufacturing – Structural Mechanics
1
3
5
7
9
11
13
0 2 4 6 8 10 12 14 16
Spee
dup
(rel
ativ
e to
EC
2 2X
L)
CPUs
One Node - S4D
SL PM
EC2 CCI2
SL VM
EC2 2XL
SL PM (ded) 1
2
3
4
5
6
7
0 2 4 6 8 10 12 14 16 Spee
dup
(rel
ativ
e to
EC
2 2X
L)
CPUs
One Node - S6
SL PM
EC2 CCI2
SL VM
EC2 2XL
SL PM (ded)
1 3 5 7 9
11 13 15 17 19
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 Spee
dup
(rel
ativ
e to
EC
2 2X
L)
CPUs
Two Nodes - S4D
SL PM
EC2 CCI2
SL VM
EC2 2XL
SL PM (ded) 1
2
3
4
5
6
7
8
9
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Spee
dup
(rel
ativ
e to
EC
2 2X
L)
CPUs
Two Nodes - S6
SL PM
EC2 CCI2
SL VM
EC2 2XL
SL PM (ded)
© 2014 IBM Corporation
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Industrial Manufacturing – CFD
0
2
4
6
8
10
12
14
16
18
1 3 5 7 9 11 13 15
Spee
dup
(rel
ativ
e to
EC
2 2X
L)
# cores
OpenFoam Speedup Backplane (higher is better)
SL PM (ded)
SL PM
SL VM
EC2 CCI2
EC2 2XL
0
1
2
3
4
5
6
7
8
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29 31
Spee
dup
(rel
ativ
e to
EC
2 2X
L)
# cores
OpenFoam Speedup Ethernet (higher is better)
SL PM (ded)
SL PM
SL VM
EC2 CCI2
EC2 2XL