3 research outputs found
An Optimizing Java Translation Framework for Automated Checkpointing and Strong Mobility
Long-running programs, e.g., in high-performance computing, need to
write periodic checkpoints of their execution state to disk to allow
them to recover from node failure. Manually adding checkpointing code
to an application, however, is very tedious. The mechanisms needed
for writing the execution state of a program to disk and restoring it
are similar to those needed for migrating a running thread or a mobile
object. We have extended a source-to-source translation scheme that
allows the migration of mobile Java objects with running threads to
make it more general and allow it to be used for automated
checkpointing. Our translation scheme allows serializable threads to
be written to disk or migrated with a mobile agent to a remote
machine. The translator generates code that maintains a serializable
run-time stack for each thread as a Java data structure. While this
results in significant run-time overhead, it allows the checkpointing
code to be generated automatically. We improved the locking mechanism
that is needed to protect the run-time stack as well as the translation
scheme. Our experimental results demonstrate an speedup of the
generated code over the original translator and show that the approach
is feasible in practice
Optimizing Checkpoint Restart with Data Deduplication
The increasing scale, such as the size and complexity, of computer systems brings more frequent occurrences of hardware or software faults; thus fault-tolerant techniques become an essential component in high-performance computing systems. In order to achieve the goal of tolerating runtime faults, checkpoint restart is a typical and widely used method. However, the exploding sizes of checkpoint files that need to be saved to external storage pose a major scalability challenge, necessitating the design of efficient approaches to reducing the amount of checkpointing data. In this paper, we first motivate the need of redundancy elimination with a detailed analysis of checkpoint data from real scenarios. Based on the analysis, we apply inline data deduplication to achieve the objective of reducing checkpoint size. We use DMTCP, an open-source checkpoint restart package, to validate our method. Our experiment shows that, by using our method, single-computer programs can reduce the size of checkpoint file by 20% and distributed programs can reduce the size of checkpoint file by 47%