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Energy-efficient scheduling

Jean Utke

Designing and implementing a tool-indedendent, adjoinable MPI wrapper library

The efficient computation of gradients by the "adjoint-mode" of algorithmic differentiation (AD) entails the inversion of MPI communication graphs. The logic to be implemented for adjoining non-blocking communication patterns is sufficiently complex to warrant  a design of components that is independent of the algorithmic differentiation tool that provides the context in which the adjoint communication is to take place. We discuss (i) how we account for the different data models  implied by the AD  tool as well as the target language, (ii) the implementation choices among the possible adjoint communications, and (iii) the currently known limitations of our approach. We hope for feedback from the community regarding this design particularly  with respect to performance and current developments in the MPI standard.

Laurent Hascoet

In this talk, I will survey recent works on energy-efficient scheduling. The goal is to minimize the energy consumption of a schedule, given some performance constraints, for instance a bound on the total execution time. I will first revisit the greedy algorithm for independent tasks in this context. Then I will present problems accounting for the reliability of a schedule: if a failure may occur, then replication or checkpoint is used to achieve a reliable schedule. The goal remains the same, i.e., minimize the energy consumption under performance constraints

Jean Utke

Designing and implementing a tool-indedendent, adjoinable MPI wrapper library

The efficient computation of gradients by the "adjoint-mode" of algorithmic differentiation (AD) entails the inversion of MPI communication graphs. The logic to be implemented for adjoining non-blocking communication patterns is sufficiently complex to warrant  a design of components that is independent of the algorithmic differentiation tool that provides the context in which the adjoint communication is to take place. We discuss (i) how we account for the different data models  implied by the AD  tool as well as the target language, (ii) the implementation choices among the possible adjoint communications, and (iii) the currently known limitations of our approach. We hope for feedback from the community regarding this design particularly  with respect to performance and current developments in the MPI standard.

Laurent Hascoet

The adjoint of MPI one-sided communications
Computing gradients of numerical models by the adjoint mode of algorithmic differentiation is a crucial ingredient for model optimization, sensitivity analysis, and uncertainty quantification of many large-scale science and engineering applications. The adjoint mode implies a reversal of the data dependencies and consequently a reversal of communications in parallelized models. Building on previous studies regarding the adjoining of MPI The adjoint of MPI one-sided communications
Computing gradients of numerical models by the adjoint mode of algorithmic differentiation is a crucial ingredient for model optimization, sensitivity analysis, and uncertainty quantification of many large-scale science and engineering applications. The adjoint mode implies a reversal of the data dependencies and consequently a reversal of communications in parallelized models. Building on previous studies regarding the adjoining of MPI two-sided communications, we investigate the construction of adjoints for certain one-sided MPI communications

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Investigating the probability distribution of false negative failure alerts in HPC systems 

As large parallel systems increase in size and complexity, failures are inevitable and exhibit complex space and time dynamics. Several key results have demonstrated that recent advances in event log analysis can provide precise failure prediction. The state-of-the-art in failure prediction provides a ratio of correctly identified failures to the number of all predicted failures of over 90\% and its able to discover around 50\% of all failures in a system. However large part of failures are not predicted and considered as false negative alerts. Therefore, developing  efficient fault tolerance strategies to tolerate failures requires a good  perception and understanding of failure prediction properties and characteristics. In order to study and understand the properties and characteristics of the false negative alerts, we conduct in this paper a statistical analysis to discover the probability distribution of such alerts and their impact on fault tolerance techniques. To this end we study failures logs from different HPC production systems. We show that: (i) surprisingly the false negative distribution has the same nature as the failure distribution; (ii) after adding failure prediction we were able to infer statistical models that describes the inter arrival time between false negative alerts and so current fault tolerance can be applied on these systems; (iii) the current failures traces contain a high amount of correlation between the failure inter arrival time that can be used to improve the failure prediction mechanism. Another important result is that checkpoint intervals can still be computed from existing first order formula when failure distribution is purely random.

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In this talk, we revisit traditional checkpointing and rollback recovery strategies, with a focus on silent data corruption errors. Contrarily to fail-stop failures, such latent errors cannot be detected immediately, and a mechanism to detect them must be provided. We consider two models: (i) errors are detected after some delays following a probability distribution (typically, an Exponential distribution); (ii) errors are detected through some verification mechanism. In both cases, we compute the optimal period in order to minimize the waste, i.e., the fraction of time where nodes do not perform useful computations. In practice, only a fixed number of checkpoints can be kept in memory, and the first model may lead to an irrecoverable failure. In this case, we compute the minimum period required for an acceptable risk. For the second model, there is no risk of irrecoverable failure, owing to the verification mechanism, but the corresponding overhead is included in the waste. Finally, both models are instantiated using realistic scenarios and application/architecture parameters.

Dries Kimpe

Triton: Exascale Storage

In this talk, I will present a status update of our work on Triton, a newly designed exascale era storage system.  In addition to Triton specific information, the presentation will also include a brief discussion about the tools and techniques that help us in implementing and designing Triton. One such tool is the use of discrete event simulation to quickly evaluate algorithms at scale before implementing them in Triton.

Tatiana Martsinkevich

On the feasibility of message logging in hybrid hierarchical FT protocols

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Optimization of Google Cloud Task Processing with Checkpoint-Restart Mechanism  

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Modern hardware architectures featuring multicores and a complex memory hierarchy raise challenges that need to be addressed by parallel applications programmers. It is therefore tempting to adapt an application communication pattern to the characteristics of the underlying hardware. The MPI standard features several functions that allow the ranks of MPI processes to be reordered according to a graph attached to a newly created communicator. In this talk, we explain how the MPI implementation of the MPI_Dist_graph_create function was  modified to reorder the MPI process ranks to create a match between the application communication pattern and the hardware topology. The experimental results on a multicore cluster show that improvements can be achieved as long as the application communication pattern is expressed by a relevant metric. We also show several areas in MPI implementations where similar techniques can be beneficial.

Eddy Caron

Seed4C: Secured Embedded Element and Data privacy for Cloud Federation

In this talk we introduce the design of a secure federated cloud from end to end. We discussed the core of this platform based on a High Performance Computing middleware that uses federated clouds and other virtual resources as well classic HPC resources. We propose an architecture to ensure a high level of security from personal devices to the targeted virtual machine. The Seed4C platform improved security in each layer. With DIET Cloud, we are able to deploy a large-scale, distributed and secure HPC  platform that spans across a large pool of resources aggregated from different providers through a secure way