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Introduction to the BOINC software David P. Anderson Space Sciences Laboratory University of California, Berkeley

Introduction to the BOINC software

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David P. Anderson Space Sciences Laboratory University of California, Berkeley. Introduction to the BOINC software. Outline. Abstractions The BOINC server software The BOINC client software and runtime system. Design goals. A few applications, lots of jobs High performance - PowerPoint PPT Presentation

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Page 1: Introduction to the BOINC software

Introduction to the BOINC software

David P. Anderson

Space Sciences LaboratoryUniversity of California, Berkeley

Page 2: Introduction to the BOINC software

Outline

• Abstractions

• The BOINC server software

• The BOINC client software and runtime system

Page 3: Introduction to the BOINC software

Design goals

• A few applications, lots of jobs

• High performance

– millions of jobs per day

• Scalability

• Fault tolerance

Page 4: Introduction to the BOINC software

Abstractions• Platform

• App version

– a collection of files, one of which is an executable main program

– associated with a platform

• App

– a set of app versions that all perform roughly the same computation

– may have versions for different platforms

– may have different versions for one platform (GPU, non-GPU)

Page 5: Introduction to the BOINC software

Abstractions

• Workunit (job)

– a collection of input files

– associated with an app (not an app version!)

– attributes• resource estimates and bounds

• latency bound

• Result (job instance)

– a collection of output files

– associated with a workunit

Page 6: Introduction to the BOINC software

Anatomy of a BOINC project

MySQLdatabase

project root/bin/cgi-bin/download/

00/ .. 3ff/html/log_*/templates/upload/

00/ .. 3ff/

serversdaemons andperiodic tasks

clients

Page 7: Introduction to the BOINC software

Work generator

MySQLdatabase

project root/bin/cgi-bin/download/

00/ .. 3ff/html/log_*/templates/upload/

00/ .. 3ff/

work generator

• Creates input files

• Creates workunits

• One per app

• Flow control

– disk space

– DB size

Page 8: Introduction to the BOINC software

Specifying a job

• Workunit template

– XML document describing• input files (logical, physical names)

• job attributes

• Result template

– XML document describing output files

• create_work()

– specifies templates, app, input files

Page 9: Introduction to the BOINC software

Validator

• Check result validity

• Compare replicas

• May be app-specific

MySQLdatabase

project root/bin/cgi-bin/download/

00/ .. 3ff/html/log_*/templates/upload/

00/ .. 3ff/

validator

Page 10: Introduction to the BOINC software

Validation

• Clients may

– return bad results

– exaggerated claimed credit

• Strategies

– app-specific consistency checking

– replication• fuzzy comparison

• homogeneous redundancy

– adaptive replication

Page 11: Introduction to the BOINC software

Assimilator

• Processes completed results

• App-specificMySQL

database

project root/bin/cgi-bin/download/

00/ .. 3ff/html/log_*/templates/upload/

00/ .. 3ff/

assimilator

Page 12: Introduction to the BOINC software

Summary

• Create app, app versions for different platforms

• Develop work generator

• Develop validator

• Develop assimilator

Isn’t there a simpler way?

Page 13: Introduction to the BOINC software

Single-job submission

• Assemble your input files and executable, thenboinc_submit --input foo --output blah program

• How this works:

– uses “wrapper” app

– executable is part of workunit

– templates are created automatically

• What it doesn’t do:

– multi-platform

– validation

Page 14: Introduction to the BOINC software

Job dispatch

MySQLdatabase

project root/bin/cgi-bin/download/

00/ .. 3ff/html/log_*/templates/upload/

00/ .. 3ff/

transitioner

feeder

scheduler(CGI or FastCGI)

share-memoryjob cache

clients

Page 15: Introduction to the BOINC software

File transfer

project root/bin/cgi-bin/download/

00/ .. 3ff/html/log_*/templates/upload/

00/ .. 3ff/

Apache

file uploadhandler

clients

Page 16: Introduction to the BOINC software

Janitorial daemons

MySQLdatabase

project root/bin/cgi-bin/download/

00/ .. 3ff/html/log_*/templates/upload/

00/ .. 3ff/

file deleter

DB purger

Page 17: Introduction to the BOINC software

Ways to deploy a BOINC server

• Linux server

• Server VM for VMWare

• Server VM for Amazon EC2

Page 18: Introduction to the BOINC software

The BOINC runtime system

Directory structure:

BOINC/projects/

lhcathome/physical_name0physical_name1

setiathome/slots/

0/logical_name0 (link file)logical_name1

1/

BOINC client

application

share-memorymessage-passing

BOINC runtime

fraction doneCPU time

suspendresumequit

Page 19: Introduction to the BOINC software

Basic API

• boinc_init()

– creates a thread that handles messages

• boinc_finish()

– creates a “finish file”

• boinc_resolve_filename()

– maps logical to physical file names

Page 20: Introduction to the BOINC software

Checkpointing

• boinc_time_to_checkpoint()

– call at points where you can checkpoint

• boinc_checkpoint_done()

– call when you’re finished checkpointing

Page 21: Introduction to the BOINC software

Compound applications

• Examples:

– coordinator program runs several worker programs in sequence

– “switcher” program probes CPU architecture, selects which executable to run

• Variants of boinc_init() let you specify which app is main program, and how messages are handled

• Each message type must be handled by 1 process

Page 22: Introduction to the BOINC software

Long-running applications

• Trickle-up messages

• Trickle-down messages

• Intermediate file transfers

Page 23: Introduction to the BOINC software

Legacy applications

• The BOINC wrapper

– takes XML “job file”

– handles all messages

Page 24: Introduction to the BOINC software

GPU and multithread apps

• Server

– you supply a function that takes an app version and a host, and returns resource usage and estimated FLOPS

– the BOINC scheduler chooses the best version

• Client

– senses and reports coprocessors (e.g. NVIDIA GPUs)

– coprocessor-aware scheduling and work fetch