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Eric Brewer 2006-08-19 05:57:52 +00:00
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10
doc/paper3/LLADD.tex
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@ -1360,7 +1360,7 @@ is used by RVM's log-merging operations~\cite{lrvm}.
Furthermore, application-specific
procedures that are analogous to standard relational algebra methods
(join, project and select) could be used to efficiently transform the data
(join, project and select) could be used to transform the data efficiently
while it is still laid out sequentially
in non-transactional memory.
@ -1604,7 +1604,7 @@ contributions, both in system design, and in algorithms for
distributed transactions~\cite{camelot}. It leaves locking to application level code,
and updates data in place. (Argus uses shadow copies to provide
atomic updates.) Camelot provides two logging modes: Redo only
(no-Steal,no-Force) and Undo/Redo (Steal, no-Force). It uses
(no-Steal, no-Force) and Undo/Redo (Steal, no-Force). It uses
facilities of Mach to provide recoverable virtual memory. It
is decoupled from Avalon, which uses Camelot to provide a
higher-level (C++) programming model. Camelot provides a lower-level
@ -1612,15 +1612,15 @@ C interface that allows other programming models to be
implemented. It provides a limited form of closed nested transactions
where parents are suspended while children are active. Camelot also
provides mechanisms for distributed transactions and transactional
RPC. While Camelot does allow appliactions to provide their own lock
RPC. Although Camelot does allow appliactions to provide their own lock
managers, implementation strategies for concurrent operations
in Camelot are similar to those
in Argus since Camelot does not provide logical undo. Camelot focuses
on distributed transactions, and hardcodes
assumptions regarding the structure of nested transactions, consensus
algorithms, communication mechanisms, and so on. In contrast, \yads
goal is to efficiently support a wide range of such mechanisms without
providing any built in support for distributed transactions.
goal is to support a wide range of such mechanisms efficiently without
providing any built-in support for distributed transactions.
More recent transactional programming schemes allow for multiple
transaction implementations to cooperate as part of the same