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A comparison of power management mechanisms: P-States vs. node-level power cap control

Proceedings - 2018 IEEE 32nd International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2018

Pedretti, Kevin P.; Grant, Ryan E.; Laros, James H.; Levenhagen, Michael J.; Olivier, Stephen L.; Ward, Harry L.; Younge, Andrew J.

Large-scale HPC systems increasingly incorporate sophisticated power management control mechanisms. While these mechanisms are potentially useful for performing energy and/or power-aware job scheduling and resource management (EPA JSRM), greater understanding of their operation and performance impact on real-world applications is required before they can be applied effectively in practice. In this paper, we compare static p-state control to static node-level power cap control on a Cray XC system. Empirical experiments are performed to evaluate node-to-node performance and power usage variability for the two mechanisms. We find that static p-state control produces more predictable and higher performance characteristics than static node-level power cap control at a given power level. However, this performance benefit is at the cost of less predictable power usage. Static node-level power cap control produces predictable power usage but with more variable performance characteristics. Our results are not intended to show that one mechanism is better than the other. Rather, our results demonstrate that the mechanisms are complementary to one another and highlight their potential for combined use in achieving effective EPA JSRM solutions.

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TYPE Conference Poster YEAR 2018
ScopusOSTIDOI

A cross-enclave composition mechanism for exascale system software

Proceedings of the 6th International Workshop on Runtime and Operating Systems for Supercomputers, ROSS 2016 - In conjunction with HPDC 2016

Evans, Noah; Pedretti, Kevin P.; Kocoloski, Brian; Lange, John; Lang, Michael; Bridges, Patrick G.

As supercomputers move to exascale, the number of cores per node continues to increase, but the I/O bandwidth between nodes is increasing more slowly. This leads to computational power outstripping I/O bandwidth. This growth, in turn, encourages moving as much of an HPC workflow as possible onto the node in order to minimize data movement. One particular method of application composition, enclaves, co-locates different operating systems and runtimes on the same node where they communicate by in situ communication mechanisms. In this work, we describe a mechanism for communicating between composed applications. We implement a mechanism using Copy onWrite cooperating with XEMEM shared memory to provide consistent, implicitly unsynchronized communication across enclaves. We then evaluate this mechanism using a composed application and analytics between the Kitten Lightweight Kernel and Linux on top of the Hobbes Operating System and Runtime. These results show a 3% overhead compared to an application running in isolation, demonstrating the viability of this approach.

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TYPE Conference Poster YEAR 2016
ScopusOSTIDOI

Achieving performance isolation with lightweight co-kernels

HPDC 2015 - Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing

Ouyang, Jiannan; Kocoloski, Brian; Lange, John; Pedretti, Kevin P.

Performance isolation is emerging as a requirement for High Performance Computing (HPC) applications, particularly as HPC architectures turn to in situ data processing and application composition techniques to increase system throughput. These approaches require the co-location of disparate workloads on the same compute node, each with different resource and runtime requirements. In this paper we claim that these workloads cannot be effectively managed by a single Operating System/Runtime (OS/R). Therefore, we present Pisces, a system software architecture that enables the co-existence of multiple independent and fully isolated OS/Rs, or enclaves, that can be customized to address the disparate requirements of next generation HPC workloads. Each enclave consists of a specialized lightweight OS cokernel and runtime, which is capable of independently managing partitions of dynamically assigned hardware resources. Contrary to other co-kernel approaches, in this work we consider performance isolation to be a primary requirement and present a novel co-kernel architecture to achieve this goal. We further present a set of design requirements necessary to ensure performance isolation, including: (1) elimination of cross OS dependencies, (2) internalized management of I/O, (3) limiting cross enclave communication to explicit shared memory channels, and (4) using virtualization techniques to provide missing OS features. The implementation of the Pisces co-kernel architecture is based on the Kitten Lightweight Kernel and Palacios Virtual Machine Monitor, two system software architectures designed specifically for HPC systems. Finally we will show that lightweight isolated co-kernels can provide better performance for HPC applications, and that isolated virtual machines are even capable of outperforming native environments in the presence of competing workloads.

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TYPE Conference Poster YEAR 2015
ScopusOSTI

An introduction to developing GitLab/Jacamar runner analyst centric workflows at Sandia

Robinson, Allen C.; Swan, Matthew S.; Harvey, Evan C.; Klein, Brandon T.; Lawson, Gary L.; Milewicz, Reed M.; Pedretti, Kevin P.; Schmitz, Mark E.; Warnock, Scott A.

This document provides very basic background information and initial enabling guidance for computational analysts to develop and utilize GitOps practices within the Common Engineering Environment (CEE) and High Performance Computing (HPC) computational environment at Sandia National Laboratories through GitLab/Jacamar runner based workflows.

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TYPE SAND Report YEAR 2022
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Results 1–25 of 218
Results 1–25 of 218