Scientific Computing in the
Consumer Digital Infrastructure
David P. Anderson
Space Sciences Lab
University of California, Berkeley
The Austin Forum
November 7, 2013
Science needs computing power
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High-performance computing
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High-throughput computing
–
Thousands or millions of independent jobs
–
What matters is the rate of job completion,
not the turnaround time of individual jobs
High-throughput computing
applications
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●
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Physical simulation
–
particle collision
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atomic/molecular (bio, nano)
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Earth climate system
Compute-intensive data analysis
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particle physics (LHC)
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Astrophysics (radio, gravitational)
–
genomics
Bio-inspired optimization
–
genetic algorithms, flocking, ant colony etc.
Approaches to HTC
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Cluster computing
–
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Grid computing
–
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share clusters between organizations
Cloud computing
–
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lots of commodity or rack-mounted PCs in a room
rent cluster nodes, e.g. Amazon EC2
Volunteer computing
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use computers owned by consumers
The Consumer Digital Infrastructure
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Computing devices
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Desktop and laptop computers
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Mobiles devices: tablets, smart phones
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Game consoles
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Set-top boxes, DVRs
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Appliances
Commodity Internet
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Cable, DSL, fiber to the home, cell networks
Measures of computing speed
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Floating-point operation (FLOP)
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GigaFLOPS (109/sec): 1 Central Processing Unit (CPU)
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TeraFLOPS (1012/sec): 1 Graphics Processing Unit (GPU)
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PetaFLOPS (1015/sec): 1 supercomputer
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ExaFLOPS (1018/sec): current Holy Grail
CDI performance potential
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1 billion Desktop/laptop PCs
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CPUs: 10 ExaFLOPS
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GPUs: 1,000 ExaFLOPS
2.5 billion smartphones
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CPUs: 10 ExaFLOPS
Volunteer computing
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Consumers donate computing capacity to
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support science
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be in a community
–
compete
History
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1997: GIMPS, distributed.net
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1999: SETI@home, Folding@home
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2003: BOINC
Limiting factors
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Volunteership
–
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Study of college students [Toth 2006]
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5% would “definitely participate”
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10% would “possible participate”
PC availability
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65% average availability [Kondo 2008]
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35% of PCs are available 24/7
Other limiting factors
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Network bandwidth (client, server)
–
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Commodity Internet
Memory, disk usage
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new PCs average 6 GB RAM
BOINC: middleware for volunteer
computing
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Supported by NSF since 2002
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Open source (LGPL)
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Based at University of California, Berkeley
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http://boinc.berkeley.edu
Volunteer computing with BOINC
projects
volunteers
LHC@home
CPDN
attachments
WCG
How to volunteer
Choose projects
Configure
Community
Creating a BOINC project
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Install BOINC server software on a Linux box
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Compile apps for Windows/Mac/Linux
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Attract volunteers
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develop web site
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generate publicity
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communicate with volunteers
Volunteer computing today
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500,000 active computers
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50 projects
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15 PetaFLOPS average
Some BOINC-based projects
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IBM World Community Grid
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Einstein@home
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Climateprediction.net
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LHC@home
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Rosetta@home
Cost
The cost of 10 TeraFLOPS for 1 year:
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CPU cluster: $1.5M
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Amazon EC2: $4M
–
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5,000 small instances
Volunteer: ~ $0.1M
How BOINC works
project
home PC
get jobs
download data, executables
BOINC
client
compute
upload outputs
HTTP
BOINC
server
Issues handled by BOINC
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Heterogeneous computers
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Untrusted, anonymous computers
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Result validation
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replication, adaptive replication
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Credit: amount of work done
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Consumer-friendly client
Using GPUs
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BOINC detects and schedules GPUs
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NVIDIA, AMD, Intel
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multiple/mixed GPUs
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various language systems (CUDA, OpenCL, CAL)
Issues
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non-preemptive GPU scheduling
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no paging of GPU memory
Multicore apps
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Next-generation PCs may have 100 cores
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BOINC supports multi-core apps
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OpenMP, MPI
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OpenCL CPU apps
Using VM technology
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CDI platforms:
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85% Windows
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7% Linux
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7% Mac OS X
Developing and maintaining versions for
different platforms is hard
Even making a portable Linux executable is
hard
Virtual machines
application
Guest operating system
Host operating system
Virtual machines
application
Debian Linux 2.6
Windows 7
BOINC VM support
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Create a VM image for your favorite environment
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Create executables for that environment
VirtualBox
executive
BOINC
client
Vbox
wrapper
shared directory:
executable
input, output
files
VM instance
VM advantages
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Develop in your favorite environment
–
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A VM is a strong “sandbox”
–
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No need for multiple versions
Can run untrusted applications
Free “checkpointing”
BOINC on Android
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New GUI
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Battery-related issues
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Released July 2013
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Google, Amazon App Stores
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~50K active devices
Why hasn’t volunteer computing
gained traction?
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“Ecosystem of projects” model
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Lots of competing projects
Problems with this model
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Creating/operating a project is too hard and risky
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Volunteers need simplicity
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No coherent PR; too many brands
Umbrella projects
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One project serves many scientists
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Examples
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CAS@home (Chinese Academy of Science)
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World Community Grid (IBM)
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U. of Westminster (desktop grid)
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Ibercivis (Spanish consortium)
Integrating BOINC
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HTCondor (U. of Wisconsin)
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Goal: BOINC-based back end for Open Science Grid
or any Condor pool
HTCondor node
Grid manager
BOINC GAHP
Job submission
BOINC
server
Integrating BOINC
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HUBzero (Purdue)
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Goal: BOINC-based back end for science portals
such as nanoHUB
Hub
BOINC
server
PCs
projects
projects
Proposal: Science@home
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Single “brand” for volunteer computing
Volunteers register for science areas rather
than projects
How to allocate computing power?
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Involve the HPC, scientific funding communities
Implementing Science@home
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BOINC “account manager” architecture
BOINC
client
Science@home
projects
projects
projects
Summary
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Volunteer computing is
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Usable for most HTC applications
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A path to ExaFLOPS computing
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A way to popularize science
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BOINC provides the software infrastructure
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Barriers are largely organizational
Contacts
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http://boinc.berkeley.edu
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davea@ssl.berkeley.edu