Refine
Year of publication
Document Type
- In Proceedings (43)
- Article (30)
- ZIB-Report (6)
- Other (4)
- Book chapter (3)
- Poster (2)
- Doctoral Thesis (1)
- Master's Thesis (1)
Is part of the Bibliography
- no (90) (remove)
Keywords
- DHT (2)
- Cache-Simulator (1)
- Grid computing (1)
- Kostenmodell (1)
- Microbenchmarks (1)
- P2P (1)
- Paxos (1)
- Range Queries (1)
- SMP-System (1)
- Speicherhierarchie (1)
User-defined and system-level checkpointing have contrary properties. While user-defined checkpoints are smaller and simpler to recover, system-level checkpointing better knows the global system's state and parameters like the expected mean time to failure (MTTF) per node. Both approaches lead to non-optimal checkpoint time, intervals, sizes, or I/O bandwidth when concurrent checkpoints conflict and compete for it.
We combine user-defined and system-level checkpointing to exploit the benefits and avoid the drawbacks of each other. Thus, applications frequently offer to create checkpoints. The system accepts such offers according to the current status and implied costs to recalculate from the last checkpoint or denies them, i.e., immediately lets continue the application without checkpoint creation. To support this approach, we develop economic models for multi-application checkpointing on shared I/O resources that are dedicated for checkpointing (e.g. burst-buffers) by defining an appropriate goal function and solving a global optimization problem.
Using our models, the checkpoints of applications on a supercomputer are scheduled to effectively use the available I/O bandwidth and minimize the failure overhead (checkpoint creations plus recalculations). Our simulations show an overall reduction in failure overhead of all nodes of up to 30% for a typical supercomputer workload (HLRN). We can also derive the most cost effective burst-buffer bandwidth for a given node's MTTF and application workload.
\newcommand{\chordsharp}{Chord$^\##$} Data lookup is a fundamental problem in peer-to-peer systems: Given a key, find the node that stores the associated object. Chord and other P2P algorithms use distributed hash tables (DHTs) to distribute the keys and nodes evenly across a logical ring. Using an efficient routing strategy, DHTs provide a routing performance of $O (\log N)$ in networks of $N$ nodes. While the routing performance has been shown to be optimal, the uniform key distribution makes it impossible for DHTs to support range queries. For range queries, consecutive keys must be stored on lo gically neighboring nodes. In this paper, we present an enhancement of Chord that eliminates the hash function while keeping the same routing performance. The resulting algorithm, named \chordsharp{}, provides a richer function ality while maintaining the same complexity. In addition to Chord, \chordsharp{} adapts to load imbalance.