Evolving the message passing programming model via a fault-tolerant object-oriented transport layer
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Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading framework allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.
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This brief report explains the method used for parameter calibration and model validation in SST/Macro and the set of tools and workflow developed for this purpose.
Proceedings - IEEE 28th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2014
Coordination languages are an established programming model for distributed computing, but have been largely eclipsed by message passing (MPI) in scientific computing. In contrast to MPI, parallel workers never directly communicate, instead 'coordinating' indirectly via key-value store puts and gets. Coordination often focuses on program expressiveness, making parallel codes easier to implement. However, coordination also benefits resilience since the key-value store acts as a virtualization layer. Coordination languages (notably Linda) were therefore leading candidates for fault-tolerance in the early '90s. We present the FOX tuple space framework, an extension of Linda ideas focused primarily on transitioning MPI codes to coordination programming. We demonstrate the notion of 'MPI Perturbation Theory,' showing how MPI codes can be naturally generalized to the tuple-space framework. We also consider details of high-performance interconnects, showing how intelligent use of RDMA hardware allows virtualization with minimal added latency. The framework is shown to be resilient to degradation of individual nodes, automatically rebalancing for minimal performance loss. Future fault-tolerant extensions are discussed.
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Proceedings of the International Conference on Dependable Systems and Networks
Extreme-scale computing will bring significant changes to high performance computing system architectures. In particular, the increased number of system components is creating a need for software to demonstrate 'pervasive parallelism' and resiliency. Asynchronous, many-task programming models show promise in addressing both the scalability and resiliency challenges, however, they introduce an enormously challenging distributed, resilient consistency problem. In this work, we explore the viability of resilient collective communication in task scheduling and work stealing and, through simulation with SST/macro, the performance of these collectives on speculative extreme-scale architectures.
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Journal of Parallel and Distributed Computing
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