openstack dc meet up june 7th at 6:30pm @geekeasydc
TRANSCRIPT
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OpenStack DC Meet Up
June 7th at 6:30pm @warehousedc
www.meetup.com/OpenStackDC
www.twitter.com/OpenStackDC
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WELCOME!
Thank you to our Sponsor,
( )!
Meet our OpenStack DC Organizers Haisam Ido
Kapil Thangavelu
Matthew Metheny
Eric Mandel
Jason Ford
Kenna McCabe
Ryan Day
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AGENDA
"High-Performance, Heterogeneous Computing and OpenStack" by Karandeep Singh, Cloud Computing and HPC Engineer at University of Southern
California / Information Sciences Institute
"Essex: Architecture and Deployment of Compute Clouds" by Jason Ford, CTO and Co-Founder of BlackMesh
"OpenStack Nova Distributed RPC with Zeromq" by Eric Windisch Senior Systems Engineer at CloudScaling
"OpenStack Bare-Metal Provisioning Framework” by Mikyung Kang at Adaptive Parallel Execution Division at University of Southern
California / Information Sciences Institute
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Heterogeneous, High-Performance Cloud Computing using OpenStack
Karan Singh and Steve Crago University of Southern California / Information Sciences Institute
June 7, 2012
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Objectives
Heterogeneous, virtualized high performance computing (HPC)
testbed
HPC resources available through private cloud
— Resources available remotely for operations, prototypes, experiments and
disadvantaged users
— Dynamic resource provisioning
— Non-proprietary open source cloud software that can be replicated and
extended as needed
Heterogeneous processing resources
— Large x86-based shared memory machine (SGI UV100)
— General-purpose many-core (Tilera TILEmpower)
— GPU-based accelerators (NVidia Tesla)
5
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Heterogeneous Processing
Testbed
6
Heterogeneous On-Demand
Processing Testbed
Shared Memory:
•(1) SGI UV100
HPC Cluster
Tiled Processor:
•(10) Tilera TILEmpower
Commodity Cluster and Storage
Storage Array
GPU Cluster:
•(3) Tesla S2050
• 1 SGI Altix UV 100 (Intel
Xeon Nehalem, 128 cores)
• 10 TILEmpower boards
(Tilera TILEPro64 640
cores)
• 3 Tesla 2050s (NVidia Fermi
GPUs, 5,376 cores)
• Commodity cluster (Intel
Xeon Clovertown, 80 cores)
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Heterogeneous Processors
Processing Component
Characteristics
SGI UV 100 Shared memory, traditional HPC, x86 processors that support legacy code. Supports KVM and LXC.
Tilera TILEmpower General-purpose many-core, 10x-100x improvement in power efficiency for integer processing, Linux-based C/C++ development environment. Supports bare-metal provisioning.
Nvidia TESLA 2050 Very high performance and efficiency (100x) for regular computational kernels, CUDA development environment. Supports LXC (host).
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Heterogeneity: Architectures
CPU: GPU:
1010 samples108 samples
136.2 seconds 139.5 seconds
SGI UV100 rendering 1926 objects
Tilera vs. x86 video transcoding
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Infrastructure as a Service (IaaS)
Provides a web services portal and developer tools for managing virtual private clusters, virtual
storage, and virtual machine images
— Images can be provided to users or users can create their own images
— Enables users to access centralized heterogeneous HPC resources through private cloud interface
— Ability to address soft real-time requirements
New machine types so that all of the development tools and higher level services (PaaS and SaaS
or ASP) can access them
— Each machine type requires (or can handle) unique image type (e.g. a GPU requires a GPU executable)
— Each machine type has an image boot process
9
Machine Types:
•SGI Ultra Violet:
uv.small, uv.large, …
•Tilera TileEmpower:
tile.1x1, tile.2x2, …
•Nvidia Tesla GPU
g1.large+s2050
Browser-based, command-line, and programming interfaces
Management of private instances, application machine images, security credentials, network firewalls and addresses, datacenters, etc.
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Agent of Innovation: from visionary to viable
Heterogeneity: Virtualization
• 3D parallel rendering system
— Tachyon v. 0.99
— Rendering a scene with 1926 objects
— Shared memory test
0
10
20
30
40
50
60
70
1 16 32 64
S
p
e
e
d
u
p
Number of H/W Threads Used
Speedup of 3D Rendering (Tachyon)
Native (w/o pinning)
KVM w/ pinning
LXC w/ pinning (2 times h/w threads)
LXC w/ pinning
LXC w/o pinning
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Agent of Innovation: from visionary to viable
Heterogeneity: GPU Access Methods
0
500
1000
1500
2000
2500
3000
3500
4000
MB
/se
c
Bytes
Host to Device Bandwidth, Pageable
Host
LXC
gVirtus
0
20
40
60
80
100
120
140
160
180
200
80x160
160x320
240x480
320x640
400x800
480x960
560x1120
640x1280
720x1440
800x1600
GFlo
ps/S
ec
Size (NxM), Single Precision Real
Matrix Multiply for Increasing NxM
Host
gVirtus
LXC
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Agent of Innovation: from visionary to viable
Heterogeneity: Message Passing
5,403 5,535 5,729 5,840 6,143 9,129
29,217
148,668
386,312
762,745
1,000
10,000
100,000
1,000,000
1 4 16 64 256 1K 4K 16K 32K 64K
To
tal
cycle
s
Message size (words)
Send/Recv (1,000 iterations)
iLib_2.0 MPI_2.0.2 MPI_1.3.5 MPI_2.1.0
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Future Plans
• Additional devices
• FPGAs
• Arm cores (Calxeda)
• Next-generation GPUs
• New host virtualization options with GPUs
• Collaboration with Nvidia
• Resource scheduling
• Platform-as-a-Service
• Security hardening
• Application demonstrations
• Deployment
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Essex: Architecture and Deployment of Compute Clouds
By Jason Ford, CTO of BlackMesh
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CTO of BlackMesh Managed Hosting
Twitter: @bmeshjason and @BlackMesh
Working with virtual technology for five years
Openstack since cactus
BlackMesh formed in 2003
Four datacenters (three in Northern VA and one in Las Vegas NV)
Manage ~650 servers today
About Me and BlackMesh
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OpenStack Overview
From: http://ken.pepple.info/openstack/2012/02/21/revisit-openstack-architecture-diablo/
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Agenda
Share nothing architecture
Nova: Compute
Swift: Object Storage
Glance: Image Service
Quantum: SDN (Network)
Keystone: Authentication
Horizon: Web Dashboard
Talk about today:
Nova and related services
What the physical layout looks like for deployments
Overall Security
Compute Images
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Openstack Overview
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Nova Architecture
Nova Services
Nova-api: The heart of Nova. Traffic cop for all other services
Nova-volume: Deals with dynamically attached block storage
Nova-network: Manages networking and vlans
Nova-scheduler: Defines where resources are going to be consumed
Nova-compute: Manages communication between hypervisor and API
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Nova Typical Deployment
Typical Non-High Available deployment
Add compute nodes as you grow
All services on one server
Hardware Firewall required for management network
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Deployment in High Availability of Nova Services
Allows for maximum uptime and service availability
Note: Nova network and volume not shown
Nova Availability Architecture
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No standard except for Ubuntu http://cloud-images.ubuntu.com/
Can add to glance and will just work on Nova compute
Can modify image by mounting
mount –o loop nameofimage.img /mnt
Can install via apt into /mnt --root=/mnt
Cloud-init packages pull meta data
CentOS and Debian create via kvm and libvirt Can use kickstart files
No automated way to pull meta data (right now)
Compute Images
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End of part 1 If interested, part 2 will cover nova-volume, nova-network,
quantum (just starting to explore). Post here: http://www.meetup.com/OpenStackDC/
Questions?
[email protected] www.blackmesh.com
The End
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OpenStack Bare-Metal Provisioning Framework
Mikyung Kang, David Kang, and Stephen Crago
USC/ISI
June 7th, 2012
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Nova-Compute Selection
Create Nova-Compute Driver to manage Bare-Metal machines
Create a filter to classify virtual and Bare-Metal machines
* Reference: Joint(NTT+ISI) bare-metal provisioning framework session in Design Summit 2012
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Bare-Metal Flags
--instance_type_extra_specs=cpu_arch:x86_64 --instance_type_extra_specs=cpu_arch:tilepro64 --instance_type_extra_specs=cpu_arch:ARM
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Instance Request
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Instance types & extra specs
Instance types for Bare-Metal machines
• vcpus: unit of BM
• BM system running a single (SMP) OS
• Usually 1
Use instance_type_extra_specs for more information
• cpu_arch: heterogeneous architecture support
• vcores: # of cores in a BM machine
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Capability & Domain
Pre-populated text file for bare-metal machine information Plan to make it DB
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Image Provisioning: Tilera
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Image Provisioning: PXE
euca-run-instances –t b1.tiny --ramdisk ari-bare –kernel aki-bare ami-a
* Reference: Joint(NTT+ISI) bare-metal provisioning framework session in Design Summit 2012
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Current status
General Bare-Metal Provisioning Framework (DONE)
• USC/ISI: OpenStack Upstream: nova/virt/baremetal/*
• Nova-compute w/ bare-metal plug-in (proxy), virtual domain stuff, and tilera-specific back-end code
New features for PXE:X86 machines (DOING)
• NTT docomo: PXE provisioning code with added features such as volume attachment, network isolation, and vnc access
• Waiting for approval to make them open-source (~6/8 or 6/11)
New features for PXE:ARM machines (DOING)
• Calxeda: ARM back-end code
• USC/ISI: ARM instance types and scheduler side
Fault-tolerance of Nova-Compute (bare-metal)
• USC/ISI: bare-metal information DB, fault-detection (master/mirror nova-compute) and fault-recovery
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Current Collaboration
USC/ISI • “Mikyung Kang” <[email protected]>
• “David Kang” <[email protected]>
NTT docomo • "Ken Ash” <[email protected]>
• "Mana Kaneko" <[email protected]>
Calxeda • "Ripal Nathuji" <[email protected]>
• "Bob Blair" <[email protected]>
Canonical • "Chuck Short" <[email protected]>
Mirantis • "Roman Bogorodskiy" <[email protected]>
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