128 research outputs found
Deterministic Consistency: A Programming Model for Shared Memory Parallelism
The difficulty of developing reliable parallel software is generating
interest in deterministic environments, where a given program and input can
yield only one possible result. Languages or type systems can enforce
determinism in new code, and runtime systems can impose synthetic schedules on
legacy parallel code. To parallelize existing serial code, however, we would
like a programming model that is naturally deterministic without language
restrictions or artificial scheduling. We propose "deterministic consistency",
a parallel programming model as easy to understand as the "parallel assignment"
construct in sequential languages such as Perl and JavaScript, where concurrent
threads always read their inputs before writing shared outputs. DC supports
common data- and task-parallel synchronization abstractions such as fork/join
and barriers, as well as non-hierarchical structures such as producer/consumer
pipelines and futures. A preliminary prototype suggests that software-only
implementations of DC can run applications written for popular parallel
environments such as OpenMP with low (<10%) overhead for some applications.Comment: 7 pages, 3 figure
Non-intrusive on-the-fly data race detection using execution replay
This paper presents a practical solution for detecting data races in parallel
programs. The solution consists of a combination of execution replay (RecPlay)
with automatic on-the-fly data race detection. This combination enables us to
perform the data race detection on an unaltered execution (almost no probe
effect). Furthermore, the usage of multilevel bitmaps and snooped matrix clocks
limits the amount of memory used. As the record phase of RecPlay is highly
efficient, there is no need to switch it off, hereby eliminating the
possibility of Heisenbugs because tracing can be left on all the time.Comment: In M. Ducasse (ed), proceedings of the Fourth International Workshop
on Automated Debugging (AAdebug 2000), August 2000, Munich. cs.SE/001003
Automatic Verification of Data Race Freedom in Device Drivers
Device drivers are notoriously hard to develop and even harder to debug. They are typically prone to many serious issues such as data races. In this paper, we present static pair-wise lock set analysis, a novel sound verification technique for proving data race freedom in device drivers. Our approach not only avoids reasoning about thread interleavings, but also allows the reuse of existing successful sequential verification techniques
Sequentializing Parameterized Programs
We exhibit assertion-preserving (reachability preserving) transformations
from parameterized concurrent shared-memory programs, under a k-round
scheduling of processes, to sequential programs. The salient feature of the
sequential program is that it tracks the local variables of only one thread at
any point, and uses only O(k) copies of shared variables (it does not use extra
counters, not even one counter to keep track of the number of threads).
Sequentialization is achieved using the concept of a linear interface that
captures the effect an unbounded block of processes have on the shared state in
a k-round schedule. Our transformation utilizes linear interfaces to
sequentialize the program, and to ensure the sequential program explores only
reachable states and preserves local invariants.Comment: In Proceedings FIT 2012, arXiv:1207.348
Fast and Precise Symbolic Analysis of Concurrency Bugs in Device Drivers
© 2015 IEEE.Concurrency errors, such as data races, make device drivers notoriously hard to develop and debug without automated tool support. We present Whoop, a new automated approach that statically analyzes drivers for data races. Whoop is empowered by symbolic pairwise lockset analysis, a novel analysis that can soundly detect all potential races in a driver. Our analysis avoids reasoning about thread interleavings and thus scales well. Exploiting the race-freedom guarantees provided by Whoop, we achieve a sound partial-order reduction that significantly accelerates Corral, an industrial-strength bug-finder for concurrent programs. Using the combination of Whoop and Corral, we analyzed 16 drivers from the Linux 4.0 kernel, achieving 1.5 - 20× speedups over standalone Corral
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Fault tolerance via diversity for off-the-shelf products: A study with SQL database servers
If an off-the-shelf software product exhibits poor dependability due to design faults, then software fault tolerance is often the only way available to users and system integrators to alleviate the problem. Thanks to low acquisition costs, even using multiple versions of software in a parallel architecture, which is a scheme formerly reserved for few and highly critical applications, may become viable for many applications. We have studied the potential dependability gains from these solutions for off-the-shelf database servers. We based the study on the bug reports available for four off-the-shelf SQL servers plus later releases of two of them. We found that many of these faults cause systematic noncrash failures, which is a category ignored by most studies and standard implementations of fault tolerance for databases. Our observations suggest that diverse redundancy would be effective for tolerating design faults in this category of products. Only in very few cases would demands that triggered a bug in one server cause failures in another one, and there were no coincident failures in more than two of the servers. Use of different releases of the same product would also tolerate a significant fraction of the faults. We report our results and discuss their implications, the architectural options available for exploiting them, and the difficulties that they may present
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