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High-performance computing (HPC) systems are growing more powerful by utilizing more hardware components. As the system mean-time-before-failure correspondingly drops, applications must checkpoint more frequently to make progress. However, as the system memory sizes grow faster than the bandwidth to the parallel file system, the cost of checkpointing begins(More)
Over the last decade, InfiniBand has become an increasingly popular interconnect for deploying modern super-computing systems. However, there exists no detection service that can discover the underlying network topology in a scalable manner and expose this information to runtime libraries and users of the high performance computing systems in a convenient(More)
SUMMARY InfiniBand has become a very popular interconnect, due to its advanced features and open standard. Large scale InfiniBand clusters are becoming very popular, as reflected by the TOP 500 supercomputer rankings. However, even with popular topologies like constant bi-section bandwidth Fat Tree, hot-spots may occur with InfiniBand, due to inappropriate(More)
Large HPC centers spend considerable time supporting software for thousands of users, but the complexity of HPC software is quickly outpacing the capabilities of existing software management tools. Scientific applications require specific versions of compilers, MPI, and other dependency libraries, so using a single, standard software stack is infeasible.(More)
As the capability and component count of systems increase, the MTBF decreases. Typically, applications tolerate failures with checkpoint/restart to a parallel file system (PFS). While simple, this approach can suffer from contention for PFS resources. Multi-level checkpointing is a promising solution. However, while multi-level checkpointing is successful(More)
Large scale InfiniBand clusters are becoming increasingly popular, as reflected by the TOP 500 Supercomputer rankings. At the same time, fat tree has become a popular interconnection topology for these clusters, since it allows multiple paths to be available in between a pair of nodes. However, even with fat tree, hot-spots may occur in the network(More)
Many parallel algorithms require efficient reduction collectives. In response, researchers have designed algorithms considering a range of parameters including data size, system size, and communication characteristics. Throughout this past work, however, processing was limited to the host CPU. Today, modern Network Interface Cards (NICs) sport programmable(More)
High performance computing (HPC) systems use checkpoint-restart to tolerate failures. Typically, applications store their states in checkpoints on a parallel file system (PFS). As applications scale up, checkpoint-restart incurs high overheads due to contention for PFS resources. The high overheads force large-scale applications to reduce checkpoint(More)
With the massive scale of high-performance computing systems, long-running scientific parallel applications periodically save the state of their execution to files called checkpoints to recover from system failures. Checkpoints are stored on external parallel file systems, but limited bandwidth makes this a time-consuming operation. Multilevel checkpointing(More)