Publications

This paper presents a fine-grain queueing model of MPI point-To-point messaging performance for use in the design and analysis of current and future large-scale computing sys-Tems. In particular, the model seeks to capture key perfor-mance behavior of MPI communication on many-core sys-Tems. We demonstrate that this model encompasses key MPI performance characteristics, such as short/long proto-col and offoad/onload protocol tradeos, and demonstrate its use in predicting the potential impact of architectural and software changes for many-core systems on communication performance. In addition, we also discuss the limitations of this model and potential directions for enhancing its fi-delity.

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This paper explores the trade-offs between on-loaded versus offloaded network stack processing for systems with varying CPU frequencies. This study explores the differences of onload and offload using experiments run at different DVFS settings to change the frequency, while measuring performance and power. This allows for a quantitative comparison of the the performance and power and trade-offs between onload and offload cards, with a wide range of CPU performances. The results show that there is often a significant performance increase in using offloaded cards especially at lower CPU frequencies, with only a small increase in power usage. This study also uses MPI profiling to analyze why some applications see a larger benefit than others. This paper's contributions are an analytical, quantitative analysis of the trade-offs between onload and offload. While there has been debate to this question, this is the first, to the authors' knowledge, analytical evaluation of the performance difference. The range of frequencies analyzed give insight on how this MPI might perform on different architectures, such as the low frequency, many-core CPUs. Finally, the power measurements allow for the study to provide further depth in the analysis.

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The metrics used for evaluating energy saving techniques for future HPC systems are critical to the correct assessment of proposed methods. Current predictions forecast that overcoming reduced system reliability, increased power requirements and energy consumption will be a major design challenge for future systems. Modern runtime energy-saving research efforts do not take into account the energy spent providing reliability. They also do not account for the increase in the probability of failure during application execution due to runtime overhead from energy saving methods. While this is very reasonable for current systems, it is insufficient for future generation systems. By taking into account the energy consumption ramifications of increased runtimes on system reliability, better energy saving techniques can be developed. This paper demonstrates how to determine the impact of runtime energy conservation methods within the context of failure-prone large scale systems. In addition, a survey of several energy savings methodologies is conducted and an analysis is performed with respect to their effectiveness in an environment in which failures occur.

Power and energy concerns are motivating chip manufacturers to consider future hybrid-core processor designs that may combine a small number of traditional cores optimized for single-thread performance with a large number of simpler cores optimized for throughput performance. This trend is likely to impact the way in which compute resources for network protocol processing functions are allocated and managed. In particular, the performance of MPI match processing is critical to achieving high message throughput. In this paper, we analyze the ability of simple and more complex cores to perform MPI matching operations for various scenarios in order to gain insight into how MPI implementations for future hybrid-core processors should be designed.

We compare and contrast the approaches and key features of two proposals for fault-tolerant MPI: User-Level Failure Mitigation (UFLM) and Fault-Aware MPI (FA-MPI). We show how they are complementary and also how they could leverage each other through modifications and/or extensions. We show how to "weaken" and extend ULFM to help integrate it with FA-MPI, with corollary benefits of broadening applicability of ULFM. Reducibility of each to the other is considered. This helps identify which components of each are minimally "required" for standardization, versus layer-able on a future MPI specification.

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Much recent research has explored fault-tolerance mechanisms intended for current and future extreme-scale systems. Evaluations of the suitability of checkpoint-based solutions have typically been carried out using relatively uncomplicated computational kernels designed to measure floating point performance. More recent investigations have added scaled-down "proxy" applications to more closely match the composition and behavior of deployed ones. However, the information obtained from these studies (whether floating point performance or application runtime) is not necessarily of the most value in evaluating resilience strategies. We observe that even when using a more sophisticated metric, the information available from evaluating uncoordinated checkpointing using both microbenchmarks and proxy applications does not agree. This implies that not only might researchers be asking the wrong questions, but that the answers to the right ones might be unexpected and potentially misleading. We seek to open a discussion on whether benchmarks designed to provide predictable performance evaluations of HPC hardware and toolchains are providing the right feedback for the evaluation of fault-tolerance in these applications, and more generally on how benchmarking of resilience mechanisms ought to be approached in the exascale design space. © 2014 Springer-Verlag Berlin Heidelberg.

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