SPECULATIVE EXECUTION IN A DISTRIBUTED FILE SYSTEM E. B. Nightingale P. M. Chen J. Flint University of Michigan

Motivation Distributed file systems are often much slower than local file systems –Due to synchronous operations required for cache coherence and data safety –Even true for file systems that weaken consistency and safety guarantees Close-to-open consistency for AFS and most versions of NFS

A better solution Most of these synchronous operations have predictable outcomes –We can bet on the outcome and let the client process go forward ( speculation ) Make operation asynchronous –Must take before that a checkpoint of the process Can restart operation if speculation failed

Why it works 1.Clients can correctly predict the outcome of many operations Few concurrent accesses to files 2.Time to take a lightweight checkpoint is often less than network round-trip time 52 ms for a small process thanks to copy-on-write 3.Most clients have free cycles

Speculator File system controls when speculations start, succeed and fail Speculator provides a mechanism to ensure correct execution of speculative code No application changes are required Speculative state is never visible from the outside

Correctness rules (I) A process that executes in speculative mode cannot externalize output –Speculator blocks the process Speculator tracks causal dependencies between kernel objects – Kernel objects modified by a speculative process will be put in a speculative state

Correctness rules (II) Speculator tracks causal dependencies between processes –Processes receiving a message or a signal from a speculative process will be checkpointed and become speculative In case of doubt, Speculator will block the execution of the speculative process

An example: conventional NFS

Linux NFSv3 implements close to open consistency –At close time, client sends to server: 1.Asynchronous write calls with the modified data 2.A synchronous commit call once it has received replies for all write calls

An example: SpecNFS

All calls are non-blocking but force the calling process to become speculative If a call returns an unexpected result, the calling process is rolled back to its checkpoint and the call is executed again –A new speculation starts

Speculation interface Three new system calls: – Create_speculation () : Returns unique spec_id and a list of previous speculations on which the speculation depends – Commit_speculation(spec_id) – Fail_speculation(spec_id)

Implementing checkpoints Checkpoints are implemented through copy-on-write fork –Speculator also saves the state of any open file descriptor and copies all pending signals Forked child is not placed on the ready queue –It just waits If speculation fails, forked child assumes the identity of the failed parent

New kernel structures Speculation structure: –Created during create_speculation() –Tracks the set of kernel objects that depend on the speculation Undo log: –Associated with each kernel object that has a speculative state –Ordered list of speculative modifications

Sharing checkpoints Letting successive speculations share the same checkpoint reduces the speculation overhead Two limitations –Speculator limits the amount of rollback work by not letting speculation share a checkpoint that is more than 500 ms old –Cannot let a speculation share a checkpoint with a previous speculation that changes state of file system

Correctness invariants 1.Speculative state should never be visible to the user or to any external device –Speculator prevents all speculative processes from externalizing output to any interface 2.A process should never view speculative state unless it is already speculatively dependent upon that state.

Invariant implementations (I) First Implementation: Block speculative processes whenever they try to perform a system call –Always correct –Limits the amount of work that can be done by a process in a speculative state

Invariant implementations (II) Second Implementation: Allow speculative processes to perform systems calls that –Do not modify state “Read-only” calls such as getpid() –Only modify state that is private to the calling process It will be rolled back if speculation fails

Invariant implementations (III) Third Implementation: Allow speculative processes to perform operations on files in speculative file systems –With VFS, can have multiple file systems on the same machine Typically NFS plus FFS or ext3 Must check type of file system –Have a special bit in superblock

Multiprocess speculation (I) Whenever a speculative process P participates in interprocess communication with a process Q Process Q must become speculatively dependent on the speculative state of process P and get checkpointed

Multiprocess speculation (II) Whenever a speculative process P modifies an object X Object X must become speculatively dependent on the speculative state of process P and get an undo list You are not responsible for the implementation details

Performance: PostMark benchmark

SpecNFS is –2.5 times faster than NFS with no latency between client and server –41 times faster than NFS with a 30ms round- trip time delay between client and server A version of BlueFS providing single-copy semantics is 49 times faster than NFS with same 30ms round-trip time delay

Performance: Apache benchmark

Building Apache server from a tarred file SpecNFS is –2 times faster than NFS with no latency between client and server –14 times faster than NFS with a 30ms round- trip time delay between client and serve –Always better than BlueFS and Coda

Performance: impact of rollbacks

Repeated Apache benchmark marking a varying fraction of the files out-of-date –Will result in speculation failures –Percentage of out-of-date files has little impact on SpecNFS performance

Performance: other

Impact of group commits and sharing state –Mostly affects Blue FS When speculative processes cannot propagate their state, Blue FS performs worse than NFS with no latency between client and server Impact magnified at 30ms latency

Conclusion Speculation enables the development of distributed file systems that are –Safe –Consistent –Fast Generic kernel support for speculative execution and causal dependency tracking could have many other applications