The Kangaroo Approach

to Data Movementon the Grid

Douglas Thain, Jim Basney,Se-Chang Son, and Miron Livny

Condor ProjectUniversity of Wisconsin

The Grid isBYOFS.

“Bring Your Own File System”

You can’t depend on the host.

Problems of configuration:• Execution sites do not necessarily have a

distributed file system, or even a userid for you.

Problems of correctness:• Networks go down, servers crash, disks fill,

users forget to start servers… Problems of performance:

• Bandwidth and latency may fluctuate due to competition with other users, both local and remote.

Applications are Not Prepared

to Handle These Errors Examples:• open(“input”) -> “connection refused”• write(file,buffer,length) -> “wait ten minutes”• close(file) -> “couldn’t write data”

Applications respond by dumping core, exiting, or producing incorrect results… or just by running slowly.

Users respond with…

Focus:“Half-Interactive” Jobs

Users want to submit batch jobs to the Grid, but still be able to monitor the output interactively.

But, network failures are expected as a matter of course, so keeping the job running takes priority over getting output.

Examples:• Simulation of high-energy collider events.

(CMS)• Simulation of molecular structures. (Gaussian)• Rendering of animated images. (Maya)

App UnreliableNetwork

Make a third party responsible for executing each application’s I/O operations.

Never return an error to the application.• (Maybe tell the user or scheduler.)

Use all available resources to hide latencies.

Benefit: Higher throughput, fault tolerance. Cost: Weaker consistency.

The Kangaroo Approach

To Data Movement

Philosophical Musings Two problems, one solution:

• Hiding errors: Retry, report the error to a third party, and use another resource to satisfy the request.

• Hiding latencies: Use another resource to satisfy the request in the background, but if an error occurs, there is no channel to report it.

This is an Old Problem

RAMBuffer

DiskApp DiskDisk

Data Mover ProcessRelieves the application of the

responsibility of collecting, scheduling, and retrying operations.

Application can request consistency operations:

Is it done?Wait until done.

Interface is a file system.

Weak consistency guarantees.

Scheduler chooses when

and where.

Apply it to a New World

RAMBuffer

Disk

App

DiskDisk

Data Mover Process

RAMBuffer

DiskDiskDisk

Accepts the responsibility of

moving data. App should never receive

errors.

Provides weak consistency guarantees.

Moves data according to network, buffer and

target availability.

File System Interface

Occasional explicitconsistency requests.

Our Vision: A Grid

FileSystem

FileSystem

FileSystem

FileSystem

KKK

K

K

KK

Data MovementSystemApp

Disk

Reality Check:Are we on the right track?

David Turek on Reliability:• Be less like a lizard, and more like a human.• (Be self repairing.)

Peter Nugent on Weak Consistency:• Datasets are written once. Recollection or

recomputation results in a new file.• (No read/write or write/write issues.)

Miron Livny on the Grid Environment:• The grid is constantly changing. Networks go

up, and down, and machines come and go. Software must be agile.

Introducing Kangaroo

- A user-level data movement system that ‘hops’ partial files from node to node on the Grid.

- A background process that will ‘fight’ for your jobs’ I/O needs.

- A ‘data valet’ that worries about errors, but never admits them to the job.

Kangaroo Prototype We have built a first-try Kangaroo that

validates the central ideas of hiding errors and latencies.

Emphasis on high-level reliability and throughput, not on low-level optimizations.

First, work to improve writes, but leave room in the design to improve reads.

Kangaroo Prototype

KKApp K

An application may contact any node in the system and perform partial-file reads and writes.

Disk

The node may then execute or buffer operations as conditions warrant.

Where are my data?Have they arrived yet?

Disk full.Credentials expired.Permission denied.

The Kangaroo Protocol

Simple, easy to implement. Same protocol is used between all

participants.• Client -> Server• Server -> Server

Can be thought of as an “indirect NFS.”• Idempotent operations on a (host,file) name.• Servers need not remember state of clients.

Get( host, file, offset, length, data )

-> returns success/failure + data

Put( host, file, offset, length, data )

-> no response

Commit()

-> returns success/failure

Push( host, file )

-> returns success/failure

The Kangaroo Protocol

The Kangaroo Protocol

The Kangaroo Protocol Writes do not return a result!

• Why? A grid application has no reasonable response to possible errors:

– Connection lostConnection lost– Out of spaceOut of space– Permission deniedPermission denied

• The Kangaroo server becomes responsible for trying and retrying the write, whether it is an intermediate or ultimate destination.

• If there is a brief resource shortage, the server may simply pause the incoming stream.

• If there is a catastrophic error, the server may drop the connection -- the caller must roll back.

The Kangaroo Protocol Two consistency operations:

• Commit:– Block until all writes have been safely recorded in Block until all writes have been safely recorded in

somesome stable storage. stable storage.– App must do this before it exits.App must do this before it exits.

• Push:– Block until all writes are delivered to their ultimate Block until all writes are delivered to their ultimate

destinations.destinations.– App may do this to externally synchronize.App may do this to externally synchronize.– User may do this to discover if data movement is User may do this to discover if data movement is

done.done. Consistency guarantees:

• The end result is the same as an interactive system.

User Interface

Although applications could write to the Kangaroo interface, we don’t expect or require this.

An interposition agent is responsible for converting POSIX operations into the Kangaroo protocol.

KApp AgentPOSIX Kangaroo

User Interface Interposition agent built with Bypass.

• A tool for trapping UNIX I/O operations and routing them through new code.

• Works on any dynamically-linked, unmodified, unprivileged program.

Examples:• vi /kangaroo/coral.cs.wisc.edu/etc/hosts

• gcc /gsiftp/server/input.c -o /kangaroo/server/output.exe

Performance Evaluation

Not a full-fledged file-system evaluation.

A proof-of-concept that shows latencies and errors can be hidden correctly.

Preview of results:• As a data-copier, Kangaroo is reasonable.• Real benefit comes from the ability to

overlap I/O and CPU.

Microbenchmark:File Transfer

Create a large output file at the execution site, and send it to a storage site.

Ideal conditions: No competition for cpu, network, or disk bandwidth.

Three methods:• Stream output directly to target.

(Online)• Stage output to disk. (Offline)• Kangaroo

Macrobenchmark:Image Processing

Post-processing of satellite image data: Need to compute various enhancements and produce output for each.• Read input image• For I=1 to N

– Compute transformation of image– Write output image

Example:• Image size about 5 MB• Compute time about 6 sec• IO-cpu ratio about 0.9 MB/s

I/O Models Compared

OUTPUT OUTPUT

CPU

OUTPUT

Online I/O:

Offline I/O:

Kangaroo:

INPUT

OUTPUT

CPU CPU CPU

OUTPUTOUTPUTCPU OUTPUTINPUT OUTPUTCPU CPU CPU

OUTPUT OUTPUTCPU OUTPUTINPUT OUTPUTCPUCPU CPU

PUSH

CPU Released Task Done

CPU Released

Task DoneTask DoneCPU Released

Summary of Results

At the micro level, our prototype provides reliability with reasonable performance.

At the macro level, I/O overlap gives reliability and speedups (for some applications.)

Kangaroo allows the application to survive on its real I/O needs: .91 MB/s. Without it, there is ‘false pressure’ to provide fast networks.

Research Problems Commit means “make data safe somewhere.”

• Greedy approach: Commit all dirty data here.• Lazy approach: Commit nothing until final

delivery.• Solution must be somewhere in between.

Disk as Buffer, not as File System• Existing buffer impl is clumsy and inefficient.

Need to optimize for 1-write, 1-read, 1-delete. Fine-Grained Scheduling

• Reads should have priority over writes. This is easy at one node, but multiple nodes?

Related Work

Some items neglected from the paper:• HPSS data movement:

- Move data from RAM -> disk -> tape• Internet Backplane Protocol (IBP)

– Passive storage building block.Passive storage building block.– Kangaroo could use IBP as underlying storage.Kangaroo could use IBP as underlying storage.

• PUNCH virtual file system– Uses NFS as data protocol.Uses NFS as data protocol.– Uses indirection for implicit naming.Uses indirection for implicit naming.

Conclusion The Grid is BYOFS. Error hiding and latency hiding are

tightly-knit problems. The solution to both is to make a third

party responsible for I/O execution. The benefits of high-level overlap can

outweigh any low-level inefficienies.

Contact Us Douglas Thain

• Thain@cs.wisc.edu Miron Livny

• Miron@cs.wisc.edu Kangaroo software, papers, and more:

• http://www.cs.wisc.edu/condor/kangaroo Condor in general:

• http://www.cs.wisc.edu/condor Questions now?